Fitbit Research Library

Title	Author	Year	Journal / Proceedings	Category	Device(s)	Population	Data Used
Amblyopia and adult health: a comprehensive analysis of long-term systemic, sensory and mental health comorbidities in a national cohort details	Lee, Kyoung A. Viola; Langholm, Carsten; Lin, Trevor; Jin, Kimberly; Aboobakar, Inas F.; Oke, Isdin; Whitman, Mary C.	2026	The British Journal of Ophthalmology	Case Study	Device unspecified	Adults	Steps, Energy Expenditure, Active Minutes/Active Zone Minutes
Assessing Wearable mHealth Adherence in Underserved Adolescents and its Associations With Physical Activity, Sports, and Safety Perceptions: Prospective Cohort Study details Link ↗	Nunez-Gaunaurd, Annabel, and Michele Raya	2026	JMIR mHealth and uHealth	Case Study	Flex	Adolescents	Steps, Intensity
Association of chronic disease risk and physical activity measured by wearable devices in the All of Us program details	Hou, Yu; Cui, Erjia; Lim, Kelvin; Chow, Lisa S.; Howell, Michael; Ikramuddin, Sayeed; Zhang, Rui	2026	Communications Medicine	Case Study	Device unspecified	Adults	Steps, Energy Expenditure, Intensity, Heart Rate
Behaviour Change for Physical Activity Is Feasible and Effective in Women Living with Metastatic Breast Cancer: A Pilot Two-Arm Randomised Trial details Link ↗	Mark Liu, Sharon Kilbreath, Jasmine Yee, Jane Beith, and Elizabeth Dylke	2026	Cancers (Basel)	Intervention	Inspire	Adults	Steps, Active Minutes/Active Zone Minutes
Comparing methods to measure wearable device adherence for physical activity monitoring for persons with autism: A prospective observational cohort study details	Tovin, Melissa M.; Madden, Sheila B.; Wu, Kaiwen; Nunez-Gaunaurd, Annabel	2026	Physiotherapy Theory and Practice	Intervention	Inspire 3	Adults, Adolescents	Steps, Heart Rate
Concurrent associations between visit-to-visit changes in actigraphy-based physical activity and cognitive aging in older adults details	Shankar, Ranjani P.; Saloner, Rowan; Chen, Coty; Cadwallader, Claire; VandeBunte, Anna M.; Diaz, Valentina; Callies, Lana; Lo, Carina; Licata, Sophia; Buxton, Jessica; Pham, Albert; Olzinski, Molly; Cobigo, Yann; Staffaroni, Adam M.; Rabinovici, Gil D.; Kramer, Joel H.; Casaletto, Kaitlin B.; Paolillo, Emily W.	2026	Neurobiology of Aging	Case Study	Flex 2, Inspire 2	Older Adults	Steps
Daily Step Count 2 Years After Anterior Cruciate Ligament Reconstruction and Associations With Cartilage Health and Knee Symptoms and Function details	Øiestad, Britt Elin; Williams, Ashley A.; Titchenal, Matthew R.; Lutz, Amelie M.; Chu, Constance R.	2026	Sports Health	Case Study	Charge HR	Patients	Steps
DEPRESS: Dataset on Emotions, Performance, Responses, Environment, and Satisfaction during COVID-19 details Link ↗	Xingtong Guo, Angela C Incollingo Rodriguez, Chao Wang, Elke A Rundensteiner, and Shichao Liu	2026	Scientific data vol. 13,1 331	Case Study	Inspire 2	Adults	Sleep, Steps, Energy Expenditure, Distance, Heart Rate
Digital health physical activity coaching for older family caregivers of persons with heart failure - TPA4You: Protocol for a pilot randomized controlled trial details Link ↗	Dawon Baik, Heather Coats, Blaine Reeder, Larry A Allen, and Catherine Jankowski	2026	Contemporary clinical trials communications	Intervention	Device unspecified	Older Adults	Sleep, Steps
Effects of a 90-Min Nap on Time-Motion Metrics and Psychophysiological Responses During Small-Sided Games in Professional Soccer Players details	Kerkeni, Mohamed; Boukhris, Omar; Kerkeni, Manel; Ammar, Achraf; Husain, Waqar; Zmijewski, Piotr; Jahrami, Haitham; Chtourou, Hamdi; Trabelsi, Khaled	2026	Scandinavian Journal of Medicine \& Science in Sports	Case Study	Charge 6	Adults	Sleep
Effects of combined GABA and L-theanine supplementation on sleep quality: an exploratory study details Link ↗	H Konno, K Naganuma, and Y Kamada	2026	European review for medical and pharmacological sciences	Case Study	Charge 5	Adults	Sleep, Steps, Heart Rate
Efficacy of Telehealth-Based Coaching to Improve Physical Activity and Overall Experience for Cancer Survivors: Secondary, Mixed Methods Analysis of a Randomized Controlled Trial details	Khairat, Saif; Kent, Erin E.; Geracitano, John; Mendis, Kaushalya; Zhou, Zhaoqiang; Bailey, Carly; Wood, William A.	2026	JMIR cancer	Intervention	Device unspecified	Patients	Steps, Energy Expenditure, Heart Rate, Active Minutes/Active Zone Minutes
Health outcomes after national acute sleep deprivation events among the American public details	Kelly, Neil J.; Chaudhary, Rahul; El Khoury, Wadih; Kalepalli, Nishita; Wang, Jesse; Patel, Priya; Chan, Irene N.; Rahman, Haris; Saiyed, Aisha; Shah, Anisha N.; McClung, Colleen A.; Okawa, Satoshi; Nouraie, Seyed Mehdi; Chan, Stephen Y.	2026	JCI insight	Case Study	Device unspecified	Adults	Sleep
Hierarchical heated markov modeling for synthesizing activity data from wearable devices details	Fang, Darren; Ruan, Dan	2026	Computational and Structural Biotechnology Journal	Methods	Inspire HR		Steps, Heart Rate
Implementation of wearable activity trackers in hospital rehabilitation: a feasibility study tailored to local settings details	Szeto, Kimberley; Arnold, John; Singh, Ben; Diestel-Feddersen, Peter; Edwards, Dominique; Cheary, Shannon; Lo Basso, Matthew; Maher, Carol	2026	BMC health services research	Intervention	Inspire 3	Patients	Steps, Intensity
Improving sleep health through sleep hygiene education in adults aged 50-80 years details Link ↗	Ashley M Pfeiffer, Craig Triplett, and Olivia Schaefers	2026	Frontiers in sleep	Intervention	Inspire 2 HR	Older Adults	Sleep
Neighborhood disadvantage and adolescent sleep health: a longitudinal population-based study details	Niu, Li; Tan, Luyao; Diaz, Angela; Xiao, Yunyu; Li, Yan; Wang, Yijie	2026	Lancet Regional Health. Americas	Case Study	Charge 2	Adolescents	Sleep
Older breast cancer survivors' exercise and support group program experiences and recommendations from the IMPROVE trial: a qualitative study details	Hundal, Jasmin; Williams, Dionne; Nock, Nora L.; Austin, Kristina; Bennet, Elizabeth; Cerne, Stephen; Moore, Halle C. F.; Petkac, Jean; Schmitz, Kathryn H.; Berger, Nathan A.; Owusu, Cynthia	2026	BMC cancer	Intervention	Blaze	Older Adults	User Friendliness
Older Latino adults' facilitators and barriers to reducing sedentary behavior following an individualized intervention details	Gaedecke, Tyler; Zahlan, Jana; Redondo-Sáenz, Diego; Marquez, David X.; Tintle, Nathan; Bronas, Ulf G.	2026	Ethnicity \& Health	Intervention	Device unspecified	Older Adults
Protocol for a single-arm, multi-component behavior change technique (BCT) intervention to develop a walking habit among caregivers for persons with Alzheimer disease and related dementias (ADRD) details Link ↗	Danielle Miller, Luis Jordan, Sherene Lambert, Ashley M Goodwin, Liron Sinvani, Alexandra Perrin, Ying Kuen Cheung, Karina W Davidson, and Mark J Butler	2026	Contemporary clinical trials	Intervention	Device unspecified	Adults	Steps
Screens, Teens, and Sleep: Is the Impact of Nighttime Screen Use on Sleep Driven by Physiological Arousal? details	Meredith-Jones, Kim A.; Haszard, Jillian J.; Galland, Barbara C.; Wickham, Shay-Ruby; Brosnan, Bradley J.; Russell-Camp, Takiwai; Taylor, Rachael W.	2026	Journal of Sleep Research	Case Study	Inspire 2	Adolescents	Heart Rate
Short-Term Effects of a Mobile Health Intervention on Healthy Behaviors and Cardiometabolic Health in Sedentary Employees: A Quasi-Experimental Study details Link ↗	Lin, Y., Lu, S., Lee, K., Ma, W., Ho, Y, Liao, W., Yang, H., and Hong, O.	2026	MIR mHealth and uHealth	Intervention	Charge 3	Adults	Steps, Energy Expenditure, Intensity
Steps to Health: Backward Walking Predicts Physical Activity Levels in Multiple Sclerosis details	VanNostrand, Michael; Monaghan, Patrick G.; Takla, Taylor N.; Fritz, Nora E.	2026	Neurorehabilitation and Neural Repair	Case Study	Versa	Adults	Steps
To what extent do cognitive abilities, conscientiousness, and physical activity predict academic performance? details Link ↗	Garner, Lauren D, and Matthew K Robison	2026	Acta psychologica	Case Study	Charge 5	Adults	Steps, Energy Expenditure, Distance, Intensity, Active Minutes/Active Zone Minutes
¡Mi Vida Saludable!: Results of a Randomized, Controlled, 2x2 Factorial Trial of an In-Person and eHealth Diet and Physical Activity Intervention in Latina Breast Cancer Survivors details	Greenlee, Heather; Santiago-Torres, Margarita; Contento, Isobel; Koch, Pamela A.; Rillamas-Sun, Eileen; Gray, Heewon L.; Brickman, Adam M.; Ogden Gaffney, Ann; Thomson, Cynthia A.; Crane, Tracy E.; Dominguez, Naxielly; Sepulveda, Jhack; Marín-Chollom, Amanda M.; Paul, Rachel; Shi, Zaixing; Ulanday, Kathleene T.; Accordino, Melissa; Camacho, Fernando J.; Crew, Katherine D.; Kalinsky, Kevin; Taback, Brett; Trivedi, Meghna S.; Hale, Christiane; Reaves, Brieyona; Beauchemin, Melissa P.; Castellano, Marisol; Fuentes, Yanette; Eddy, Martha; Bella, Ana Leon; Meisner, Allison; Hershman, Dawn L.	2025	Journal of the Academy of Nutrition and Dietetics	Intervention	Zip	Adults	Steps
A 10-week remote monitoring study of sleep features and their variability in individuals with and without ADHD details	Denyer, Hayley; Carr, Ewan; Deng, Qigang; Asherson, Philip; Bilbow, Andrea; Folarin, Amos; Groom, Madeleine J.; Hollis, Chris; Sankesara, Heet; Dobson, Richard Jb; Kuntsi, Jonna	2025	BMC psychiatry	Case Study	Charge 3	Adults, Children	Sleep
A culturally tailored community gardening approach to improving physical activity, fruit and vegetable consumption, and psychological health among African American women: A pre-post feasibility study details URL ↗	Canton, Imani; Jakachira, Vanesu; Blackman, Dawn; Rose, Heather; Aguiñaga, Susan	2025	Health Promotion Perspectives	Intervention	Charge 3	Adults	Sleep, Steps, Heart Rate
A Culturally Tailored mHealth Intervention (MobileMen App) to Promote Physical Activity in African American Men: Protocol for a Comparative Effectiveness Trial details	Nuss, Kayla; Brice, Amanda; Hebert, Callie; Nauta, Phillip; Stull, April J.; Swift, Damon L.; Griffith, Derek M.; Buller, David B.; Newton, Robert L.	2025	JMIR research protocols	Intervention	Charge 6	Adults	Steps, Intensity
A Dual In-Person and Remote Assessment Approach to Developing Digital End Points Relevant to Autism and Co-Occurring Conditions: Protocol for a Multisite Observational Study details URL ↗	Yorke, Isabel; Boatman, Charlotte A.; Roy Choudhury, Akash; Oakley, Bethany; Conde, Pauline; Sankesara, Heet; Ranjan, Yatharth; Rashid, Zulqarnain; Dineley, Judith; Downs, Johnny; Chatham, Christopher H.; Cummins, Nicholas; Folarin, Amos; Loth, Eva; Buitelaar, Jan; Murphy, Declan; Dobson, Richard; Simonoff, Emily	2025	JMIR Research Protocols	Intervention	Inspire 2	Adults, Children	Sleep, Steps, Heart Rate
A Multiple Technology-Based Physical Activity Intervention for Latina Adolescents: Results From the Chicas Fuertes Randomized Controlled Trial details	Carson, Jacob R.; Greenstadt, Emily; Olivera, Brittany; Dunsiger, Shira; Zive, Michelle; Higgins, Michael; Godino, Job; Marcus, Bess; Meyer, Dawn; Larsen, Britta	2025	JMIR mHealth and uHealth	Intervention	Inspire HR	Adolescents	Steps, Intensity, Heart Rate
A performance validation of six commercial wrist-worn wearable sleep-tracking devices for sleep stage scoring compared to polysomnography details URL ↗	Schyvens, An-Marie; Peters, Brent; Van Oost, Nina Catharina; Aerts, Jean-Marie; Masci, Federica; Neven, An; Dirix, Hélène; Wets, Geert; Ross, Veerle; Verbraecken, Johan	2025	Sleep Advances: A Journal of the Sleep Research Society	Usability	Charge 5	Adults	Sleep
A Personalized, Texting-Based Conversational Agent to Address Sleep Disturbance in Individuals Who Have Survived Breast Cancer: Protocol for a Pilot Waitlist Randomized Controlled Trial details	Tsai, Chi-Shan; Szewczyk, Warren; Drerup, Michelle; Liao, Jason; Vasbinder, Alexi; Greenlee, Heather; Heffner, Jaimee L.; Yung, Rachel; Reding, Kerryn W.	2025	JMIR research protocols	Intervention	Charge 4	Adults	Sleep
A pilot exercise intervention to evaluate the role of cardiorespiratory fitness in modulating cardiotoxicity among childhood cancer survivors exposed to anthracycline therapy details	Toro-Salazar, Olga H.; Pescatello, Linda S.; Mah, May Ling; Wilhelm, Carolyn; Orsey, Andrea D.; Berthod, Tiffany; Mosha, Maua H.; Brimacombe, Michael; Fan, Tongyao; Wanner, Corbinian; Slawinski, Michelle; Hor, Kan N.	2025	Cardio-Oncology (London, England)	Intervention	Alta HR	Adults, Children	Steps, Intensity, Heart Rate, Active Minutes/Active Zone Minutes
A randomized comparative effectiveness trial to evaluate two programs for promotion of physical activity after spinal cord injury in manual wheelchair users details	Martinez, Jenna M.; Haubert, Lisa L.; Eberly, Valerie J.; Weiss, Walter B.; Rankin, Jeffery W.	2025	Frontiers in Sports and Active Living	Intervention	Blaze, Versa	Adults	Steps, Heart Rate, Active Minutes/Active Zone Minutes
A remotely delivered exercise-based rehabilitation program for patients with persistent chemotherapy-induced peripheral neuropathy (EX-CIPN): Protocol for a phase I feasibility trial details	Antonen, Eric M.; Nadler, Michelle B.; Langelier, David M.; Campbell, Kristin L.; Flamer, David; Cho, Jang Hyuk; Capozza, Scott; Avery, Lisa; Bland, Kelcey A.; Leatherdale, Scott; Manthorne, Jackie; Jones, Jennifer M.	2025	PloS One	Intervention	Device unspecified	Patients	Steps, User Friendliness
A Series of Personalized Melatonin Supplement Interventions for Poor Sleep: Feasibility Randomized Crossover Trial for Personalized N-of-1 Treatment details URL ↗	Butler, Mark J.; Chandereng, Thevaa; Ahn, Heejoon; Slotnick, Stefani; Miller, Danielle; Perrin, Alexandra; Rodillas, Jordyn; Friel, Ciaran P.; Goodwin, Ashley M.; Cheung, Ying Kuen; Davidson, Karina W.	2025	JMIR Formative Research	Intervention	Charge 5	Adults	Sleep
Accelerometers can correctly count orthopaedic patients' early post-operative steps while using walking aids details	Tsamassiotis, Spiros; Schwarze, Michael; Gehring, Philipp; Karkosch, Roman F.; Tücking, Lars-René; Einfeldt, Ann-Kathrin; Jakubowitz, Eike	2025	Journal of Experimental Orthopaedics	Case Study	Charge 3, Garmin Vivofit 4	Adults	Steps
Acceptability and Preliminary Efficacy of a Novel Web-Based Physical Activity for the Heart (PATH) Intervention Designed to Promote Physical Activity in Adults With Obesity: Protocol for a Pilot Randomized Controlled Trial details	Kariuki, Jacob; Burke, Lora; Erickson, Kirk; Sereika, Susan; Paul, Sudeshna; Cheng, Jessica; Biza, Heran; Abdirahman, Amjad; Wilbraham, Katherine; Milton, Heather; Brown, Cornelius; Sells, Matthew; Osei Baah, Foster; Wells, Jessica; Chandler, Rasheeta; Barone Gibbs, Bethany	2025	JMIR research protocols	Intervention	Device unspecified	Adults	Steps
Acceptability of the Fit2ThriveMB mHealth physical activity promotion intervention in women with metastatic breast cancer details	Starikovsky, Julia; Solk, Payton; Desai, Ria; Reading, Jean M.; Hasanaj, Kristina; Wang, Shirlene D.; Carden, Lillian B.; Wolter, Melanie; Hickey, Brendan; Lee, Jungwha; Song, Jing; Freeman, Hannah; Alexander, Jacqueline; Spring, Bonnie; Gradishar, William; Phillips, Siobhan M.	2025	Supportive Care in Cancer: Official Journal of the Multinational Association of Supportive Care in Cancer	Intervention	Inspire HR	Patients	Steps
Activity tracking devices in pregnancy: Understanding the participant experience in a longitudinal birth cohort details	Redding, Ashley; Coates, Dionne; Cassidy-Bushrow, Andrea E.; Straughen, Jennifer K.; Santarossa, Sara	2025	Women's Health (London, England)	Intervention	Charge 4, Charge 5	Pregnant Women	Sleep, Steps, Heart Rate
Addressing Low Physical Activity in COPD: The Importance of Patients' Symptom Perception details	Zo, Sungmin; Kang, Danbee; Kong, Sung A.; Shin, Sun Hye; Lee, Jiseon; Do, Jong Geol; Park, Hye Yun	2025	Tuberculosis and Respiratory Diseases	Case Study	Charge 4	Patients	Steps, Intensity
Adherence to Accelerometer Use in Older Adults Undergoing mHealth Cardiac Rehabilitation: Secondary Analysis of a Randomized Clinical Trial details	Barua, Souptik; Upadhyay, Dhairya; Pena, Stephanie; McConnell, Riley; Varghese, Ashwini; Adhikari, Samrachana; LeRoy, Erik; Schoenthaler, Antoinette; Dodson, John A.	2025	Journal of Medical Internet Research	Intervention	Inspire, Inspire 2	Older Adults	Steps, Distance, Intensity, Device Weartime
Adolescent smartphone use, sleep, and physical activity: daily associations between sensor-based measures in the adolescent brain cognitive development (ABCD) study details	Alexander, Jordan D.; Nguyen-Louie, Tam T.; Gupta, Suhaani; Cummins, Kevin M.; Wade, Natasha E.	2025	Psychiatry Research	Case Study	Charge	Adolescents	Sleep, Steps, Device Weartime
AirPredict: an eHealth platform for asthma management leveraging wearable sensors, digital diaries, and air quality monitoring to optimize patient outcomes details	Atzeni, Michele; Cossu, Luca; Gaiotti, Sergio; Cappon, Giacomo; Tinè, Mariaenrica; Previtero, Daniele; Padrin, Ylenia; Baraldo, Simonetta; Semenzato, Umberto; Vettoretti, Martina	2025	Frontiers in Digital Health	Intervention	Charge 6	Patients	Heart Rate
American Life in Realtime: Benchmark, publicly available person-generated health data for equity in precision health details URL ↗	Chaturvedi, Ritika R.; Angrisani, Marco; Troxel, Wendy M.; Jain, Monika; Gutsche, Tania; Ortega, Eva; Boch, Adrien; Liang, Citina; Sima, Shiyang; Mezlini, Aziz; Daza, Eric J.; Boodaghidizaji, Miad; Suen, Sze-chuan; Chaturvedi, Alok R.; Ghasemkhani, Hossein; Ardekani, Arezoo M.; Kapteyn, Arie	2025	PNAS Nexus	Case Study	Inspire 2	Older Adults	Sleep, Steps, Heart Rate
An approach to boost adherence to self-data reporting in mHealth applications for users without specific health conditions details	Aguiar, Maria; Cejudo, Ander; Epelde, Gorka; Chaves, Deisy; Trujillo, Maria; Artola, Garazi; Ayala, Unai; Bilbao, Roberto; Tueros, Itziar	2025	BMC medical informatics and decision making	Case Study	Device unspecified	Adults	Steps, Energy Expenditure
An Example Analysis for a Gender-inclusive Approach in Sport and Exercise Science Research using Fitbit Outcomes from the All of Us Research Program Dataset details	Navalta, James W.; Davis, Dustin W.; Thomas, Jafra D.; Stone, Whitley J.	2025	International Journal of Exercise Science	Survey Research	Device unspecified	Adults	Steps, Energy Expenditure, Heart Rate, Active Minutes/Active Zone Minutes
Analysis of influencing factors of sleep quality in severe trauma patients without continuous sedation details	Jin, Yue; Wang, Shuya	2025	Frontiers in Medicine	Case Study	Charge 2	Patients	Sleep, Heart Rate
Assessment of Sleep Measures and their agreement: Youth-Reported, Caregiver-Reported, and Fitbit-Derived Data in a Large Early Adolescent Cohort details	Kiss, Orsolya; Shaska, Adrianna; Müller-Oehring, Eva M.; Hasler, Brant P.; Franzen, Peter L.; Fitzgerald, Douglas H.; Clark, Duncan B.; Baker, Fiona C.	2025	Sleep	Case Study	Charge 2	Adolescents	Sleep
Association between working conditions during the COVID-19 pandemic and sleep and stress among Colombian healthcare workers details	Carrillo-González, Andrés; Cantor-Cutiva, Lady Catherine	2025	Archives of Environmental \& Occupational Health	Case Study	Device unspecified	Adults	Sleep
Associations between objective and self-perceived physical activity and participation in everyday activities in mild stroke survivors details	de Diego-Alonso, Cristina; Alegre-Ayala, Jorge; Blasco-Abadía, Julia; Doménech-García, Víctor; Part\&Sed-Stroke collaborators’; Bellosta-López, Pablo	2025	PloS One	Case Study	Inspire 2	Adults	Steps, Energy Expenditure
At-home Breast Oncology care Delivered with EHealth solutions (ABODE) study protocol: a randomised controlled trial details	Mac, Amanda; Kalia, Mohini; Reel, Emma; Amir, Eitan; Isenberg, Adina; Kim, Raymond H.; Kennedy, Erin; Koch, C. Anne; Li, Madeline; McCready, David; Metcalfe, Kelly; Okrainec, Allan; Papadakos, Janet; Rotstein, Sarah; Rodin, Gary; Xu, Wei; Zhong, Toni; ABODE Study Group; Cil, Tulin D.	2025	BMJ open	Intervention	Device unspecified	Patients	Steps, Heart Rate
Capturing Real-World Habitual Sleep Patterns With a Novel User-Centric Algorithm to Preprocess Fitbit Data in the All of Us Research Program: Retrospective Observational Longitudinal Study details	Master, Hiral; Annis, Jeffrey; Ching, Jack H.; Gleichauf, Karla; Han, Lide; Coleman, Peyton; Full, Kelsie M.; Zheng, Neil; Ruderfer, Douglas; Hernandez, John; Schneider, Logan D.; Brittain, Evan L.	2025	Journal of Medical Internet Research	Validation	Device unspecified	Adults	Sleep
Changing User Experience of Wearable Activity Monitors Over 7 Years: Repeat Cross-Sectional Survey Study details	Beckett, Darcy; Curtis, Rachel; Szeto, Kimberley; Maher, Carol	2025	Journal of Medical Internet Research	Usability, Survey Research	Device unspecified	Adults	Device Weartime
Characterization and clustering of intra-day physical activity patterns using accelerometry among sexual and gender minority adults details	Lopez-Veneros, David; Caceres, Billy A.; Jackman, Kasey; Belloir, Joseph A.; Sharma, Yashika; Bakken, Suzanne; Ensari, Ipek	2025	BMC public health	Case Study	Inspire 2	Adults	Steps, Intensity
Characterization of Post-Viral Infection Behaviors Among Patients With Long COVID: Prospective, Observational, Longitudinal Cohort Analyses of Fitbit Data and Patient-Reported Outcomes details	Zhang, Tianmai M.; Sharp, Sydney P.; Scott, John D.; Taren, Douglas; Samaniego, Jane C.; Unger, Elizabeth R.; Bertolli, Jeanne; Lin, Jin-Mann S.; Ramers, Christian B.; Godino, Job G.	2025	JMIR formative research	Case Study	Charge 5	Adults, Patients	Sleep, Steps, Heart Rate
Characterizing proximal risk for depressive symptoms and suicidal ideation with acute cannabis use and withdrawal among adolescents using ecological momentary assessment: Study protocol details	Feibus, Isabella; Mahiques, Marta Borrego; Costello, Meghan; Potter, Kevin; Bentley, Kate H.; Hoeppner, Bettina B.; Liu, Luwei; Evohr, Bryn; Yan, Lynn; Gilman, Jodi; Evins, A. Eden; Kossowsky, Joe; Schuster, Randi M.	2025	PloS One	Case Study	Inspire 3	Adolescents	Sleep, Steps
Circadian rhythm of heart rate and activity: A cross-sectional study details	Natarajan, Aravind; Gleichauf, Karla; Khalid, Maryam; Heneghan, Conor; Schneider, Logan Douglas	2025	Chronobiology International	Case Study	Versa 2, Inspire 2, Sense, Versa 3, Charge 5, Sense 2, Inspire 3, Fitbit Luxe, Versa 4	Adults	Heart Rate
Comparing the Accuracy of Different Wearable Activity Monitors in Patients With Lung Cancer and Providing Initial Recommendations: Protocol for a Pilot Validation Study details	Benzo, Roberto M.; Singh, Rujul; Presley, Carolyn J.; Tetrick, Macy K.; Chaplow, Zachary L.; Hery, Chloe M.; Yu, Jane; Washington, Peter; Penedo, Frank J.; Paskett, Electra D.; Lugade, Vipul; Fortune, Emma	2025	JMIR research protocols	Validation	Charge 6	Adults	Steps, Intensity
Concurrent Validity of a Physical Activity Vital Sign Used in an Adult Preventive Cardiology Clinic details	McCarthy, Margaret; Fletcher, Jason; Melkus, Gail; Vorderstrasse, Allison; Chehade, Mireille; Katz, Stuart	2025	Nursing Research	Validation	Device unspecified	Patients	Steps, Distance
Considerations in using heart rate-based physical activity estimates from consumer wearables in individuals with varying weight status details	Brown, Denver M. Y.; Wing, David; Pfledderer, Christopher D.; Stoepker, Peter; Fairclough, Stuart J.; Carlson, Jordan A.	2025	The International Journal of Behavioral Nutrition and Physical Activity	Case Study	Device unspecified	Adolescents	Intensity, Heart Rate
Consumer-facing and professional medical devices in cardiology: monitoring and evaluation of big data and the implications for the practice of cardiology details URL ↗	Nuvvula, Sri; Makaryus, Amgad N.	2025	Expert Review of Medical Devices	Review	Device unspecified	Patients	Heart Rate
Contexts, affective and physical states and their variations during physical activity in older adults: an intensive longitudinal study with sensor-triggered event-based ecological momentary assessments details	Delobelle, Julie; Compernolle, Sofie; Vetrovsky, Tomas; Van Cauwenberg, Jelle; Van Dyck, Delfien	2025	The International Journal of Behavioral Nutrition and Physical Activity	Intervention	Inspire 2, Ionic	Older Adults	Steps
Continuous heart rate measurements in patients with cardiac disease: Device comparison and development of a novel artefact removal procedure details	Vermunicht, Paulien; Makayed, Katsiaryna; Buyck, Christophe; Knaepen, Lieselotte; Piedrahita Giraldo, Juan Sebastian; Naessens, Sebastiaan; Hens, Wendy; Craenenbroeck, Emeline Van; Laukens, Kris; Desteghe, Lien; Heidbuchel, Hein	2025	Digital Health	Validation	Inspire 2	Patients	Intensity, Heart Rate
Cross-evaluation of wearable data for use in Parkinson's disease research: a free-living observational study on Empatica E4, Fitbit Sense, and Oura details	Reithe, Haakon; Marty, Brice; Torrado, Juan C.; Førsund, Elise; Husebo, Bettina S.; Erdal, Ane; Kverneng, Simon U.; Sheard, Erika; Tzoulis, Charalampos; Patrascu, Monica	2025	Biomedical Engineering Online	Usability	Sense	Adults	Steps, Energy Expenditure, Intensity, Heart Rate
Daily Heart Rate per Step: A Wearables Metric Associated With Cardiovascular Disease in a Cross-Sectional Study of the All of Us Research Program details	Chen, Zhanlin; Wang, Charles T.; Hu, Carolyn J.; Ward, Kendra; Kho, Abel; Webster, Gregory	2025	Journal of the American Heart Association	Intervention	Device unspecified	Adults	Steps, Heart Rate
Data from the All of Us research program reinforces existence of activity inequality details	Jeong, Hayoung; Roghanizad, Ali R.; Master, Hiral; Kim, Juseong; Kouame, Aymone; Harris, Paul A.; Basford, Melissa; Marginean, Kayla; Dunn, Jessilyn	2025	NPJ digital medicine	Case Study	Charge 4, Versa 3	Adults	Steps, Heart Rate
Design and baseline characteristics of an implementation study to increase activity with social incentives: The STEP together trial details	Scheffey, Krista; Aronson, Joshua; Goncalves, Yolande; Greysen, S. Ryan; Iwu, Ashley; Kwong, Pui L.; Nezir, Freya; Small, Dylan; Glanz, Karen	2025	Contemporary Clinical Trials	Intervention	Inspire 2, Inspire 3	Adults, Older Adults	Steps, Intensity, Goals
Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study details	Kim, Jeong-Kyun; Mun, Sujeong; Lee, Siwoo	2025	JMIR medical informatics	Case Study	Inspire 2	Adults	Sleep, Steps, Heart Rate
Dialysis-Imposed Patterns of Nocturnal Sleep Duration: A Multi-Center Prospective Study in Patients Using a Wearable Activity Tracker details	Han, Maggie; van der Sande, Frank M.; Kooman, Jeroen P.; Tao, Xia; Preciado, Priscila; Tisdale, Lela; Thwin, Ohnmar; Kotanko, Peter	2025	Kidney360	Case Study	Charge 2	Patients	Sleep
Digital Fitness Revolution: User Perspectives on Fitbit's Role in Health Management details	Jang, Seong-Bin; Kim, Minseong	2025	Behavioral Sciences (Basel, Switzerland)	Validation, Review	Charge 4		Sleep, Steps, Heart Rate
Digital Health Intervention to Reduce Malnutrition Among Individuals With Gastrointestinal Cancer Receiving Cytoreductive Surgery Combined With Hyperthermic Intraperitoneal Chemotherapy: Feasibility, Acceptability, and Usability Trial details	Lin, Yu Chen; Hagen, Ryan; Powers, Benjamin D.; Dineen, Sean P.; Milano, Jeanine; Hume, Emma; Sprow, Olivia; Diaz-Carraway, Sophia; Permuth, Jennifer B.; Deneve, Jeremiah; Alishahi Tabriz, Amir; Turner, Kea	2025	JMIR cancer	Intervention	Inspire 2	Adults	Food
Digital, Personalized Clinical Trials Among Older Adults, Lessons Learned From the COVID-19 Pandemic, and Directions for the Future: Aggregated Feasibility Data From Three Trials Among Older Adults details	Arader, Lindsay; Miller, Danielle; Perrin, Alexandra; Vicari, Frank; Friel, Ciaran P.; Vrany, Elizabeth A.; Goodwin, Ashley M.; Butler, Mark	2025	Journal of Medical Internet Research	Systematic Review	Device unspecified	Adults, Older Adults	Steps, User Friendliness, Device Weartime
Do Patients Sleep Better at Home or in the Hospital Following Primary Total Joint Arthroplasty? details	Liao, Gerald Y.; Chansky, Howard; Manner, Paul A.; Brinkmann, Elyse; Fernando, Navin D.; Hernandez, Nicholas M.	2025	The Journal of Arthroplasty	Case Study	Inspire 2	Patients	Sleep
Dog Owners Exhibit Better Diet Quality but Similar Physical Activity Compared to Non-Owners: A Case-Control Study details	Margaritis, Konstantinos Lazaridis; Perantonaki, Marilena; Pyrga, Katerina; Pardali, Eleni C.; Poulimeneas, Dimitrios; Goulis, Dimitrios G.; Tsigga, Maria; Grammatikopoulou, Maria G.	2025	Nutrients	Case Study	Zip	Adults	Steps
Ecological momentary assessment of physical and eating behaviours: The WEALTH feasibility and optimisation study with recommendations for large-scale data collection details	Janek, Michael; Kuhnova, Jitka; Cardon, Greet; Van Dyck, Delfien; Cimler, Richard; Elavsky, Steriani; Fezeu, Leopold K.; Oppert, Jean-Michel; Buck, Christoph; Hebestreit, Antje; Harrington, Janas; Sigcha, Luis; Van de Ven, Pepijn; Donnelly, Alan; Vetrovsky, Tomas; WEALTH consortium	2025	PloS One	Intervention	Charge 5	Adults	Steps, Heart Rate
Effect of arthroscopic repair on sleep disturbances in rotator cuff tear patients: A prospective cohort study analyzing short-term postoperative pain correlations details	Kim, Hyojune; Lee, Jangwon; Koh, Kyoung Hwan	2025	Journal of Orthopaedic Surgery (Hong Kong)	Case Study	Inspire 2	Patients	Sleep
Effect of Cannabigerol on Sleep and Quality of Life in Veterans: A Decentralized, Randomized, Placebo-Controlled Trial details URL ↗	Emerson, Chris R.; Webster, Courtney E.; Daza, Eric J.; Klamer, Brett G.; Tummalacherla, Meghasyam	2025	Medical Cannabis and Cannabinoids	Case Study	Inspire 2	Adults	Sleep
Effect of Intraoperative Intravenous Infusion of Esketamine Combined with Dexmedetomidine on Postoperative Sleep Disturbance in Patients Undergoing Radical Mastectomy details URL ↗	Geng, Xingyu; Pu, Yutian; Hu, Ziwei; Zhang, Heling; Wang, Maosan; Fang, Can; Lv, Gaochao; Li, Wanting; Zhang, Xinyue; Fan, Xiaoxuan; Liu, Su; Chen, Xiuxia; Wu, Jingru	2025	Drug Design, Development and Therapy	Case Study	Charge 2	Patients	Sleep
Effectiveness of an mHealth-based impact exercise program for bone health in postmenopausal women: a randomised controlled trial protocol details	Sañudo, Borja; Reverte-Pagola, Gonzalo; Maher, Carol; Godino, Job; Carrasco, Luis; Oviedo, Miguel Ángel; Feria, Adrián; Sánchez-Trigo, Horacio; Gamboa, Hugo; Domingo-Molina, Raquel; Sánchez-Arteaga, Alejandro; Giráldez, Miguel Ángel; Martínez-Maestre, Mª Ángeles; Cepeda, Elena; Ladrón-de-Guevara, Carmen; Rangel, Carlos; Pecci, Javier; Farrahi, Vahid; Tejero, Sergio	2025	BMC public health	Intervention	Versa 3	Pregnant Women	Steps, Intensity
Effectiveness of PEER Intervention on Older Adults' Physical Activity Time Series Using Smoothing Spline ANOVA details	Liu, Yi; Liu, Chang; Ni, Liqiang; Zhang, Wei; Chen, Chen; Lopez, Janet; Zheng, Hao; Thiamwong, Ladda; Xie, Rui	2025	Mathematics (Basel, Switzerland)	Intervention	Charge 5	Older Adults	Intensity, Active Minutes/Active Zone Minutes
Effects of a Valerian‐Hops Extract Combination (Ze 91019) on Sleep Duration and Daytime Cognitive and Psychological Parameters in Occasional Insomnia: A Randomized Controlled Feasibility Trial details URL ↗	Schicktanz, Nathalie; Gerhards, Christiane; Schlitt, Thomas; Aerni, Amanda; Müggler, Elia; de Quervain, Dominique; Papassotiropoulos, Andreas; Boonen, Georg; Drewe, Juergen; Butterweck, Veronika	2025	Brain and Behavior	Case Study	Charge 5	Adults	Sleep
Effects of pre- and post-surgery physical activity interventions on physical activity and sedentary behaviour levels following knee and hip arthroplasty: A systematic review and meta-analysis of randomised controlled trials details	d'Unienville , Noah; Singh, Ben; Gower, Bethany; Szeto, Kimberley; Badger, Heather; Krywanio, Matilda; Maher, Carol; Thewlis, Dominic	2025	Osteoarthritis and Cartilage	Systematic Review	Device unspecified	Patients	Steps, Energy Expenditure, Intensity
Effects of Virtual Reality Meditation on Sleep and Delirium in ICU Patients: A Randomized Controlled Trial details	Kim, Soogyeong; Kang, Jiyeon	2025	Computers, informatics, nursing: CIN	Intervention	Charge 3	Patients	Sleep
Effects of web platform delivery of a physical activity program for breast cancer survivors: a randomized controlled trial details URL ↗	Pinto, Bernardine M.; Kindred, Madison; Dunsiger, Shira; Mitchell, Sheryl; Patel, Ashwin; Ostendorf, Danielle; Huebschmann, Amy G.	2025	Journal of Cancer Survivorship	Intervention	Inspire 2	Adults	Intensity, Active Minutes/Active Zone Minutes
Engagement in a digital health physical activity program, TPA4You, among older family care partners of persons with heart failure: A Scenario-based design details	Baik, Dawon; Allen, Larry A.; Coats, Heather; Matlock, Daniel D.; Jankowski, Catherine	2025	Geriatric Nursing (New York, N.Y.)	Intervention	Device unspecified	Older Adults	User Friendliness
Engagement of African American Women With Fitness Trackers and Mobile Technology for Shared Physical Activity Goals: Mixed Methods Study details	Sweeney, Allison; Simmons, Timothy; Nair, Anika; Decker, Lindsay	2025	JMIR mHealth and uHealth	Intervention	Inspire	Adults	Steps, Intensity
Enhancing Interpretable, Transparent, and Unobtrusive Detection of Acute Marijuana Intoxication in Natural Environments: Harnessing Smart Devices and Explainable AI to Empower Just-In-Time Adaptive Interventions: Longitudinal Observational Study details	Bae, Sang Won; Chung, Tammy; Zhang, Tongze; Dey, Anind K.; Islam, Rahul	2025	Jmir Ai	Case Study	Charge 2	Adults	Sleep, Steps, Heart Rate
Enhancing Physical Activity in Older Adults More Than 6 Months Post Total Hip or Knee Replacement Through Telerehabilitation: A Pilot Randomized Controlled Trial details URL ↗	Takenaka, Hiroto; Ida, Kunio; Goto, Shin; Suzuki, Junya	2025	Journal of Aging and Physical Activity	Intervention	Sense	Older Adults	Steps, Intensity, Active Minutes/Active Zone Minutes
Evaluating Fitbits for Assessment of Physical Activity and Sleep in Pediatric Pain: Feasibility and Acceptability Pilot Study details	Nestor, Bridget A.; Baumer, Andreas M.; Chimoff, Justin; Delecourt, Benoit; Koike, Camila; Tacugue, Nicole; Brusseau, Roland; Roy, Nathalie; Gaytan-Fuentes, Israel A.; Sethna, Navil; Wallace, Danielle; Kossowsky, Joe	2025	JMIR formative research	Usability	Charge 3, Inspire 2	Children, Adolescents	Sleep, Steps, Heart Rate, Device Weartime
Evaluating the role of interpersonal support on daily physical activity across systems, contexts, and time among African American women: an ecological momentary assessment study details URL ↗	Sweeney, Allison M.; Prine, Halle; Yang, Chih-Hsiang; Wilson, Dawn K.; Forthofer, Melinda; Martin, Pamela	2025	Annals of Behavioral Medicine	Intervention	Inspire	Adults	Steps, Goals, Active Minutes/Active Zone Minutes
Evaluation of an integrated digital and mobile intervention to improve outcomes for patients with moderate to severe COPD details	O'Connor, Laurel; Wang, Biqi; Ye, Zehao; Behar, Stephanie; Tarrant, Seanan; Stamegna, Pamela; Pretz, Caitlin; Dunkel, Leah; Savage, Brandon; Scornavacca, Thomas; Shirshac, Jeanne; Wilkie, Tracey; Toomey, Shaun; Mullen, Marie; Fisher, Kimberly; Tigas, Emil; Wong, Steven; McManus, David D.; Alper, Eric; Martinez, Fernando; Walkey, Allan; Lindenauer, Peter K.; Dickson, Eric; Broach, John P.; Kheterpal, Vik; Soni, Apurv	2025	NPJ digital medicine	Intervention	Charge 5	Patients
Evening preference with evening-type rest-activity rhythm: a risk for poor quality of life details	Mun, Sujeong; Kim, Jeong-Kyun; Baek, Younghwa; Park, Kihyun; Lee, Siwoo	2025	Health and Quality of Life Outcomes	Case Study	Inspire 2	Adults	Steps
Examining the Agreement Between Subjective and Objective Measures of Sleep: A Comparison of Munich Chronotype Questionnaire and Fitbit-Derived Sleep Metrics details	Rohr, Kayla E.; Thomas, Michael L.; McCarthy, Michael J.; Meruelo, Alejandro D.	2025	Journal of Sleep Research	Usability	Device unspecified	Adolescents	Sleep, Heart Rate
Exploring the Psychological and Physiological Insights Through Digital Phenotyping by Analyzing the Discrepancies Between Subjective Insomnia Severity and Activity-Based Objective Sleep Measures: Observational Cohort Study details	Yeom, Ji Won; Kim, Hyungju; Pack, Seung Pil; Lee, Heon-Jeong; Cheong, Taesu; Cho, Chul-Hyun	2025	JMIR mental health	Case Study	Inspire 3	Adults	Sleep, Steps, Heart Rate
Exploring the relative importance of the factors associated with menopausal symptoms using a random forest model: a cross-sectional study details	Chin, Meejung; Hahn, Sowon; Kim, Yeon Soo; Kwon, Young Hye; Park, Yeon-Hwan; Choi, Younghwan; Kim, Gahye; Kim, Youjin; Lee, Inju; Yoon, Hyun Jeong; Bae, Hanjin	2025	Women's Health Nursing (Seoul, Korea)	Case Study	Charge 5	Adults	Steps
Feasibility and Cultural Adaptation of a Community-Engaged Physical Activity Intervention for Hispanic Older Adults: Pilot Study details URL ↗	Zlatar, Zvinka Z.; Greenwood-Hickman, Mikael Anne; Lujan, Lazaro N. Martinez; Cooper, Julie; Florez-Acevedo, Stefani; Marquez, David X.; Aceves, Rosa Gutierrez; Vargas, Andrea Paula; Rosenberg, Dori E.	2025	JMIR Formative Research	Intervention	Inspire 2	Adults	Steps, Goals, Active Minutes/Active Zone Minutes
Feasibility of an Individualized Exercise Training Program for Children with Hypertrophic Cardiomyopathy details	Wanner, Julianne; Burstein, Danielle; Paridon, Stephen; Shah, Maully; O'Malley, Shannon; Lin, Kimberly Y.; Edelson, Jonathan B.	2025	Pediatric Cardiology	Intervention	Device unspecified	Children	Heart Rate
Feasibility of Data Collection Via Consumer-Grade Wearable Devices in Adolescent Student Athletes: Prospective Longitudinal Cohort Study details URL ↗	Ransom, Danielle; Tudor, Brant; Irani, Sarah; Rehman, Mohamed; Suskauer, Stacy; Mularoni, P. Patrick; Ahumada, Luis	2025	JMIR Formative Research	Usability	Sense	Adolescents	Sleep, Steps, Heart Rate, Active Minutes/Active Zone Minutes
Feasibility trial of STRONG: A digital intervention to improve nutritional management for individuals with esophageal and gastroesophageal junction cancer details	Lin, Yu Chen; Pimiento, Jose M.; Milano, Jeanine; Riccardi, Diane; Mckinnie, Nakesha; Hume, Emma; Sprow, Olivia; Diaz-Carraway, Sophia; Budnetz, Mara; Hagen, Ryan; Al-Jumayli, Mohammed; Pereira, Allan Lima; Sinnamon, Andrew J.; Somasundaram, Ashwin; Permuth, Jennifer B.; Tabriz, Amir Alishahi; Turner, Kea	2025	Contemporary Clinical Trials Communications	Intervention	Inspire 2	Adults	Food
Fit4Surgery: A pilot randomized controlled trial to assess the feasibility of prehabilitation prior to debulking surgery for ovarian cancer details	Silberman, Jason N.; Benjamin, Annella; Solk, Payton; Matei, Daniela; Alter, Raanan; Hinchcliff, Emily; Roque, Dario; Marcus, Jenna; Tanner, Edward; McKoy, June M.; Flores, Ann Marie; Kocherginsky, Masha; Phillips, Siobhan; Barber, Emma	2025	Gynecologic Oncology	Usability, Case Study	Device unspecified	Patients	Steps
Fitbit Physical Activity and Sleep Data in the All of Us Research Program: Data Exploration and Processing Considerations for Research details	Bailey, Caitlin P.; Dodd, Kevin W.; McClain, James J.; Seo, Isabell; Wheeler, William; Wolff-Hughes, Dana L.	2025	Medicine and Science in Sports and Exercise	Survey Research	One, Zip, Flex, Charge, Surge, Blaze, Alta, Inspire, Versa, Sense, Ionic, Fitbit Luxe	Adults	Sleep, Steps, Intensity, Heart Rate
Fitbit-measured physical activity is inversely associated with incident atrial fibrillation among All of Us participants details URL ↗	Barua, Souptik; Upadhyay, Dhairya; Surapaneni, Aditya; Grams, Morgan; Jankelson, Lior; Heffron, Sean	2025	American Heart Journal	Survey Research	Device unspecified	Adults	Intensity
Fitbit-Measured Sleep Duration in Young Adolescents is Associated with Functional Connectivity in Attentional, Executive Control, Memory, and Sensory Networks details	Turan, Ozerk; Garner, Jonathan; Isaiah, Amal; Palatino, Maylin; Ernst, Thomas; Wang, Ze; Chang, Linda	2025	Sleep	Case Study	Device unspecified	Adolescents	Sleep
Frailty is associated with low physical activity and poor sleep quality in patients undergoing myeloablative allogeneic hematopoietic cell transplantation: a Fitbit® pilot study details	Libbert, Caryn R.; He, Fiona; El Jurdi, Najla; Fagrelius, Helen; Juckett, Mark; Maakaron, Joseph; Juckett, William; Evanoff, Nicholas; Dengel, Donald R.; Holtan, Shernan G.	2025	Frontiers in Medical Technology	Case Study	Sense	Adults, Patients	Sleep, Steps
Gender diversity and daily steps: Findings from the Adolescent Brain Cognitive Development Study details	Nagata, Jason M.; Sui, Shirley; Kim, Angela E.; Shao, Iris Yuefan; Otmar, Christopher D.; Ganson, Kyle T.; Testa, Alexander; Dooley, Erin E.; Gooding, Holly C.; Baker, Fiona C.; Pettee Gabriel, Kelley	2025	Annals of Epidemiology	Case Study	Charge 2	Adolescents	Steps
GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women details	Yi, Li; Hart, Jaime E.; Wilt, Grete; Hu, Cindy R.; Jimenez, Marcia Pescador; Lin, Pi-I. Debby; Suel, Esra; Hystad, Perry; Hankey, Steve; Zhang, Wenwen; Chavarro, Jorge E.; Laden, Francine; James, Peter	2025	The International Journal of Behavioral Nutrition and Physical Activity	Case Study	Charge HR, Charge 2, Charge 3	Adults	Sleep, Steps, Intensity
Heat-Treated Limosilactobacillus fermentum PS150 Improves Sleep Quality with Severity-Dependent Benefits: A Randomized, Placebo-Controlled Trial details	Lee, Mon-Chien; Chen, Chao-Yuan; Chen, Ching-Yun; Huang, Chi-Chang	2025	Nutrients	Case Study	Inspire 3	Adults	Sleep
Identifying Optimal Wearable Devices for Monitoring Mobility in Hospitalized Older Adults: Feasibility, Acceptability, and Validity Study details URL ↗	Nascimento, Paulo; Kirkwood, Renata; Griffith, Lauren E.; Duong, Mylinh; Cooper, Cody; Hao, Yujiao; Zheng, Rong; Raza, Samir; Beauchamp, Marla	2025	JMIR Aging	Validation, Usability	Versa	Older Adults	Steps, User Friendliness
Impact of Frailty on Physical Activity in the Postoperative Period After Liver Transplant Surgery: Pilot Study Using Fitbit Watch details	Shamaa, Tayseer M.; Allenspach, Lisa; Shamaa, Omar; Hage-Hassan, Omar; Kitajima, Toshihiro; Shimada, Shingo; Bajjoka-Francis, Iman; Abouljoud, Marwan S.; Nagai, Shunji	2025	Clinical Transplantation	Usability	Inspire 2	Patients	Steps
Impact of Usual-Care Physiotherapy on Physical Activity and Self-Efficacy in People With Multiple Sclerosis: An Observational Longitudinal Study details	Torchio, Alessandro; Fusari, Giulia; Cattaneo, Davide; Grosso, Cristina; Pagliari, Chiara; Crispiatico, Valeria; Perini, Gloria; Jonsdottir, Johanna	2025	International journal of MS care	Case Study	Versa	Adults	Steps, Intensity
Improved glycemic outcomes in people with type 2 diabetes using smart blood glucose monitoring integrated with popular digital health therapeutics details	Grady, Mike; Holt, Elizabeth; Cameron, Hilary; Edelman, Steven	2025	Scientific Reports	Intervention	Inspire 2	Adults	Steps
Improving Outcomes for Care Partners of Individuals With Traumatic Brain Injury: Results for a mHealth Randomized Control Trial of the CareQOL App details	Carlozzi, Noelle E.; Troost, Jonathan P.; Sen, Srijan; Choi, Sung Won; Wu, Zhenke; Miner, Jennifer A.; Lombard, Wendy L.; Graves, Christopher; Sander, Angelle M.	2025	Archives of Physical Medicine and Rehabilitation	Intervention	Device unspecified	Adults	Sleep, Steps, User Friendliness
Inconclusive Single-Lead ECGs From Smart-Devices: Impact of Baseline ECG Anomalies details	Isenegger, Corinne; Mannhart, Diego; Weidlich, Simon; Brügger, Jonas; Serban, Teodor; Jordan, Fabian; Krisai, Philipp; Knecht, Sven; Schaerli, Nicolas; Subin, Behnam; Mosher, Luke; du Fay de Lavallaz, Jeanne; Schaer, Beat; Mahfoud, Felix; Kühne, Michael; Sticherling, Christian; Badertscher, Patrick	2025	JACC. Clinical electrophysiology	Case Study	Sense	Patients	Heart Rate
Innovative health monitoring for wheelchair users: A scoping review of smartwatch applications details	Oliveira, José Igor V.; Almeida, Rízia; de Lucena, Erick Guilherme Peixoto; Tessutti, Vitor; Silva, Emely Pujólli; Uchida, Marco Carlos	2025	Assistive technology: the official journal of RESNA	Validation, Systematic Review	Charge 2, Flex 2, Versa	Adults	Energy Expenditure, Heart Rate
Insights into maternal sleep: a large-scale longitudinal analysis of real-world wearable device data before, during, and after pregnancy details	Young-Lin, Nichole; Heneghan, Conor; Liu, Yun; Schneider, Logan; Niehaus, Logan; Haney, Ariel; Asiedu, Mercy; Gleichauf, Karla; Shreibati, Jacqueline Baras; Lafon, Belen	2025	EBioMedicine	Case Study	Device unspecified	Pregnant Women	Sleep, Heart Rate
Integration of Wearables Into a Cardiac Rehabilitation Program and Its Impact on Physical Activity and Exercise Capacity in Older Patients With Cardiovascular Disease details	Yagi, Eijiro; Matsumura, Koichiro; Uchigashima, Yuki; Shiroyama, Jun; Hase, Mitsuki; Nanba, Tomoya; Yamada, Nobuhiro; Funauchi, Yohei; Ueno, Masafumi; Togi, Kiyonori; Shirotani, Manabu; Nakazawa, Gaku	2025	Advances in Rehabilitation Science and Practice	Case Study	Versa 3	Older Adults, Patients	Heart Rate
Interpretable framework for predicting preoperative cardiorespiratory fitness using wearable data details	Hussain, Iqram; Zeepvat, Julianna; Reid, M. Cary; Czaja, Sara; Pryor, Kane O.; Boyer, Richard	2025	Computer Methods and Programs in Biomedicine	Case Study	Charge 3	Older Adults	Heart Rate
Isotemporal Substitution Effect of 24-h Movement Behaviors on Well-Being, Cognition, and BMI Among Older Adults details	Oginni, John; Ryu, Suryeon; Chen, Yingying; Gao, Zan	2025	Journal of Clinical Medicine	Case Study	Inspire 3	Older Adults	Sleep, Steps, Energy Expenditure, Intensity, Active Minutes/Active Zone Minutes
KArAT (Knee Arthroplasty Activity Trial): Rationale and design features of a multicenter randomized controlled trial details	Losina, Elena; Collins, Jamie E.; Kumara, Mahima; Ehrlich-Jones, Linda; Opare-Addo, Maame; Safran-Norton, Clare; Segal, Neil A.; Mitchell, Lauren M.; Kopp, Paul T.; Selzer, Faith; Mass, Hanna; Paskewicz, Michael; Chang, Rowland W.; Dunlop, Dorothy; Chen, Antonia F.; Lerner, Samuel; Chin, Samantha; Pellegrini, Christine; Katz, Jeffrey N.	2025	Osteoarthritis and Cartilage Open	Intervention	Inspire 3	Adults	Steps, Intensity
Large-scale digital phenotyping: Identifying depression and anxiety indicators in a general UK population with over 10,000 participants details	Zhang, Yuezhou; Stewart, Callum; Ranjan, Yatharth; Conde, Pauline; Sankesara, Heet; Rashid, Zulqarnain; Sun, Shaoxiong; Dobson, Richard J. B.; Folarin, Amos A.	2025	Journal of Affective Disorders	Case Study	Device unspecified	Adults	Sleep, Steps, Energy Expenditure, Heart Rate
Latent Default Mode Network Connectivity Patterns: Associations With Sleep Health and Adolescent Psychopathology details URL ↗	Zhang, Linhao; Geier, Charles; House, Ellen; Oshri, Assaf	2025	Brain and Behavior	Case Study	Charge HR	Adolescents	Sleep
Leveraging Accelerometry and Heartrate Data from Consumer Wearables to Predict Physical Activity in Children: A Device Agnostic Approach details	Ghosal, Rahul; White, James W.; Finnegan, Olivia; Nelakuditi, Srihari; Brown, Trey; Pate, Russ; Welk, Greg; de Zambotti, Massimiliano; Wang, Yuan; Burkart, Sarah; Adams, Elizabeth L.; Armstrong, Bridget; Beets, Michael W.; Weaver, R. Glenn	2025	Medicine and Science in Sports and Exercise	Validation	Sense	Children	Steps, Heart Rate
Longitudinal trends in physical activity and sleep before, during, and after pregnancy using Fitbit and EHR data from the All of Us research program details	Lo, Claire; Annis, Jeffrey; Master, Hiral; Cakar, Adnan; Osmundson, Sarah; Ruderfer, Douglas; Brittain, Evan	2025	American journal of obstetrics \& gynecology MFM	Case Study	Device unspecified	Pregnant Women	Sleep, Steps
Machine learning applied to wearable fitness tracker data and the risk of hospitalizations and cardiovascular events details URL ↗	Kundrick, John; Naniwadekar, Aditi; Singla, Virginia; Kancharla, Krishna; Bhonsale, Aditya; Voigt, Andrew; Shalaby, Alaa; Estes, N. A. Mark; Jain, Sandeep K.; Saba, Samir	2025	American Journal of Preventive Cardiology	Case Study	Device unspecified	Adults	Steps, Heart Rate
Mental Stress Assessment and Clinical Application of Wearable Devices as Evaluable Outcomes in Robotic Prostatectomy details	Naiki, Taku; Mimura, Yoshihisa; Sugiyama, Yosuke; Etani, Toshiki; Nakane, Akihiro; Nagai, Takashi; Tasaki, Yoshihiko; Shimizu, Nobuhikio; Gonda, Masakazu; Aoki, Maria; Morikawa, Toshiharu; Iwatsuki, Shoichiro; Hamamoto, Shuzo; Umemoto, Yukihiro; Yasui, Takahiro	2025	Annals of Surgical Oncology	Case Study	Charge 2	Adults	Heart Rate
mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED): statistical analysis plan details URL ↗	Vetrovsky, Tomas; Kral, Norbert; Pfeiferova, Marketa; Seifert, Bohumil; Capek, Vaclav; Jurkova, Katerina; Steffl, Michal; Cimler, Richard; Kuhnova, Jitka; Harris, Tess; Ussher, Michael; Wahlich, Charlotte; Malisova, Katerina; Pelclova, Jana; Dygryn, Jan; Elavsky, Steriani; Maes, Iris; Van Dyck, Delfien; Rowlands, Alex; Yates, Tom	2025	Trials	Intervention	Inspire 2	Patients	Steps, Goals
mHealth-Based Diabetes Prevention Program for Chinese Mothers With Abdominal Obesity: Randomized Controlled Trial details	Huang, Qinyuan; Zhong, Qinyi; Zeng, Yanjing; Li, Yimeng; Wiley, James; Wang, Man Ping; Chen, Jyu-Lin; Guo, Jia	2025	JMIR mHealth and uHealth	Intervention	Alta HR	Adults	Sleep, Steps, Energy Expenditure, Food
Modulating Brain Activity to Improve Goal-directed Physical Activity in Older Adults: A Pilot Randomized Controlled Trial details	Lo, On-Yee; Ask, Levi; Kahya, Melike; Travison, Thomas; Lipsitz, Lewis A.; Manor, Brad	2025	The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences	Intervention	Device unspecified	Older Adults	Steps
MOMs Chat \& Care Study: Rationale and design of a pragmatic randomized clinical trial to prevent severe maternal morbidity among Black birthing people details	Fitzpatrick, Stephanie L.; Polo, Jennifer; Ephraim, Patti; Vrany, Elizabeth; Chiuzan, Codruta; Basile, Melissa; Friel, Ciaran P.; Moon, Khatiya Chelidze; Silvia, Emily; Bleau, Hallie; Nicholson, Wanda; Lewis, Dawnette; MOMs Chat Care Research Group	2025	Contemporary Clinical Trials	Intervention	Device unspecified	Adults	Steps
Monitoring Adolescent Sport-Related Concussion Recovery Using Consumer-Grade Wearables: A Pilot Study details	Ransom, Danielle M.; Tudor, Brant H.; Irani, Sarah A.; Rehman, Mohamed A.; Suskauer, Stacy J.; Svingos, Adrian M.; Ahumada, Luis M.; Mularoni, P. Patrick	2025	The Journal of Head Trauma Rehabilitation	Case Study	Sense	Adolescents	Sleep, Steps, Heart Rate
More variable circadian rhythms in epilepsy captured by long-term heart rate recordings from wearable sensors details	Smith, Billy C.; Thornton, Christopher; Stirling, Rachel E.; Besné, Guillermo M.; Gascoigne, Sarah J.; Evans, Nathan; Taylor, Peter N.; Leiberg, Karoline; Karoly, Philippa J.; Wang, Yujiang	2025	Epilepsia	Case Study	Device unspecified	Adults	Heart Rate
Multidomain postoperative recovery trajectories after lumbar and thoracolumbar spine surgery details	Yakdan, Salim; Zhang, Jingwen; Benedict, Braeden; Xu, Ziqi; Javeed, Saad; Zhang, Justin K.; Steel, Benjamin A.; Gupta, Vivek P.; Botterbush, Kathleen; Piccirillo, Jay F.; Rodebaugh, Thomas L.; Goodin, Burel R.; Buchowski, Jacob M.; Neuman, Brian; Hafez, Daniel; Kelly, Michael; Ray, Wilson Z.; Lu, Chenyang; Frumkin, Madelyn; Greenberg, Jacob K.	2025	The Spine Journal: Official Journal of the North American Spine Society	Case Study	Inspire 2	Patients	Steps, Intensity
Multimodal Sensing and Modeling of Endocrine Therapy Adherence in Breast Cancer Survivors details	Yuan, Fangxu; Kaur, Navreet; Wang, Zhiyuan; Gonzales, Manuel; Alcaraz, Cristian Garcia; Estrella, Gabriel; Wells, Kristen J.; Barnes, Laura E.	2025	Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies	Intervention	Sense	Adults	Sleep, Steps, Heart Rate, Active Minutes/Active Zone Minutes
No evidence of fluctuations in daily step count between infusions in people with multiple sclerosis treated with anti-CD20 monoclonal antibodies details	Block, Valerie J.; Henderson, Kyra; Poole, Shane; Joseph, Gabby B.; Gelfand, Jeffrey M.; Cree, Bruce Ac; Bove, Riley	2025	Multiple Sclerosis Journal - Experimental, Translational and Clinical	Case Study	Device unspecified	Patients	Steps
Objective vs perceived sleep in Belgian occupational drivers: A field study details	Schyvens, An-Marie; Van Oost, Nina Catharina; Peters, Brent; Veys, Frederik; Aerts, Jean-Marie; Masci, Federica; Neven, An; Dirix, Hélène; Wets, Geert; Ross, Veerle; Verbraecken, Johan	2025	Sleep Medicine	Case Study	Charge 5	Adults	Sleep
Optimization and pre-use suitability selection for wrist photoplethysmography-based heart rate monitoring in patients with cardiac disease details URL ↗	Vermunicht, Paulien; Buyck, Christophe; Naessens, Sebastiaan; Hens, Wendy; Verberckt, Caro; Van Craenenbroeck, Emeline; Laukens, Kris; Desteghe, Lien; Heidbuchel, Hein	2025	European Heart Journal. Digital Health	Intervention	Inspire 2	Patients	Heart Rate
Optimizing a mHealth physical activity intervention with mindful awareness lessons in breast cancer survivors: Fit2ThriveMIND protocol details	Wolter, Melanie; Reading, Jean M.; Solk, Payton; Starikovsky, Julia; Hasanaj, Kristina; Wang, Shirlene D.; Siddique, Juned; Horowitz, Bruriah; Spring, Bonnie; Carden, Lillian B.; Fox, Rina; Sauer, Christina; Freeman, Hannah; Frey, Julia; Victorson, David; Phillips, Siobhan M.	2025	Contemporary Clinical Trials	Intervention, Systematic Review	Device unspecified	Adults	Steps, Intensity, Device Weartime
Pain detection using biometric information acquired by a wristwatch wearable device: a pilot study of spontaneous menstrual pain in healthy females details	Hirayama, Hideyuki; Yoshida, Shiori; Sasaki, Konosuke; Yuda, Emi; Yoshida, Yutaka; Miyashita, Mitsunori	2025	BMC research notes	Case Study	Sense 2	Adults	Heart Rate
Patient-Centered mHealth Intervention to Improve Self-Care in Patients With Chronic Heart Failure: Phase 1 Randomized Controlled Trial details	Kitsiou, Spyros; Gerber, Ben S.; Buchholz, Susan W.; Kansal, Mayank M.; Sun, Jiehuan; Pressler, Susan J.	2025	Journal of Medical Internet Research	Intervention	Charge 2	Patients	Sleep, Steps, Intensity, Heart Rate
Perioperative Wearable Device Features are associated with Moderate-to-Severe Chronic Pain after Surgery in the “All of Us” Research Program details URL ↗	Zhang, Wenyu; Ross, Mindy K.; Frumkin, Madelyn R.	2025	medRxiv	Case Study		Adults	Sleep, Steps
Personalized Physician-Assisted Sleep Advice for Shift Workers: Algorithm Development and Validation Study details	Shen, Yufei; Choto Olivier, Alicia; Yu, Han; Ito-Masui, Asami; Sakamoto, Ryota; Shimaoka, Motomu; Sano, Akane	2025	JMIR formative research	Case Study	Device unspecified	Adults	Sleep, Steps, Heart Rate
Physical Activity, Sleep, and Quality of Life in Pulmonary Arterial Hypertension: Novel Insights From Wearable Devices details	Hughes, Andrew M.; Lindsey, Alisha; Annis, Jeffrey; Burke, Kelly; Master, Hiral; Silverman-Lloyd, Luke G.; Garry, Jonah D.; Blaha, Michael J.; Berman Rosenzweig, Erika S.; Frantz, Robert P.; Hassoun, Paul M.; Horn, Evelyn M.; Leopold, Jane A.; Rischard, Franz P.; Larive, Brett; Hill, Nicholas S.; Erzurum, Serpil C.; Beck, Gerald J.; Hemnes, Anna R.; Brittain, Evan L.	2025	Pulmonary Circulation	Usability	Charge 3, Versa, Charge 5	Adults	Sleep, Steps
Physiological Data Collected From Wearable Devices Identify and Predict Inflammatory Bowel Disease Flares details	Hirten, Robert P.; Danieletto, Matteo; Sanchez-Mayor, Milagros; Whang, Jessica K.; Lee, Kyung Won; Landell, Kyle; Zweig, Micol; Helmus, Drew; Fuchs, Thomas J.; Fayad, Zahi A.; Nadkarni, Girish N.; Keefer, Laurie; Suarez-Farinas, Mayte; Sands, Bruce E.	2025	Gastroenterology	Survey Research	Device unspecified	Adults	Heart Rate
Pilot Study on the Effect of Cannabidiol-Coated Fabric for Pillow Covers Improves the Sleep Quality of Shift Nurses details	Afzal, Mashita; Huang, Chieh-Liang; Huang, Shih-Hao; Li, Chia-Ing; Liao, Wen-Chun; Yang, Juan-Cheng; Ma, Wen-Lung	2025	Healthcare (Basel, Switzerland)	Intervention	Charge 3	Adults	Sleep
Predicting Incident Type 2 Diabetes Using Wearable Activity and Polygenic Risk: A Survival-Modeling Study in All of Us details	Rahman, Md Hafizur; Arian, Ash; Konda, Sreenivas; McGuinn, Laura A.; Islam, Humayera; Chowdhury, Muhammad Ashique Haider; Shahriar, Mohammad Hasan; Rayna, Shahrin Emdad; Farzana, Shahla; Tasmin, Saira; Manna, Ridwana Maher; Haider, Mohammad Rifat; Ahsan, Habibul	2025	The Journal of Clinical Endocrinology and Metabolism	Case Study	Device unspecified	Adults	Steps
Predicting Real-World Physical Activity in Multiple Sclerosis: An Integrated Approach Using Clinical, Sensor-Based, and Self-Reported Measures details	Monaghan, Patrick G.; VanNostrand, Michael; Takla, Taylor N.; Fritz, Nora E.	2025	Sensors (Basel, Switzerland)	Case Study	Versa 2	Adults	Steps, Intensity, Active Minutes/Active Zone Minutes
Predicting Sleep and Sleep Stage in Children Using Actigraphy and Heartrate via a Long Short-Term Memory Deep Learning Algorithm: A Performance Evaluation details	Weaver, R. Glenn; White, James W.; Finnegan, Olivia; Yang, Hongpeng; Zhong, Zifei; Kiely, Keagan; Jones, Catherine; Tong, Yan; Nelakuditi, Srihari; Ghosal, Rahul; Brown, David E.; Pate, Russ; Welk, Gregory J.; de Zambotti, Massimiliano; Wang, Yuan; Burkart, Sarah; Adams, Elizabeth L.; Armstrong, Bridget; Beets, Michael W.	2025	Journal of Sleep Research	Case Study	Sense	Children	Sleep, Heart Rate
Predicting Social Frailty in Older Adults Using Fitbit-Derived Circadian and Heart Rate Biomarkers: Cross-Sectional Study details	Maekawa, Hiroki; Kume, Yu	2025	JMIR formative research	Case Study	Inspire	Older Adults	Steps, Heart Rate
Psychometric evaluation of the exercise self-regulatory efficacy scale using objective measures of physical functioning in persons with chronic obstructive pulmonary disease details	Bamonti, Patricia M.; Wingood, Mariana; Robinson, Stephanie A.; Rose, Grace A.; Moy, Marilyn L.	2025	Respiratory Medicine	Intervention	Zip	Adults	Steps
Real-Time and Long-Term Effects of Medical Marijuana on Older Adults: Protocol for the Study on Medical Marijuana and its Long-Term Effects (the SMILE study) Prospective Cohort details	Robinson, Kendall R.; Seeger, Stella D.; Nave, Lauren; Mejia, Marlin; Vander Meulen, Maria; Rashid, Ahmed; Mickle, Angela M.; Sibille, Kimberly; Li, Zhigang; Przkora, Rene; Schmidt, Siegfried; Lo, Margaret C.; Cook, Robert L.; Wang, Yan	2025	JMIR research protocols	Case Study	Charge 5, Charge 6	Older Adults	Sleep, Steps, Heart Rate
Relationship Between Activity Tracker Metrics and the Physical Activity Index and Their Association With Cardiometabolic Phenotypes, Subclinical Atherosclerosis, and Cardiac Remodeling: Cross-Sectional Study details URL ↗	Huang, Weiting; Wong, Mark Kei Fong; Loh, Enver De Wei; Koh, Tracy; Tan, Alex Weixian; Shen, Xiayan; Varli, Onur; Kong, Siew Ching; Chin, Calvin Woon Loong; Tan, Swee Yaw; Yap, Jonathan Jiunn Liang; Ng, Eddie Yin Kwee; Yeo, Khung Keong	2025	JMIR mHealth and uHealth	Case Study	Charge HR	Adults	Steps, Intensity, Heart Rate
Relationship between social determinants of health, health-related quality of life, health perceptions, and physical activity during pregnancy details	Nowell, Kallie; Dlugonski, Deirdre; DeFranco, Emily; May, Linda; Hawk, Gregory S.; Hoch, Johanna M.	2025	Women's Health (London, England)	Case Study	Device unspecified	Pregnant Women	Steps, Heart Rate
Relationship Between Step Count and the Timed Up and Go and L Test of Functional Mobility Among Adults With Transtibial Amputation details	Leister, Kyle R.; Barreira, Tiago V.	2025	Archives of Physical Medicine and Rehabilitation	Case Study	Inspire 3	Adults	Steps
Reliability and Accuracy of the Fitbit Charge 4 Photoplethysmography Heart Rate Sensor in Ecological Conditions: Validation Study details	Ceugniez, Maxime; Devanne, Hervé; Hermand, Eric	2025	JMIR mHealth and uHealth	Validation	Charge 4	Adults	Heart Rate
Rethinking measurement of movement-evoked pain with digital technology details	Frumkin, Madelyn R.; Zhang, Jingwen; Xu, Ziqi; Yakdan, Salim; Benedict, Braeden; Javeed, Saad; Zhang, Justin; Botterbush, Kathleen; Goodin, Burel R.; Lu, Chenyang; Ray, Wilson Z.; Greenberg, Jacob K.	2025	The Journal of Pain	Case Study	Inspire 2	Adults	Steps, Heart Rate
Scoping review of the utilization of wearable devices in pediatric and young adult oncology details	Collier, Lane; Grimshaw, Sarah L.; Stolper, Julian; Passmore, Elyse; Ball, Gareth; Elliott, David A.; Conyers, Rachel	2025	NPJ digital medicine	Review	Device unspecified	Adults, Children, Adolescents	Steps, Heart Rate
Selecting Wearable Devices to Measure Cardiovascular Functions in Community-Dwelling Adults: Application of a Practical Guide for Device Selection details	Lu, Jessica K.; Wang, Weilan; Goh, Jorming; Maier, Andrea B.	2025	Mayo Clinic Proceedings. Digital Health	Systematic Review	Charge 6	Adults	User Friendliness
Self-Reported Acceptance of a Wearable Activity Monitor in Persons With Stroke: Usability Study details	Nam, Jamie; Bellinger, Grace C.; Li, Junyao; French, Margaret A.; T Roemmich, Ryan	2025	JMIR cardio	Case Study	Inspire 2	Adults	Steps, Heart Rate, Device Weartime
Self-reported and tracker-estimated physical activity outcomes in women with chronic pelvic pain disorders: A longitudinal evaluation of construct validity details	Nagaldinne, Tanisee; Shahnawaz, Samia; Bakken, Suzanne R.; Elhadad, Noemie; Horan, Emma N.; Ewing-Garber, Carol; Rodrigues, Jovita; Danieletto, Matteo; Landell, Kyle; Ensari, Ipek	2025	medRxiv: The Preprint Server for Health Sciences	Case Study	Device unspecified	Adults	Steps, Intensity
Sensor-triggered ecological momentary assessment in physical activity and sedentary behaviour research among Belgian community-dwelling elderly: lessons learnt from intensive longitudinal studies details	Delobelle, Julie; Lebuf, Elien; Compernolle, Sofie; Vetrovsky, Tomas; Van Cauwenberg, Jelle; Cimler, Richard; Kuhnova, Jitka; Van Dyck, Delfien	2025	BMJ open	Case Study	Inspire 2, Ionic	Older Adults	Steps
Sleep Compensation on Work-Free days Is Associated with Better Sleep Quality details	Aslamyar, Diana; von Gall, Charlotte	2025	Nature and Science of Sleep	Case Study	Inspire 2	Adults	Sleep
Sleep duration and efficiency moderate the effects of prenatal and childhood ambient pollutant exposure on global white matter microstructural integrity in adolescence details	Cotter, Devyn L.; Kiss, Orsolya; Ahmadi, Hedyeh; de Jesus, Alethea; Schwartz, Joel; Baker, Fiona C.; Hackman, Daniel A.; Herting, Megan M.	2025	bioRxiv: The Preprint Server for Biology	Case Study	Charge 2	Adolescents	Sleep
Sleep duration and timing are associated with next-day physical activity: Insights from two large-scale wearable sensor studies details URL ↗	Leota, Josh; Czeisler, Mark É.; Le, Flora; Presby, David M.; Capodilupo, Emily R.; Scott, Hannah; Wiley, Joshua F.; Drummond, Sean P. A.; Rajaratnam, Shantha M. W.; Facer-Childs, Elise R.	2025	Proceedings of the National Academy of Sciences	Case Study	Device unspecified	Adults	Sleep, Steps, Intensity
Sleep Quality in Shift-Working Nurses: Subjective and Objective Evaluation details Link ↗	Željka Dujmić, Štefica Mikšić, Ivana Barać, Josip Samardžić, Lea Maršić, Petar Samardžić, Zvjezdana Gvozdanović, Ivana Jelinčić, Blaženka Kljajić Bukvić, Marija Barišić, Davorka Čavar-Lovrić, Ružica Mrkonjić, Ivica Mihaljević, and Nikolina Farčić	2025	International journal of environmental research and public health	Case Study	Charge 3	Adults	Sleep
Smartphone Application With Health Coaching Facilitates Multi‐Symptom Improvement in IBS Patients: A Pilot Feasibility Trial details URL ↗	Eisele, Max; Yousuf, Munazza; Haskey, Natasha; D'Silva, Adrijana; Nasser, Yasmin; Franco, Laura; Raman, Maitreyi	2025	Neurogastroenterology and Motility	Intervention	Inspire 3	Adults	Sleep, Steps, Intensity
Snacktivity™ to Promote Physical Activity in Primary Care, Community Health and Public Health Settings: A Feasibility Randomised Controlled Trial details	Daley, Amanda J.; Griffin, Ryan A.; Sanders, James P.; Gokal, Kajal; Ives, Natalie; Skrybant, Magdalena; Parretti, Helen M.; Edwardson, Charlotte L.; Biddle, Stuart J. H.; Jolly, Kate; Greaves, Colin J.; Greenfield, Sheila M.; Maddison, Ralph; Esliger, Dale W.; Sherar, Lauren B.; Frew, Emma; Mutrie, Nanette; Maylor, Ben; Yates, Tom; Tearne, Sarah; Moakes, Catherine A.	2025	International Journal of Behavioral Medicine	Intervention	Versa 2	Adults	Active Minutes/Active Zone Minutes
Somatomotor Disconnection Links Sleep Duration With Socioeconomic Context, Screen Time, Cognition, and Psychopathology details	Michael, Cleanthis; Taxali, Aman; Angstadt, Mike; McCurry, Katherine L.; Weigard, Alexander; Kardan, Omid; Molloy, M. Fiona; Toda-Thorne, Katherine; Burchell, Lily; Dziubinski, Maria; Choi, Jason; Vandersluis, Melanie; Hyde, Luke W.; Heitzeg, Mary M.; Sripada, Chandra	2025	Biological Psychiatry Global Open Science	Review	Charge 2	Adolescents	Sleep
Temporal relationships between depression, self-efficacy, and physical activity in individuals with stroke details URL ↗	Bellinger, Grace C.; Roemmich, Ryan T.; Psoter, Kevin J.; Wegener, Stephen T.; Keatley, Eva; French, Margaret A.	2025	medRxiv	Case Study	Inspire 2	Adults	Steps
Tension and Trauma Releasing Exercises for People with Multiple Sclerosis: A Randomized Controlled Trial details	Skovgaard, Lasse; Trénel, Philipp; Hanehøj, Kirsten; Lynning, Marie	2025	Advances in Mind-Body Medicine	Measurement, Intervention	Charge 3	Patients	Sleep
The Association Between Quality of Recovery, Objective and Subjective Sleep Quality, and Pain After Abdominal Surgery: A Cross-Sectional Study details	Wozniak, Anita Bilde; Knudstrup, Katja Tenna; Bilberg, Randi Marie; Konradsen, Hanne	2025	Gastroenterology Nursing: The Official Journal of the Society of Gastroenterology Nurses and Associates	Case Study	Charge 4	Patients	Sleep, Heart Rate
The Effect of Assistive Devices on the Accuracy of Fitbits in Healthy Individuals: A Brief Report details	Jaworski, John; Makowski, Brian; Weaver, Michael; Seils, Michael; Scheid, Jennifer L.	2025	International Journal of Environmental Research and Public Health	Validation	Inspire 3	Adults	Steps
The effect of sleep quality on glucose variability among adolescents with type 1 diabetes in China: A multi-central temporal longitudinal association analysis details URL ↗	Li, Qingting; Lv, Wencong; Yuwen, Weichao; Jia, Zhumin; Li, Xia; Guo, Jia	2025	Sleep Medicine	Case Study	Inspire HR	Adolescents	Sleep
The effectiveness and cost effectiveness of Snacktivity™ as an intervention to promote physical activity and health outcomes: a study protocol for a multi-centre randomised controlled trial details	Daley, Amanda J.; Griffin, Ryan A.; Sanders, James P.; Edwardson, Charlotte L.; Neal, Liam; Lee, Sam; Skrybant, Magdalena; Moakes, Catherine A.; Gkini, Eleni; Frew, Emma; Greaves, Colin J.; Dobell, Alexandra; Gokal, Kajal; Tearne, Sarah; Parretti, Helen M.; Biddle, Stuart J. H.; Jolly, Kate; Greenfield, Sheila M.; Maddison, Ralph; Esliger, Dale W.; Sherar, Lauren B.; Mutrie, Nanette; Yates, Tom; Ives, Natalie	2025	Trials	Intervention	Versa 4	Adults	Intensity, Active Minutes/Active Zone Minutes
The effects of diaphragm release on sleep quality: a pilot feasibility study details	Erol, Erkan; Kurtboğan, Muhammed	2025	BMC pulmonary medicine	Intervention	Inspire 2	Adults	Sleep, Heart Rate
The feasibility and acceptability of delivering and evaluating a physical activity intervention (ACCEPTANCE) for cervical cancer survivors details	Millet, Nessa; McDermott, Hilary J.; Munir, Fehmidah; Edwardson, Charlotte L.; Plekhanova, Tatiana; Moss, Esther L.	2025	Pilot and Feasibility Studies	Intervention	Inspire	Adults	User Friendliness
The Impact of Macronutrient Intake on Sleep Quality in Female Endurance Athletes: A Pilot Observational Cross-Sectional Study details	Koikawa, Natsue; Minamino, Yume; Kawasaki, Yu; Kasai, Takatoshi; Suzuki, Yoshio	2025	Nutrients	Case Study	Charge 3	Adults	Sleep
The mLIFE randomized trial examining the impact of gamifying social support provision for weight loss details	Turner-McGrievy, Gabrielle M.; Delgado-Díaz, Diana Carolina; DuBois, Kelli E.; Aydin, Halide Zeynep; Monroe, Courtney M.; Kim, Yesil; Hardin, James; Wilcox, Sara; Valafar, Homayoun	2025	Obesity (Silver Spring, Md.)	Intervention		Adults	Weight
The Physical Activity at Work (PAW) Program in Thai Office Workers: Mixed Methods Process Evaluation Study details	Akksilp, Katika; Rouyard, Thomas; Isaranuwatchai, Wanrudee; Nakamura, Ryota; Müller-Riemenschneider, Falk; Teerawattananon, Yot; Chen, Cynthia	2025	JMIR formative research	Intervention	Inspire HR	Adults	Steps, Device Weartime
The relationship between sleep and problem behaviors in children with attention-deficit/hyperactivity disorder details URL ↗	Ghanim, Fanar; Harkness, Kelsey; Wiley, Bevin; Guadagni, Veronica; Murias, Kara	2025	European Journal of Pediatrics	Case Study	Charge 2	Children	Sleep
The role of health monitoring technologies in optimising athletes' self-regulation details	Gakh, Roman V.; Fedoniuk, Larisa Ya; Furman, Oksana Ye; Kramchenkova, Vira O.; Kuznetsov, Oleksiy I.	2025	Wiadomosci Lekarskie (Warsaw, Poland: 1960)	Systematic Review	Charge 5		Sleep, Heart Rate
Trajectories of Adherence to Study-Prescribed Physical Activity Goals in a mHealth Weight Loss Intervention details	Bizhanova, Zhadyra; Burke, Lora E.; Brooks, Maria M.; Rockette-Wagner, Bonny; Kariuki, Jacob K.; Sereika, Susan M.	2025	Sensors (Basel, Switzerland)	Intervention, Case Study	Charge 2	Adults	Steps, Food, Intensity
Transcutaneous auricular vagus nerve stimulation (taVNS) improves sleep quality in chronic insomnia disorder: A double-blind, randomized, sham-controlled trial details URL ↗	Yeom, Ji Won; Kim, Hyojin; Park, Soohyun; Yoon, Yeaseul; Seo, Ju Yeon; Cho, Chul-Hyun; Lee, Heon-Jeong	2025	Sleep Medicine	Case Study	Charge 4	Adults	Sleep
Unlocking the Potential of Wear Time of a Wearable Device to Enhance Postpartum Depression Screening and Detection: Cross-Sectional Study details URL ↗	Hurwitz, Eric; Meltzer-Brody, Samantha; Butzin-Dozier, Zachary; Patel, Rena C.; Elhadad, Noémie; Haendel, Melissa A.	2025	JMIR Formative Research	Case Study	Device unspecified	Pregnant Women	Device Weartime
Unlocking the potential of wearable technology: Fitbit-derived measures for predicting ADHD in adolescents details URL ↗	Rahman, Muhammad Mahbubur	2025	Frontiers in Child and Adolescent Psychiatry	Case Study	Charge 2	Adolescents	Energy Expenditure, Heart Rate
Usability and Implementation Considerations of Fitbit and App Intervention for Diverse Cancer Survivors: Mixed Methods Study details	Dabbagh, Zakery; Najjar, Reem; Kamberi, Ariana; Gerber, Ben S.; Singh, Aditi; Soni, Apurv; Cutrona, Sarah L.; McManus, David D.; Faro, Jamie M.	2025	JMIR cancer	Intervention	Charge 2, Charge 5	Patients	Steps, Goals
Use of mHealth Technology for Improving Exercise Adherence in Patients With Heart Failure: Systematic Review details	Deka, Pallav; Salahshurian, Erin; Ng, Teresa; Buchholz, Susan W.; Klompstra, Leonie; Alonso, Windy	2025	Journal of Medical Internet Research	Systematic Review	Charge HR, Inspire HR		Steps, Heart Rate
Using Continuous Glucose Monitoring as a Biological Feedback Strategy to Motivate Physical Activity in Cancer Survivors: A Mixed-Methods Pilot Study details	Liao, Yue; Brannon, Grace E.; Rethorst, Chad D.; Baum, Miranda; Bevers, Therese B.; Schembre, Susan M.; Basen-Engquist, Karen M.	2025	Cancer Control: Journal of the Moffitt Cancer Center	Intervention	Inspire	Adults	Steps, Intensity, Heart Rate, User Friendliness
Using Step Trackers Among Older People Receiving Aged Care Services Is Feasible and Acceptable: A Mixed-Methods Study details	Dawson, Rik; Kay, Judy; Cameron, Lauren; Bucalon, Bernard; Sherrington, Catherine; Haynes, Abby	2025	Healthcare	Usability	Inspire 3	Older Adults	Steps, User Friendliness
Using Wear Time for the Analysis of Consumer-Grade Wearables' Data: Case Study Using Fitbit Data details	Baroudi, Loubna; Zernicke, Ronald Fredrick; Tewari, Muneesh; Carlozzi, Noelle E.; Choi, Sung Won; Cain, Stephen M.	2025	JMIR mHealth and uHealth	Usability	Charge, Inspire 2	Adults	Steps, Device Weartime
Utility of a Wearable Tracker to Assess Sleep Quality in Nurses and Their Spouses: A Prospective Cohort Study details	Ishinuki, Tomohiro; Goda, Erika; Tatsumi, Hiroomi; Kutomi, Goro; Ohyanagi, Toshio; Ohnishi, Hirofumi; Masuda, Yoshiki; Hui, Thomas T.; Mizuguchi, Toru	2025	SAGE open nursing	Case Study	Device unspecified	Adults	Sleep, Steps
Validation of an Open-Source Smartwatch for Continuous Monitoring of Physical Activity and Heart Rate in Adults details	Ravanelli, Nicholas; Lefebvre, KarLee; Brough, Amy; Paquette, Simon; Lin, Wei	2025	Sensors (Basel, Switzerland)	Validation	Charge 5	Adults	Steps
Validation of the Caen Chronotype Questionnaire: Exploring the added value of amplitude and correlations with actigraphy details	Hickman, Robert; Lai Jie, Daniel; Shergill, Sukhi; Laborde, Sylvain; D'Oliveira, Teresa C.	2025	Chronobiology International	Case Study	Charge 4	Adults	Sleep
Validation of the Fitbit Charge 5 for the Detection of Heart Rate and Electrodermal Activity details	Ko, Katherine; McArthur, Genevieve; Johnco, Carly	2025	Psychophysiology	Validation	Charge 5	Adults	Intensity, Heart Rate
Validity of Heart Rate Measurement Using Wearable Devices During Cardiopulmonary Exercise Testing in Patients With Cardiovascular Disease: Prospective Pilot Validation Study details	Kitagaki, Kazufumi; Hongo, Yuji; Futai, Rie; Hasegawa, Takeshi; Morikawa, Hiroshi; Shimoyama, Hisashi	2025	JMIR cardio	Validation	Inspire 3	Patients	Heart Rate
Validity of the Fitbit wearable activity monitor to estimate step counts in free-living conditions in ambulatory children and youth living with disability details	Voss, Christine; Bremer, Emily; Sharma, Ritu; Martin Ginis, Kathleen A.; Arbour-Nicitopoulos, Kelly P.	2025	Disability and Rehabilitation	Validation	Charge HR	Children	Steps
Virtual Group-based Walking Intervention for Adults with Schizophrenia-Spectrum Disorders: Psychosocial Outcome Results from a Pilot Randomized Controlled Trial details	Browne, Julia; Kunicki, Zachary; Jarskog, L. Fredrik; Sheeran, Paschal; Abrantes, Ana M.; Elliott, Tonya; Gonzalez, Oscar; Penn, David L.; Battaglini, Claudio	2025	Community Mental Health Journal	Intervention	Charge	Adults	Steps, Heart Rate
Wearable Devices Detect Physiological Changes that Precede and Are Associated with Symptomatic and Inflammatory Rheumatoid Arthritis Flares details URL ↗	Sharma, Pragya; Danieletto, Matteo; Whang, Jessica K.; Landell, Kyle; Helmus, Drew; Sands, Bruce E.; Suarez-Farinas, Mayte; Gulko, Percio S.; Hirten, Robert P.	2025	medRxiv	Case Study	Device unspecified	Adults	Steps, Heart Rate
Wearable Devices in Remote Cardiac Rehabilitation With and Without Weekly Online Coaching for Patients With Coronary Artery Disease: Randomized Controlled Trial details URL ↗	Nishio, Ryota; Dohi, Tomotaka; Yokoyama, Miho; Nakade, Taisuke; Takahashi, Norihito; Chikata, Yuichi; Endo, Hirohisa; Nishiyama, Hiroki; Okai, Iwao; Iwata, Hiroshi; Okazaki, Shinya; Miyauchi, Katsumi; Daida, Hiroyuki; Minamino, Tohru	2025	JMIR mHealth and uHealth	Intervention	Sense	Patients	Steps, Intensity, Heart Rate
Wearable sensor data visualization for patient monitoring and management: a Cancer Wellness application in Vietnam details	Nguyen, Huyen Thi Hoa; Tran, Tran Ngoc; Nguyen, Giang Huong; Nguyen, Tung Truong; Nguyen, Ngan Thi Thuy; Pham, Hieu Huy; Bui, Linh Khanh; Nguyen, Anh Chau; Anderson, Debra J.	2025	Future science OA	Case Study	Charge 5	Adults	Sleep, Steps, Heart Rate
Wearable technology for mobility measurement in orthopedics and traumatology: a comparison of commercially available systems details	Keppler, A. M.; Zaccaria, R.; Weigert, M.; Keppler, L.; Böcker, W.; Neuerburg, C.; Schniepp, R.; Fürmetz, J.	2025	Archives of Orthopaedic and Trauma Surgery	Validation	Charge 3	Older Adults, Children	Steps
Wearable Technology in Cardiology: Advancements, Applications, and Future Prospects details	Jena, Nihar; Singh, Prabhat; Chandramohan, Deepak; Garapati, Hari N.; Gummadi, Jyotsna; Mylavarapu, Maneeth; Shaik, Bushra Firdous; Nanjundappa, Athmananda; Apala, Dinesh Reddy; Toquica, Christian; Lapsiwala, Boney; Simhadri, Prathap Kumar	2025	Reviews in Cardiovascular Medicine	Validation, Review	One, Flex, Charge, Inspire, Charge 4, Versa, Sense, Fitbit Luxe	Adults	Steps, Heart Rate
What is the effect of postpartum hemorrhage on physical activity after cesarean? details	Felfeli, Mina; Lehn, Samuel; Tveit, Meghan; Hill, Devin; Ahmadzia, Homa K.	2025	International Journal of Gynaecology and Obstetrics: The Official Organ of the International Federation of Gynaecology and Obstetrics	Case Study	Inspire	Patients, Pregnant Women	Steps, Device Weartime
Working Women Walking Program: A Sequential Multiple Assignment Randomized Trial details	Buchholz, Susan W.; Daniel, Manju; Kitsiou, Spyros; Schoeny, Michael E.; Halloway, Shannon; Johnson, Tricia J.; Vispute, Sachin; Wilbur, JoEllen	2025	Journal of Physical Activity \& Health	Intervention	Charge 2, Charge 3	Adults	Steps, Goals
A comparison of the rates of clock-based nocturnal hypoglycemia and hypoglycemia whilst asleep among people living with diabetes: findings from the Hypo-METRICS study details	Martine-Edith, Gilberte; Divilly, Patrick; Zaremba, Natalie; Søholm, Uffe; Broadley, Melanie; Baumann, Petra Martina; Mahmoudi, Zeinab; Gomes, Mikel; Ali, Namam; Abbink, Evertine J.; de Galan, Bastiaan E.; Brøsen, Julie Maria Bøggild; Pedersen-Bjergaard, Ulrik; Vaag, Allan A.; McCrimmon, Rory; Renard, Eric; Heller, Simon; Evans, Mark; Cigler, Monika; Mader, Julia K.; Speight, Jane; Pouwer, Frans; Amiel, Stephanie; Choudhary, Pratik	2024	Diabetes Technology \& Therapeutics	Case Study	Charge 4	Adults	Sleep
A Digital Biomarker Dataset in Hematopoietic Cell Transplantation: A Longitudinal Study of Caregiver-Patient Dyads (dHCT) details	Jalin, Aditya; Swatthong, Nawat; Rozwadowski, Michelle; Kumar, Rajnish; Barton, Deb; Braun, Tom; Carlozzi, Noelle; Hanauer, David A.; Hassett, Afton; Choi, Sung Won	2024	medRxiv: The Preprint Server for Health Sciences	Case Study	Charge 3	Patients	Sleep, Steps, Heart Rate
A lifestyle physical activity intervention for women in alcohol treatment: A pilot randomized controlled trial details	Abrantes, Ana M.; Browne, Julia; Stein, Michael D.; Anderson, Bradley; Iacoi, Sydney; Barter, Sarah; Shah, Zainab; Read, Jennifer; Battle, Cynthia	2024	Journal of Substance Use and Addiction Treatment	Intervention	Alta	Adults	Steps
A multiple technology-based and individually-tailored Sit Less program for people with cardiovascular disease: A randomized controlled trial study protocol details	Park, Chorong; Larsen, Britta; Mogos, Mulubrhan; Muchira, James; Dietrich, Mary; LaNoue, Marianna; Jean, Jason; Norfleet, John; Doyle, Abigail; Ahn, Soojung; Mulvaney, Shelagh	2024	PloS One	Intervention	Inspire 2	Adults	Steps, Intensity, Active Minutes/Active Zone Minutes
A Novel Scale of Lifestyle Physical Activity: Measure Description and Intervention Responsiveness details	Browne, Julia; Halverson, Tate F.; Battle, Cynthia L.; Stein, Michael D.; Bergeron, Alicia; Abrantes, Ana M.	2024	American Journal of Lifestyle Medicine	Intervention	Device unspecified	Adults	Steps
A pilot randomised controlled trial exploring the feasibility and efficacy of a human-AI sleep coaching model for improving sleep among university students details	Liu, Jintana; Ito, Sakura; Ngo, Tra My; Lawate, Ashwini; Ong, Qi Chwen; Fox, Tatiana Erlikh; Chang, Si Yuan; Phung, Duy; Nair, Elizabeth; Palaiyan, Malar; Joty, Shafiq; Abisheganaden, John; Lee, Chuen Peng; Lwin, May Oo; Theng, Yin Leng; Ho, Moon-Ho Ringo; Chia, Michael; Bojic, Iva; Car, Josip	2024	Digital Health	Intervention	Inspire 2	Adults	Sleep
A pilot randomized controlled trial of a virtual peer-support exercise intervention for female older adults with cancer details	Smith-Turchyn, Jenna; Sinclair, Susanne; O'Loughlin, Erin K.; Innes, Anthea; Vani, Madison F.; Beauchamp, Marla; Phillips, Stuart M.; Richardson, Julie; Thabane, Lehana; Sabiston, Catherine M.	2024	BMC geriatrics	Intervention	Inspire 2	Older Adults	Steps, Intensity, Active Minutes/Active Zone Minutes
A Pregnancy and Postnatal RCT Among Women With Gestational Diabetes Mellitus and Overweight/Obesity: The PAIGE2 Study details	Kemp, Bridie J.; Kelly, Bronagh; Cupples, Georgina; Fleck, Olwen; McAuley, Emma; Creighton, Rachel M.; Wallace, Helen; Graham, Una; Mulligan, Ciara; Kennedy, Adele; Patterson, Chris C.; McCance, David R.	2024	Journal of the Endocrine Society	Intervention	Device unspecified	Pregnant Women	Steps
A Remotely Delivered Light-Intensity Physical Activity Intervention for Older Cancer Survivors: Protocol for a Feasibility Randomized Controlled Trial details	Blair, Cindy K.; Brown-Glaberman, Ursa; Walters, Scott T.; Pestak, Claire; Boyce, Tawny; Barriga, Laura; Burgess, Ellen; Tawfik, Bernard; Killough, Cynthia; Kinney, Anita Y.; Demark-Wahnefried, Wendy; Meisner, Angela L.; Wiggins, Charles L.; Pankratz, V. Shane; Davis, Sally	2024	JMIR research protocols	Intervention	Inspire 3	Older Adults	Steps
A single-armed proof-of-concept study of Lymfit: A personalized, virtual exercise intervention to improve health outcomes in lymphoma survivors in the pandemic details	Angelillo, Christopher; Tock, Wing Lam; Salaciak, Matthew; Reid, Ryan E. R.; Andersen, Ross E.; Maheu, Christine; Johnson, Nathalie A.	2024	PloS One	Intervention	Device unspecified	Adults	Sleep, Steps, Intensity
A tree-based explainable AI model for early detection of Covid-19 using physiological data details	Talib, Manar Abu; Afadar, Yaman; Nasir, Qassim; Nassif, Ali Bou; Hijazi, Haytham; Hasasneh, Ahmad	2024	BMC medical informatics and decision making	Case Study	Versa 2		Sleep, Steps, Heart Rate
Accuracy of consumer-based activity trackers to measure and coach patients with lower limb lymphoedema details	Blondeel, Astrid; Devoogdt, Nele; Asnong, Anne; Geraerts, Inge; De Groef, An; Heroes, An-Kathleen; Van Calster, Charlotte; Troosters, Thierry; Demeyer, Heleen; Ginis, Pieter; De Vrieze, Tessa	2024	PloS One	Validation	Zip, Alta, Inspire	Adults, Patients	Steps
Accuracy of Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP Versus Polysomnography: Systematic Review details	Schyvens, An-Marie; Van Oost, Nina Catharina; Aerts, Jean-Marie; Masci, Federica; Peters, Brent; Neven, An; Dirix, Hélène; Wets, Geert; Ross, Veerle; Verbraecken, Johan	2024	JMIR mHealth and uHealth	Systematic Review	Charge 4, Garmin Vivosmart 4		Sleep
Accuracy of parent-reported sleep duration among adolescents assessed using accelerometry details	Turan, Ozerk; Garner, Jonathan; Chang, Linda; Isaiah, Amal	2024	Pediatric Research	Case Study	Charge 2, Charge 4	Children	Sleep
Accuracy of smartwatches for the remote assessment of exercise capacity details	Jamieson, Alexandra; Jones, Siana; Chaturvedi, Nishi; Hughes, Alun D.; Orini, Michele	2024	Scientific Reports	Usability	Sense, Garmin Vivoactive 4	Adults	Steps, Distance, Heart Rate
Accuracy of Three Commercial Wearable Devices for Sleep Tracking in Healthy Adults details	Robbins, Rebecca; Weaver, Matthew D.; Sullivan, Jason P.; Quan, Stuart F.; Gilmore, Katherine; Shaw, Samantha; Benz, Abigail; Qadri, Salim; Barger, Laura K.; Czeisler, Charles A.; Duffy, Jeanne F.	2024	Sensors (Basel, Switzerland)	Case Study	Sense 2	Adults	Sleep
Accuracy of wrist-worn activity trackers for measuring steps in patients after major abdominal surgery: A validation study details	Li, Zhi; Feng, Weiyan; Zhou, Lili; Gong, Shu	2024	Digital Health	Validation	Inspire HR	Patients	Steps
Actigraphy Study Endpoints to Reduce Sample Size and Facilitate Drug Development for Pediatric Pulmonary Arterial Hypertension details	Sun, Haihao; Stockbridge, Norman; Ivy, D. Dunbar; Clark, Jennifer; Bates, Angela; Handler, Stephanie S.; Krishnan, Usha S.; Mullen, Mary P.; Yung, Delphine; Hopper, Rachel K.; Varghese, Nidhy P.; Avitabile, Catherine M.; Fineman, Jeff; Austin, Eric D.; Freire, Grace	2024	The Journal of Pediatrics	Intervention	Charge 2	Children	Steps, Heart Rate
Actívatexto: Feasibility and Acceptability of a Mobile Intervention That Promotes Smoking Cessation and Physical Activity among Latinos details	Lara, Daimarelys; Alaniz-Cantú, Edgar I.; Siddalingaiaha, Simran; Oliveira, Igor; Chávez-Iñiguez, Arlette; DeJesus, Elisa; Fuller, Daniel; Marquez, David X.; Vásquez, Elizabeth; Li, Dongmei; McIntosh, Scott; Ossip, Deborah J.; Cupertino, Ana Paula; Cartujano-Barrera, Francisco	2024	Cancer Research Communications	Intervention	Versa 4	Adults	Intensity, Active Minutes/Active Zone Minutes, Device Weartime
Adherence to the Mediterranean diet and sleep quality are inter-correlated with flash glucose monitoring (FGM)-measured glycemia among children with type 1 diabetes details	Muayyad, Mariam; Abusnana, Salah; Mussa, Bashair M.; Helal, Radwa; Abdelrahim, Dana N.; Abdelreheim, Naguib Hassan; Al Amiri, Elham; Daboul, Mays; Al-Abadla, Zainab; Lessan, Nader; Faris, MoezAlIslam E.	2024	Journal of Education and Health Promotion	Case Study	Ace 2, Ace 3	Patients	Sleep
Adolescents' Daily Lives (ADL) project: an intensive longitudinal design study protocol examining the associations between physical literacy, movement behaviours, emotion regulation and mental health details	Ames, Megan; Srinivasa Gopalan, Sharan; Sihoe, C. Emmett; Craig, Stephanie G.; Garcia-Barrera, Mauricio; Liu, Sam; Rhodes, Ryan; Rush, Jonathan; Buckler, E. Jean	2024	BMJ open	Intervention	Inspire 3	Adolescents	Sleep, Steps, Intensity, Heart Rate
An adapted transdiagnostic sleep and circadian intervention for adults with excess weight and suboptimal sleep health: pilot study results details	Imes, Christopher C.; Kline, Christopher E.; Patel, Sanjay R.; Sereika, Susan M.; Buysse, Daniel J.; Harvey, Allison G.; Burke, Lora E.	2024	Sleep Advances: A Journal of the Sleep Research Society	Intervention	Charge 4	Adults	Sleep
An Outdoor Walking Program for Immigrant Muslim Older Adults: A Community-Based Participatory Intervention details	Salma, Jordana; Yamamoto, Shelby; Salbach, Nancy M.; Barclay, Ruth; Jones, Allyson	2024	Nursing Open	Intervention	Alta	Older Adults	Steps
Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study details	Singh, Rujul; Tetrick, Macy K.; Fisher, James L.; Washington, Peter; Yu, Jane; Paskett, Electra D.; Penedo, Frank J.; Clinton, Steven K.; Benzo, Roberto M.	2024	Journal of Medical Internet Research	Case Study	Device unspecified	Adults	Steps, Heart Rate
Assessing the current utilization status of wearable devices in clinical research details	Miyakoshi, Takashi; Ito, Yoichi M.	2024	Clinical Trials (London, England)	Usability, Review	Device unspecified
Assessing the impact of message relevance and frequency on physical activity change: A secondary data analysis from the random AIM trial details	Wu, Jingchuan; Brunke-Reese, Deborah; Lagoa, Constantino M.; Conroy, David E.	2024	Digital Health	Intervention	Versa	Adults	Steps, Intensity, Heart Rate
Assessment of Fitbit Charge 4 for sleep stage and heart rate monitoring against polysomnography and during home monitoring in Huntington's disease details	Doheny, Emer P.; Renerts, Klavs; Braun, Andreas; Werth, Esther; Baumann, Christian; Baumgartner, Philipp; Morgan-Jones, Philippa; Busse, Monica; Lowery, Madeleine M.; Jung, Hans H.	2024	Journal of clinical sleep medicine: JCSM: official publication of the American Academy of Sleep Medicine	Validation	Charge 4	Adults	Sleep, Heart Rate
Assessment of sleep characteristics using Fitbit Charge 4 in head and neck cancer patients undergoing palliative chemotherapy and radiotherapy: a prospective observational study details	Jain, Anuj; Suryavanshi, Jha; Waindeskar, Vaishali; Gupta, Manish; Kaushal, Ashutosh; Kumar, Harish	2024	Palliative Care and Social Practice	Case Study	Charge 4	Patients	Sleep
Association between changes in habitual stepping activity and cognition in older adults details URL ↗	O’Brien, Myles W.; Bray, Nick W.; Quirion, Isadora; Ahmadi, Shirko; Faivre, Pierre; Gallant, Francois; Gagnon, Caroline; Sénéchal, Martin; Dupuy, Olivier; Bélanger, Mathieu; Mekari, Said	2024	Scientific Reports	Intervention	Inspire 2 HR	Older Adults	Steps
Association of physical activity and screen time with cardiovascular disease risk in the Adolescent Brain Cognitive Development Study details	Nagata, Jason M.; Weinstein, Shayna; Alsamman, Sana; Lee, Christopher M.; Dooley, Erin E.; Ganson, Kyle T.; Testa, Alexander; Gooding, Holly C.; Kiss, Orsolya; Baker, Fiona C.; Pettee Gabriel, Kelley	2024	BMC public health	Case Study	Charge	Adolescents	Steps
Association of Physical Activity from Wearable Devices and Chronic Disease Risk: Insights from the All of Us Research Program details	Hou, Yu; Cui, Erjia; Ikramuddin, Sayeed; Zhang, Rui	2024	medRxiv: The Preprint Server for Health Sciences	Case Study	Device unspecified	Adults	Steps, Energy Expenditure, Intensity
Association of Remote Patient-Reported Outcomes and Step Counts With Hospitalization or Death Among Patients With Advanced Cancer Undergoing Chemotherapy: Secondary Analysis of the PROStep Randomized Trial details	Manz, Christopher R.; Schriver, Emily; Ferrell, William J.; Williamson, Joelle; Wakim, Jonathan; Khan, Neda; Kopinsky, Michael; Balachandran, Mohan; Chen, Jinbo; Patel, Mitesh S.; Takvorian, Samuel U.; Shulman, Lawrence N.; Bekelman, Justin E.; Barnett, Ian J.; Parikh, Ravi B.	2024	Journal of Medical Internet Research	Case Study	Inspire HR	Patients	Steps
Association of Wearable Derived Pulse Rate Variability With Pediatric Appendectomy Complications details	Pitt, J. Benjamin; Carter, Michela; Zeineddin, Suhail; Bai, Iris; Hua, Rui; Kwon, Soyang; Ghomrawi, Hassan; Abdullah, Fizan	2024	Journal of Pediatric Surgery	Case Study	Inspire 2, Inspire HR	Children	Heart Rate
Associations between sleep health, negative reinforcement learning, and alcohol use among South Florida college students with elevated internalizing symptoms details	Sollenberger, Nathan A.; Cummings, Logan R.; Freitag, Josefina; Trucco, Elisa M.; Gomez, Sthefany; Giraldo, Melanie; Muse, Gabriela; Mattfeld, Aaron T.; McMakin, Dana L.	2024	Alcohol (Fayetteville, N.Y.)	Case Study	Charge 4	Adults	Sleep
Associations of seasonally available global positioning systems-derived walkability and objectively measured sleep in the Nurses' Health Study 3 Mobile Health Substudy details	Hu, Cindy R.; Wilt, Grete E.; Roscoe, Charlotte; Iyer, Hari S.; Kessler, William H.; Laden, Francine; Chavarro, Jorge E.; Coull, Brent; Redline, Susan; James, Peter; Hart, Jaime E.	2024	Environmental Epidemiology (Philadelphia, Pa.)	Intervention	Charge HR, Charge 2, Charge 3	Adults	Sleep
Augmenting Prognostication: Utilizing Activity Trackers to Enhance Survival Prediction in Metastatic Non-Small Cell Lung Cancer details	Jo, Yeonjung; Puri, Sonam; Haaland, Benjamin; Coletta, Adriana M.; Chipman, Jonathan J.; Embrey, Kelsey; Kerrigan, Kathleen C.; Patel, Shiven B.; Moynahan, Kelly; Gumbleton, Matthew; Akerley, Wallace L.	2024	Clinical Lung Cancer	Usability	Alta HR, Inspire 2, Inspire HR	Patients	Steps, Distance, Intensity, Heart Rate
Autocorrelation of daily resting heart rate: A novel metric of postoperative recovery details	Carter, Michela; Hua, Rui; O'Brien, Megan K.; Benjamin Pitt, J.; Kwon, Soyang; Jayaraman, Arun; Mk Ghomrawi, Hassan; Abdullah, Fizan	2024	International Journal of Medical Informatics	Case Study	Device unspecified	Children	Heart Rate
Benefits of physical activity self-monitoring in patients with haemophilia: a prospective study with one-year follow-up details	Pérez-Alenda, Sofía; Carrasco, Juan J.; Querol-Fuentes, Felipe; Megías-Vericat, Juan Eduardo; Querol-Giner, Felipe; Luz Sánchez-Sánchez, María; Bonanad, Santiago; Núñez-Cortés, Rodrigo	2024	Haemophilia: The Official Journal of the World Federation of Hemophilia	Case Study	Charge HR	Adults	Steps, Intensity
Biometrically measured sleep in medical students as a predictor of psychological health and academic experiences in the preclinical years details	Oberleitner, Lindsay M.; Baxa, Dwayne M.; Pickett, Scott M.; Sawarynski, Kara E.	2024	Medical Education Online	Survey Research	Charge HR	Adults	Sleep
Can Wearable Technology Help Guide Dieting Safety? details	Tang, Maya; Powell, Joseph; Li, Xiao	2024	Research Square	Intervention	Versa	Adults	Heart Rate
Changes in Rest-Activity Rhythms in Adolescents as They Age: Associations With Brain and Behavioral Changes in the ABCD Study details	Zhang, Rui; Schwandt, Melanie L.; Vines, Leah; Volkow, Nora D.	2024	Journal of the American Academy of Child and Adolescent Psychiatry	Case Study	Charge	Adolescents	Sleep, Steps
Changes in rest-activity rhythms in adolescents as they age: associations with brain changes and behavior in the ABCD study details	Zhang, Rui; Schwandt, Melanie; Vines, Leah; Volkow, Nora D.	2024	medRxiv: The Preprint Server for Health Sciences	Case Study	Charge	Adolescents	Sleep, Steps
Commercially available activity monitors such as the fitbit charge and apple watch show poor validity in patients with gait aids after total knee arthroplasty details	Kooner, Paul; Baskaran, Sandhya; Gibbs, Vanessa; Wein, Sam; Dimentberg, Ronald; Albers, Anthony	2024	Journal of Orthopaedic Surgery and Research	Validation	Charge	Adults	Steps
Commonly Used Dose of Montmorency Tart Cherry Powder Does Not Improve Sleep or Inflammation Outcomes in Individuals with Overweight or Obesity details	Tucker, Robin M.; Kim, Nahyun; Gurzell, Eric; Mathi, Sruti; Chavva, Shreya; Senthilkumar, Dharshini; Bartunek, Olivia; Fenton, Kayla C.; Herndon-Fenton, Sidney J.; Cardino, Vanessa N.; Cooney, Gabrielle M.; Young, Sam; Fenton, Jenifer I.	2024	Nutrients	Case Study	Inspire 3	Adults	Sleep
Comparing self-reported energy intake using an online dietary tool with energy expenditure by an activity tracker details	Vasileiou, Aikaterina; Searle, Dominique; Larsen, Sofus C.; Magkos, Faidon; Horgan, Graham; Stubbs, R. James; Santos, Inês; Palmeira, António L.; Heitmann, Berit L.	2024	Nutrition (Burbank, Los Angeles County, Calif.)	Validation	Charge 2	Adults	Energy Expenditure, Heart Rate
Comparison of daily step count between the Fitbit Inspire 3 and the activPAL 3 in adults with transtibial amputation details	Leister, Kyle R.; Burke, Sara E.; Kim, Joon Young; Duenas, Victor H.; Barreira, Tiago V.	2024	Frontiers in Rehabilitation Sciences	Validation	Inspire 3	Adults	Steps
Comparison of raw accelerometry data from ActiGraph, Apple Watch, Garmin, and Fitbit using a mechanical shaker table details	White, James W.; Finnegan, Olivia L.; Tindall, Nick; Nelakuditi, Srihari; Brown, David E.; Pate, Russell R.; Welk, Gregory J.; de Zambotti, Massimiliano; Ghosal, Rahul; Wang, Yuan; Burkart, Sarah; Adams, Elizabeth L.; Chandrashekhar, Mvs; Armstrong, Bridget; Beets, Michael W.; Weaver, R. Glenn	2024	PloS One	Validation	Sense		Heart Rate
Cook and Move for Your Life, an eHealth intervention for women with breast cancer details	Greenlee, Heather; Rillamas-Sun, Eileen; Yung, Rachel L.; Cobos, Sofia; Donzella, Sidney M.; Huang, Yuhan; Schattenkerk, Liza; Ueland, Katherine; VanDoren, Matthew; Myers, Samantha A.; Garcia, Gino; King, Theresa; Santiago-Torres, Margarita; Di, Chongzhi; Dey, Neelendu; Guthrie, Katherine A.; Davidson, Nancy E.	2024	NPJ breast cancer	Intervention	Aria	Adults	Weight
Criterion-Related Validity of Consumer-Wearable Activity Trackers for Estimating Steps in Primary Schoolchildren under Controlled Conditions: Fit-Person Study details	Mayorga-Vega, Daniel; Casado-Robles, Carolina; Guijarro-Romero, Santiago; Viciana, Jesús	2024	Journal of Sports Science \& Medicine	Validation	Ace 2	Children	Steps
Deconstructing Fitbit to Specify the Effective Features in Promoting Physical Activity Among Inactive Adults: Pilot Randomized Controlled Trial details	Takano, Keisuke; Oba, Takeyuki; Katahira, Kentaro; Kimura, Kenta	2024	JMIR mHealth and uHealth	Intervention, Case Study	Sense	Adults	Steps, Goals
Design and rationale for a randomized clinical trial testing the efficacy of a lifestyle physical activity intervention for people with HIV and engaged in unhealthy drinking details	Abrantes, Ana M.; Ferguson, Erin; Stein, Michael D.; Magane, Kara M.; Fielman, Sarah; Karzhevsky, Skylar; Flanagan, Amanda; Siebers, Robert; Quintiliani, Lisa M.	2024	Contemporary Clinical Trials	Intervention	Device unspecified	Adults	Steps, Device Weartime
Detection of Arrhythmias Using Smartwatches-A Systematic Literature Review details	Bogár, Bence; Pető, Dániel; Sipos, Dávid; Füredi, Gábor; Keszthelyi, Antónia; Betlehem, József; Pandur, Attila András	2024	Healthcare (Basel, Switzerland)	Systematic Review	Charge, Charge HR, Charge 2, Blaze, Sense	Adults	Sleep, Heart Rate
Detection of Common Respiratory Infections, Including COVID-19, Using Consumer Wearable Devices in Health Care Workers: Prospective Model Validation Study details	Esmaeilpour, Zeinab; Natarajan, Aravind; Su, Hao-Wei; Faranesh, Anthony; Friel, Ciaran; Zanos, Theodoros P.; D'Angelo, Stefani; Heneghan, Conor	2024	JMIR formative research	Validation	Sense, Versa 3	Adults	Heart Rate
Detection of sedentary time and bouts using consumer-grade wrist-worn devices: a hidden semi-Markov model details	Salim, Agus; Brakenridge, Christian J.; Lekamlage, Dulari Hakamuwa; Howden, Erin; Grigg, Ruth; Dillon, Hayley T.; Bondell, Howard D.; Simpson, Julie A.; Healy, Genevieve N.; Owen, Neville; Dunstan, David W.; Winkler, Elisabeth A. H.	2024	BMC medical research methodology	Intervention	Versa 2, Inspire HR, Ionic	Adults	Steps, Intensity, Heart Rate
Digital phenotyping in bipolar disorder: Using longitudinal Fitbit data and personalized machine learning to predict mood symptomatology details	Lipschitz, Jessica M.; Lin, Sidian; Saghafian, Soroush; Pike, Chelsea K.; Burdick, Katherine E.	2024	Acta Psychiatrica Scandinavica	Case Study	Inspire	Adults	Sleep, Steps, Heart Rate
Digital Phenotyping of Geriatric Depression Using a Community-Based Digital Mental Health Monitoring Platform for Socially Vulnerable Older Adults and Their Community Caregivers: 6-Week Living Lab Single-Arm Pilot Study details	Song, Sunmi; Seo, YoungBin; Hwang, SeoYeon; Kim, Hae-Young; Kim, Junesun	2024	JMIR mHealth and uHealth	Intervention	Sense	Older Adults	Sleep, Steps, Heart Rate
Digital Rehabilitation Program for Breast Cancer Survivors on Adjuvant Hormonal Therapy: A Feasibility Study details	Chan, Wing-Lok; Wong, Yat-Lam; Tai, Yin-Ling; Liu, Michelle; Yun, Bryan; Zhang, Yuning; Hou, Holly Li-Yu; Kwong, Dora; Lee, Victor Ho-Fun; Lam, Wendy Wing-Tak	2024	Cancers	Intervention	Device unspecified	Adults	Steps, Intensity, Active Minutes/Active Zone Minutes
Digitizing Survivorship Care Plans Through the POST-Treatment Health Outcomes of Cancer Survivors (POSTHOC) Mobile App: Protocol for a Phase II Randomized Controlled Trial details	Chung, Kaitlin H.; Youngblood, Shari M.; Clingan, Carin L.; Deighton, Dana C.; Jump, Virginia A.; Manuweera, Thushini; McGeorge, Nicolette M.; Renn, Cynthia L.; Rosenblatt, Paula Y.; Winder, Aaron T.; Zhu, Shijun; Kleckner, Ian R.; Kleckner, Amber S.	2024	JMIR research protocols	Intervention		Patients	Sleep, Steps, Intensity
Ecological Momentary Intervention to Replace Sedentary Time With Physical Activity to Improve Executive Function in Midlife and Older Latino Adults: Pilot Randomized Controlled Trial details	Bronas, Ulf G.; Marquez, David X.; Fritschi, Cynthia; Petrarca, Katherine; Kitsiou, Spyros; Ajilore, Olu; Tintle, Nathan	2024	Journal of Medical Internet Research	Intervention	Charge 4	Adults	Steps, User Friendliness, Active Minutes/Active Zone Minutes
Effect of communicating genetic risk of type 2 diabetes and wearable technologies on wearable device-measured behavioural outcomes in East Asians: protocol of a randomised controlled trial details	Kim, Youngwon; Godino, Job G.; Cheung, Flora Lai Tung; Multhaup, Michael; Chan, Derwin King Chung K. C.; Chen, Ziyuan; Ho, Harrison Hin Sheung; Tse, Tsz Him Timothy; Au Yeung, Shiu Lun Ryan; Lou, Shan; Zhang, Joni H.; Wang, Mengyao; Chung, Brian; Griffin, Simon	2024	BMJ open	Intervention	Inspire	Adults	Steps, Intensity, Goals
Effect of desflurane maintenance on postoperative sleep quality in patients undergoing elective breast surgery: A non-inferiority randomized controlled trail details	Wang, Xiaohua; Xiong, Bingrui; Wu, Tangjing; Liu, Xin; Li, Ke; Wang, Shan; Deng, Ming-Gang; Peng, Mian	2024	Sleep Medicine	Case Study	Charge 2	Patients	Sleep
Effect of kaempferol ingestion on physical activity and sleep quality: a double-blind, placebo-controlled, randomized, crossover trial details	Ikeda, Yasutaka; Gotoh-Katoh, Aina; Okada, Shinpei; Handa, Shuichi; Sato, Teruyuki; Mizokami, Tsubasa; Saito, Bungo	2024	Frontiers in Nutrition	Case Study	Charge 4	Adults	Steps, Intensity, Heart Rate
Effectiveness of a digital health and financial incentive intervention to promote physical activity in patients with type 2 diabetes: study protocol for a randomised controlled trial with a nested qualitative study-ACTIVATE trial details	Sanders, James P.; Daley, Amanda J.; Esliger, Dale W.; Roalfe, Andrea K.; Colda, Antoanela; Turner, Joanne; Hajdu, Soma; Potter, Andrew; Humayun, Asif M.; Spiliotis, Ioannis; Reckless, Ian; Mytton, Oliver	2024	Trials	Intervention	Device unspecified	Adults	Intensity, Heart Rate
Effectiveness of a Lifestyle Improvement Support App in Combination with a Wearable Device in Japanese People with Type 2 Diabetes Mellitus: STEP-DM Study details	Takahashi, Akiko; Ishii, Manabu; Kino, Yurika; Sasaki, Kazuyo; Matsui, Takahiro; Arakawa, Kenji; Kunisaki, Makoto	2024	Diabetes Therapy: Research, Treatment and Education of Diabetes and Related Disorders	Case Study	Charge 5	Adults	Sleep, Steps, Heart Rate
Effects of a mobile health intervention on health-related outcomes in Japanese office workers: a pilot study details	Meguro, Takumi; Takayama, Fuminori; Hammarlund, Hampus; Honjo, Masaru	2024	International Journal of Occupational Medicine and Environmental Health	Intervention	Fitbit Luxe	Adults	Sleep, Steps
Effects of night-float shifts on cognitive function among radiology residents details	Flink, Carl C.; Hobohm, Robert E.; Zhang, Bin; Jacobson, Deborah L.; England, Eric B.	2024	Emergency Radiology	Case Study	Charge 3	Adults	Sleep, Steps, Energy Expenditure, Distance, Intensity
Efficacy of Activity Trackers in Patients With Heart Failure With Preserved Ejection Fraction details	Kogelschatz, Benjamin; Penn, Brittany A.; Leavitt, Ashlynn J.; Dranow, Elizabeth; Ma, Christy L.; Ryan, John J.	2024	Cureus	Medical	Device unspecified	Patients	Steps
Efficacy of Auricular Acupressure Combined With Positive Psychological Techniques on Sleep Quality in Cancer Patients Undergoing Radiotherapy: A Randomized Controlled Trial details	Bi, Liuna; Gao, Wenjuan; Zhang, Qian; Li, Na; Zhang, Xian; Han, Jing	2024	Cancer Nursing	Intervention	Charge 3	Patients	Sleep
Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial details	White, Katie M.; Carr, Ewan; Leightley, Daniel; Matcham, Faith; Conde, Pauline; Ranjan, Yatharth; Simblett, Sara; Dawe-Lane, Erin; Williams, Laura; Henderson, Claire; Hotopf, Matthew	2024	JMIR mHealth and uHealth	Intervention	Charge	Adults	Steps, Heart Rate
Engagement With Daily Symptom Reporting, Passive Smartphone Sensing, and Wearable Device Data Collection During Chemotherapy: Longitudinal Observational Study details	McClaine, Sean; Fedor, Jennifer; Bartel, Christianna; Chen, Leeann; Durica, Krina C.; Low, Carissa A.	2024	JMIR cancer	Case Study	Inspire	Patients	User Friendliness, Device Weartime
Evaluating Accuracy in Five Commercial Sleep-Tracking Devices Compared to Research-Grade Actigraphy and Polysomnography details	Kainec, Kyle A.; Caccavaro, Jamie; Barnes, Morgan; Hoff, Chloe; Berlin, Annika; Spencer, Rebecca M. C.	2024	Sensors (Basel, Switzerland)	Validation, Systematic Review	Inspire, Versa, Garmin Vivosmart	Adults	Sleep
Evaluating the impact of individuals' morningness-eveningness on the effectiveness of a habit-formation intervention for a simple and a complex behavior details	Phillips, L. Alison; More, Kimberly R.; Russell, Daniel; Kim, Hyun Seon	2024	Journal of Behavioral Medicine	Intervention	Zip	Adults	Steps
Evaluating the technical use of a Fitbit during an intervention for patients with pulmonary arterial hypertension with quality of life as primary endpoint: Lessons learned from the UPHILL study details	Kwant, Chermaine T.; de Man, Frances S.; Bogaard, Harm J.; Noordegraaf, Anton Vonk	2024	Pulmonary Circulation	Intervention	Charge 3	Patients	Steps
Evaluation of Machine Learning to Detect Influenza Using Wearable Sensor Data and Patient-Reported Symptoms: Cohort Study details	Farooq, Kamran; Lim, Melody; Dennison-Hall, Lawrence; Janson, Finn; Olszewska, Aspen Hazel; Ahmad Zabidi, Muhammad Mamduh; Haratym-Rojek, Anna; Narowski, Karol; Clinch, Barry; Prunotto, Marco; Chawla, Devika; Hunter, Victoria; Ukachukwu, Vincent	2024	Journal of Medical Internet Research	Case Study	Charge HR	Adults	Sleep, Steps, Heart Rate
Examining a Remote Group-Based Type 2 Diabetes Self-Management Education Program in the COVID-19 Era Using the ORBIT Model: Small 6-Week Feasibility Study details	Hiemstra, Madison S.; Reichert, Sonja M.; Mitchell, Marc S.	2024	JMIR formative research	Intervention	Inspire 2	Adults	Steps, Goals
Exploring Health-Related Quality of Life in Children With Hypertrophic Cardiomyopathy and Relationship to Physical Activity details	Wagner, Mitchell J.; Jeewa, Aamir; Pidborochynski, Tara; Lemaire-Paquette, Samuel; Khoury, Michael; Cunningham, Chentel; Dhillon, Santokh; Laroussi, Nassiba Alami; Vaujois, Laurence; Dallaire, Frederic; Schantz, Daryl; Armstrong, Kathryn; Mawad, Wadi; Bradley, Timothy J.; Conway, Jennifer	2024	Journal of the American Heart Association	Case Study	Charge, Charge HR	Children	Steps, Distance, Intensity, Active Minutes/Active Zone Minutes
Exploring Pain Reduction through Physical Activity: A Case Study of Seven Fibromyalgia Patients details	Jenssen, Marit Dagny Kristine; Salvi, Elisa; Fors, Egil Andreas; Nilsen, Ole Andreas; Ngo, Phuong Dinh; Tejedor, Miguel; Bellika, Johan Gustav; Godtliebsen, Fred	2024	Bioengineering (Basel, Switzerland)	Case Study	Charge 3, Charge 4, Versa 3	Patients	Steps, Intensity, Heart Rate
Exploring the Applications of Explainability in Wearable Data Analytics: Systematic Literature Review details	Abdelaal, Yasmin; Aupetit, Michaël; Baggag, Abdelkader; Al-Thani, Dena	2024	Journal of Medical Internet Research	Review	Device unspecified
Exploring the effects of fitbit incentive on treatment outcomes in veterans undergoing intensive pain rehabilitation program details	Toor, Tiffany; Palyo, Sarah; Schopmeyer, Kathryn; Simmons, Alan N.; Strigo, Irina A.	2024	Journal of Patient-Reported Outcomes	Intervention	Device unspecified	Patients	Steps, Energy Expenditure, Distance, Goals
Exploring the Use of Activity Trackers to Support Physical Activity and Reduce Sedentary Behavior in Adults Diagnosed With Type 2 Diabetes: Qualitative Interview Study Using the RE-AIM Framework details	Hodgson, William; Kirk, Alison; Lennon, Marilyn; Janssen, Xanne	2024	JMIR diabetes	Case Study	Device unspecified	Adults	Sleep, Steps, Distance, User Friendliness
Exploring the usefulness of real-time digitally supported fatigue monitoring in fatigue management: Perspectives from occupational therapists and brain injury survivors details	Ezekiel, Leisle; Wilding, Harriet; Dearling, Jeremy; Collett, Johnny; Dawes, Helen	2024	The British Journal of Occupational Therapy	Case Study	Charge 4	Adults	Intensity, User Friendliness, Active Minutes/Active Zone Minutes
Family-Focused Facilitated Fitness: Feasibility and Acceptability of a Couple-Based Physical Activity Intervention for Hematopoietic Cell Transplant Recipients and their Caregiving Partners details	Langer, Shelby L.; Joseph, Rodney P.; Mistretta, Erin; Tao, Chun; Porter, Laura; Spain, Allison; Khera, Nandita	2024	Transplantation and Cellular Therapy	Intervention	Inspire 2	Adults	Steps
Feasibility and preliminary effects of the Fit2ThriveMB pilot physical activity promotion intervention on physical activity and patient reported outcomes in individuals with metastatic breast cancer details	Phillips, Siobhan M.; Starikovsky, Julia; Solk, Payton; Desai, Ria; Reading, Jean M.; Hasanaj, Kristina; Wang, Shirlene D.; Cullather, Erin; Lee, Jungwha; Song, Jing; Spring, Bonnie; Gradishar, William	2024	Breast Cancer Research and Treatment	Intervention	Device unspecified	Patients	Steps, Goals, Device Weartime
Feasibility characteristics of wrist-worn fitness trackers in health status monitoring for post-COVID patients in remote and rural areas details	Wiebe, Madeleine; Mackay, Marnie; Krishnan, Ragur; Tian, Julie; Larsson, Jakob; Modanloo, Setayesh; Job McIntosh, Christiane; Sztym, Melissa; Elton-Smith, Gail; Rose, Alyssa; Ho, Chester; Greenshaw, Andrew; Cao, Bo; Chan, Andrew; Hayward, Jake	2024	PLOS digital health	Usability	Charge 2	Patients	Sleep, Steps, Heart Rate
Feasibility of application-based psychomotor vigilance testing to assess fatigue in doctors working night shifts and correlation with smartwatch assessed shift intensity details	Weetman, Stefan; Roche, Matthew; Leckie, Todd; Samuels, Theophilus; Hodgson, Luke	2024	Occupational and Environmental Medicine	Usability, Case Study	Versa 2	Adults	Steps, Active Minutes/Active Zone Minutes
Feasibility of at-Home Sleep Monitoring in Adolescents with and without Concussion details	Donahue, Catherine C.; Smulligan, Katherine L.; Wingerson, Mathew J.; Kniss, Joshua R.; Simon, Stacey L.; Wilson, Julie C.; Howell, David R.	2024	Nature and Science of Sleep	Usability	Charge 2	Adolescents	Sleep
Feasibility of Fit24, a Digital Diabetes Prevention Program for Hispanic Adolescents: Qualitative Evaluation Study details	Soltero, Erica G.; Musaad, Salma M.; O'Connor, Teresia M.; Thompson, Debbe; Norris, Keith; Beech, Bettina M.	2024	JMIR formative research	Intervention	Charge 5	Children	Steps, User Friendliness
Feasibility of wearable sensor signals and self-reported symptoms to prompt at-home testing for acute respiratory viruses in the USA (DETECT-AHEAD): a decentralised, randomised controlled trial details	Quer, Giorgio; Coughlin, Erin; Villacian, Jorge; Delgado, Felipe; Harris, Katherine; Verrant, John; Gadaleta, Matteo; Hung, Ting-Yang; Ter Meer, Janna; Radin, Jennifer M.; Ramos, Edward; Adams, Monique; Kim, Lomi; Chien, Jason W.; Baca-Motes, Katie; Pandit, Jay A.; Talantov, Dmitri; Steinhubl, Steven R.	2024	The Lancet. Digital Health	Intervention	Sense	Adults	Sleep, Steps, Heart Rate
Feasibility Study on Menstrual Cycles With Fitbit Device (FEMFIT): Prospective Observational Cohort Study details	Lang, Anna-Lena; Bruhn, Rosa-Lotta; Fehling, Maya; Heidenreich, Anouk; Reisdorf, Jonathan; Khanyaree, Ifrah; Henningsen, Maike; Remschmidt, Cornelius	2024	JMIR mHealth and uHealth	Case Study	Inspire 2	Adults	Sleep, Steps, Heart Rate
Feeling Younger on Active Summer Days? On the Interplay of Behavioral and Environmental Factors With Day-to-Day Variability in Subjective Age details	Schmidt, Laura I.; Rupprecht, Fiona S.; Gabrian, Martina; Jansen, Carl-Philipp; Sieverding, Monika; Wahl, Hans-Werner	2024	Innovation in Aging	Case Study	Charge HR	Older Adults	Steps, Intensity
Fitbit's accuracy to measure short bouts of stepping and sedentary behaviour: validation, sensitivity and specificity study details	Delobelle, Julie; Lebuf, Elien; Dyck, Delfien Van; Compernolle, Sofie; Janek, Michael; Backere, Femke De; Vetrovsky, Tomas	2024	Digital Health	Validation, Intervention	Inspire 2, Ionic	Adults	Steps
From intention to behavior: Within- and between-person moderators of the relationship between intention and physical activity details	Knapova, Lenka; Cho, Young Won; Chow, Sy-Miin; Kuhnova, Jitka; Elavsky, Steriani	2024	Psychology of Sport and Exercise	Case Study	Charge 3, Charge 4	Adults	Steps
Healthy at Home for COPD: An Integrated Digital Monitoring, Treatment, and Pulmonary Rehabilitation Intervention details	O'Connor, Laurel; Behar, Stephanie; Tarrant, Seanan; Stamegna, Pamela; Pretz, Caitlin; Shirshac, Jeanne; Scornavacca, Thomas; Wilkie, Tracey; Fisher, Kimberly; Tigas, Emil; Mullen, Marie; Hyder, Michael; Wong, Steven; Savage, Brendon; Toomey, Shaun; Wang, Biqi; Zai, Adrian; Alper, Eric; Lindenauer, Peter; Dickson, Eric; Broach, John; McManus, David; Kheterpal, Vik; Soni, Apurv	2024	Research Square	Intervention	Charge 5	Patients	Heart Rate, Device Weartime
Heart Rate Monitoring Among Breast Cancer Survivors: Quantitative Study of Device Agreement in a Community-Based Exercise Program details	Page, Lindsey L.; Fanning, Jason; Phipps, Connor; Berger, Ann; Reed, Elizabeth; Ehlers, Diane	2024	JMIR cancer	Intervention	Inspire HR	Adults	Heart Rate
Home-based circuit training and community walking for intermittent claudication details	Waddell, Alexander; Denton, Francesca; Powell, Richard; Broom, David R.; Birkett, Stefan T.; McGregor, Gordon; Harwood, Amy E.	2024	Annals of Vascular Surgery	Intervention	Charge 4	Patients	Steps
Imagery rescripting and cognitive restructuring for inpatients with moderate and severe depression - a controlled pilot study details	Kanczok, Jabin; Jauch-Chara, Kamila; Müller, Franz-Josef	2024	BMC psychiatry	Intervention	Charge 3	Patients	Steps
Impact of Environmental Noise and Sleep Health on Pediatric Hypertension Incidence: ABCD Study details	De Moraes, Augusto César F.; Ma, Martin Y.; Nascimento-Ferreira, Marcus V.; Hunt, Ethan H.; Hoelscher, Deanna M.	2024	Journal of the American Heart Association	Case Study	Charge HR 2	Adolescents	Sleep
Impact of Outdoor Play Structures on Moderate to Vigorous Physical Activity in Children during Recess: A Comparative Study details	Fuentes Diaz, Maria Fernanda; Sénéchal, Martin; Bouchard, Danielle R.	2024	Children (Basel, Switzerland)	Case Study	Inspire 2	Children	Intensity, Heart Rate
Implementation of a randomized mobile-technology lifestyle program in individuals with nonalcoholic fatty liver disease details	Tincopa, Monica A.; Patel, Nik; Shahab, Areesha; Asefa, Haila; Lok, Anna S.	2024	Scientific Reports	Intervention	Zip	Patients	Steps
Improving Early Prediction of Abnormal Recovery after Appendectomy in Children using Real-world Data from Wearables details	Hua, Rui; O'Brien, Megan K.; Carter, Michela; Pitt, J. Benjamin; Kwon, Soyang; Ghomrawi, Hassan M. K.; Jayaraman, Arun; Abdullah, Fizan	2024	Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference	Case Study	Inspire 2	Patients	Sleep, Steps, Heart Rate
Improving multimodal physical function in adults with heterogeneous chronic pain; Protocol for a multisite feasibility RCT details	Hooker, Julia E.; Brewer, Julie R.; McDermott, Katherine; Kanaya, Millan; Somers, Tamara J.; Keefe, Francis; Kelleher, Sarah; Fisher, Hannah M.; Burns, John; Wilson, Rebecca; Kulich, Ronald; Polykoff, Gary; Parker, Robert A.; Greenberg, Jonathan; Vranceanu, Ana-Maria; THRIVE Study TeamJennifer Plumb-Vilardaga, PhD. Shannon Miller, Allison Diachina, Sara Hogan, Latrice Yates	2024	Contemporary Clinical Trials	Intervention	Inspire 3	Adults	Steps, Goals
Increased Steps in Japanese Older Adults Associated with Improved Winter Sleep Quality details	Harai, Nozomi; Okuma, Hideyuki; Tsuchiya, Kyoichiro; Matsuoka, Satoshi; Kashiwagi, Kenji	2024	Gerontology \& Geriatric Medicine	Case Study	Charge 5	Older Adults	Sleep
Individual-Level Experiences of Structural Inequity and Their Association with Subjective and Objective Sleep Outcomes in the Adolescent Brain Cognitive Development Study details	Harriman, Nigel Walsh; Chen, Jarvis T.; Lee, Sunmin; Slopen, Natalie	2024	The Journal of Adolescent Health: Official Publication of the Society for Adolescent Medicine	Case Study	Charge HR	Adolescents	Sleep
Integrating genome-wide information and wearable device data to explore the link of anxiety and antidepressants with pulse rate variability details	Friligkou, Eleni; Koller, Dora; Pathak, Gita A.; Miller, Edward J.; Lampert, Rachel; Stein, Murray B.; Polimanti, Renato	2024	Molecular Psychiatry	Case Study	Device unspecified	Adults	Steps, Heart Rate
Leveraging mHealth Technologies for Public Health details	Velmovitsky, Pedro Elkind; Kirolos, Merna; Alencar, Paulo; Leatherdale, Scott; Cowan, Donald; Morita, Plinio Pelegrini	2024	JMIR public health and surveillance	Review	Device unspecified	Older Adults	User Friendliness
Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis details	Zhang, Yuezhou; Folarin, Amos A.; Sun, Shaoxiong; Cummins, Nicholas; Ranjan, Yatharth; Rashid, Zulqarnain; Stewart, Callum; Conde, Pauline; Sankesara, Heet; Laiou, Petroula; Matcham, Faith; White, Katie M.; Oetzmann, Carolin; Lamers, Femke; Siddi, Sara; Simblett, Sara; Vairavan, Srinivasan; Myin-Germeys, Inez; Mohr, David C.; Wykes, Til; Haro, Josep Maria; Annas, Peter; Penninx, Brenda Wjh; Narayan, Vaibhav A.; Hotopf, Matthew; Dobson, Richard Jb; RADAR-CNS consortium	2024	Journal of Medical Internet Research	Case Study	Charge 2, Charge 3	Adults	Sleep, Steps, Heart Rate
Mental and Physical Readiness for Weight Loss After Abdominal Organ Transplant details	Cote, Maria P.; Atthota, Srilakshmi; MacDonald, Anne; Cataldo, Jennie; Shah, Anushi; Flores, Flor; Singh, Ruby; Elias, Nahel; Dageforde, Leigh Anne	2024	The Journal of Surgical Research	Intervention	Charge 4	Patients	Steps
MHealth devices demonstrate validity and reliability in detecting steps in chronic stroke survivors who rely on assistive devices details	Vieira Costa, Pollyana Helena; Thome Teixeira da Silva, Leonardo Vinicius; Dias de Jesus, Thainá Paula; Dario, Daniella Moura; Torriani-Pasin, Camila; Polese, Janaine Cunha	2024	Journal of Bodywork and Movement Therapies	Validation	Ultra	Adults	Steps
Missing Data Statistics Provide Causal Insights into Data Loss in Diabetes Health Monitoring by Wearable Sensors details	Braem, Carlijn I. R.; Yavuz, Utku S.; Hermens, Hermie J.; Veltink, Peter H.	2024	Sensors (Basel, Switzerland)	Systematic Review	Charge HR, Charge 2	Patients	Steps, Heart Rate
Modeling engagement with a digital behavior change intervention (HeartSteps II): An exploratory system identification approach details	De La Torre, Steven A.; El Mistiri, Mohamed; Hekler, Eric; Klasnja, Predrag; Marlin, Benjamin; Pavel, Misha; Spruijt-Metz, Donna; Rivera, Daniel E.	2024	Journal of Biomedical Informatics	Intervention	Versa	Adults	Steps
Monitoring Substance Use with Fitbit Biosignals: A Case Study on Training Deep Learning Models Using Ecological Momentary Assessments and Passive Sensing details	Li, Shizhe; Fan, Chunzhi; Kargarandehkordi, Ali; Sun, Yinan; Slade, Christopher; Jaiswal, Aditi; Benzo, Roberto M.; Phillips, Kristina T.; Washington, Peter	2024	AI (Basel, Switzerland)	Case Study	Charge 5	Adults	Sleep, Steps, Heart Rate
Neuroplastic Responses to Chiropractic Care: Broad Impacts on Pain, Mood, Sleep, and Quality of Life details	Haavik, Heidi; Niazi, Imran Khan; Amjad, Imran; Kumari, Nitika; Ghani, Usman; Ashfaque, Moeez; Rashid, Usman; Navid, Muhammad Samran; Kamavuako, Ernest Nlandu; Pujari, Amit N.; Holt, Kelly	2024	Brain Sciences	Intervention	Device unspecified	Adults	Sleep, Steps, Heart Rate, Active Minutes/Active Zone Minutes
Optimization of mHealth behavioral interventions for patients with chronic lymphocytic leukemia: the HEALTH4CLL study details	Lee, Che Young; Gordon, Max J.; Markofski, Melissa M.; LaVoy, Emily C.; Peterson, Susan K.; Li, Liang; Fares, Sara; Baum, Miranda; Pace, Margaret; Walsh, Danielle; Ferrajoli, Alessandra; Basen-Engquist, Karen	2024	Journal of Cancer Survivorship: Research and Practice	Intervention	Device unspecified	Patients	Steps, Energy Expenditure, Food, Goals, Active Minutes/Active Zone Minutes
Participatory development of an mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED) details	Novak, Jan; Jurkova, Katerina; Lojkaskova, Anna; Jaklova, Andrea; Kuhnova, Jitka; Pfeiferova, Marketa; Kral, Norbert; Janek, Michael; Omcirk, Dan; Malisova, Katerina; Maes, Iris; Dyck, Delfien Van; Wahlich, Charlotte; Ussher, Michael; Elavsky, Steriani; Cimler, Richard; Pelclova, Jana; Tufano, James J.; Steffl, Michal; Seifert, Bohumil; Yates, Tom; Harris, Tess; Vetrovsky, Tomas	2024	BMC public health	Intervention	Inspire 2	Patients	Steps
Patterns of virtual reality and Fitbit wearable activity device use after skull base surgery details	Pandrangi, Vivek C.; Araujo, Ana; Buncke, Michelle; Olson, Brennan; Jorizzo, Matthew; Said-Al-Naief, Nasser; Sanusi, Olabisi; Ciporen, Jeremy; Shindo, Maisie; Schindler, Joshua; Colaianni, C. Alessandra; Clayburgh, Daniel; Andersen, Peter; Flint, Paul; Wax, Mark K.; Geltzeiler, Mathew; Li, Ryan J.	2024	International Forum of Allergy \& Rhinology	Intervention	Device unspecified	Patients	Steps
Perceived and physiological strains of societal participation in people with multiple sclerosis: a real-time assessment study details	Gravesteijn, Arianne S.; Ouwerkerk, Maaike; Eijssen, Isaline C. J. M.; Beckerman, Heleen; De Groot, Vincent	2024	Journal of Rehabilitation Medicine	Case Study	Charge 2, Charge 3	Adults	Heart Rate
Performance of wearable sleep trackers during nocturnal sleep and periods of simulated real-world smartphone use details	Willoughby, Adrian R.; Golkashani, Hosein Aghayan; Ghorbani, Shohreh; Wong, Kian F.; Chee, Nicholas I. Y. N.; Ong, Ju Lynn; Chee, Michael W. L.	2024	Sleep Health	Validation	Sense	Adults	Sleep
Physical activity and menopausal symptoms: evaluating the contribution of obesity, fitness, and ambient air pollution status details	Elavsky, Steriani; Burda, Michal; Cipryan, Lukáš; Kutáč, Petr; Bužga, Marek; Jandačková, Vera; Chow, Sy-Miin; Jandačka, Daniel	2024	Menopause (New York, N.Y.)	Case Study	Charge 3	Adults, Older Adults	Intensity
Physical activity and sedentary behaviour of Bahraini people with type 2 diabetes: A cross-sectional study details	Rajab, Ebrahim; Wasif, Pearl; Doherty, Sally; Gaynor, Declan; Malik, Hani; Fredericks, Salim; Al-Qallaf, Amal; Almuqahwi, Rabab; Alsharbati, Wafa; Rashid-Doubell, Fiza	2024	Digital Health	Case Study	Flex 2	Adults	Steps, Intensity
Physical Activity and Sedentary Time Among U.S. Adolescents Before and During COVID-19: Findings From a Large Cohort Study details	Hunt, Ethan T.; Brazendale, Keith; De Moraes, Augusto C. F.; Malkani, Raja; Heredia, Natalia I.; Pfledderer, Christopher D.; Brown, Denver M.; Hoelscher, Deanna M.; Beets, Michael W.; Weaver, Robert G.	2024	AJPM focus	Case Study	Charge 2	Adolescents	Steps, Intensity
Physical activity decreases in patients on the liver transplant waiting list and influences postoperative outcome-a prospective cohort study details	Magyar, Christian T. J.; Bühlmann, Lea; Becchetti, Chiara; Beekman, Lara; Candinas, Daniel; Beldi, Guido; Kim-Fuchs, Corina; Berzigotti, Annalisa; Banz, Vanessa	2024	Hepatobiliary Surgery and Nutrition	Case Study	Charge 2	Patients	Steps, Energy Expenditure, Distance, Intensity
Physical activity patterns of children and adolescents with Down syndrome: Using the Fitbit and parental proxy questionnaire details	Yang, Seung Hyeon; Kim, Hwa In; Van Riper, Marcia; Choi, Eun Kyoung	2024	Journal of Pediatric Nursing	Case Study	Charge 5	Children, Adolescents	Steps, Energy Expenditure, Intensity
Pilot evaluation on an adapted tele-behavioral activation to increase physical activity in persons with depression: a single-arm pilot study details	Rethorst, Chad D.; Trombello, Joseph M.; Chen, Patricia M.; Carmody, Thomas J.; Goodman, Lynnel C.; Lazalde, Alejandra; Trivedi, Madhukar H.	2024	BMC psychology	Intervention	Inspire HR	Adults	Steps, Intensity, Active Minutes/Active Zone Minutes
Pilot Randomized Controlled Trial of Lymfit: A Theory-Guided Exercise Intervention for Young Adults with Lymphoma details	Tock, Wing Lam; Johnson, Nathalie A.; Andersen, Ross E.; Salaciak, Matthew; Angelillo, Christopher; Loiselle, Carmen G.; Hébert, Maude; Maheu, Christine	2024	Healthcare (Basel, Switzerland)	Intervention	Charge 5	Adults	Steps, Device Weartime
Pilot study comparing sleep logs to a commercial wearable device in describing the sleep patterns of physicians-in-training details	Hassinger, Amanda B.; Kwon, Misol; Wang, Jia; Mishra, Archana; Wilding, Gregory E.	2024	PloS One	Usability	Inspire	Adults	Sleep
Predicting long-term sleep deprivation using wearable sensors and health surveys details	Trujillo, Rafael; Zhang, Enshi; Templeton, John Michael; Poellabauer, Christian	2024	Computers in Biology and Medicine	Measurement	Charge HR	Adults	Steps, Active Minutes/Active Zone Minutes
Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers details	Xu, Qidi; Kim, Yejin; Chung, Karen; Schulz, Paul; Gottlieb, Assaf	2024	JMIR formative research	Case Study	Charge 4	Patients	Sleep, Steps, Heart Rate
Preoperative determinants of normative postoperative recovery rate following minimally invasive repair of pectus excavatum details	Carter, Michela; Chen, Austin R.; Pitt, J. Benjamin; Hua, Rui; Edobor, Arianna; Kwon, Soyang; Goldstein, Seth D.; Ghomrawi, Hassan M. K.; Abdullah, Fizan	2024	Pediatric Surgery International	Case Study	Inspire 2	Patients, Children	Steps, Heart Rate, Device Weartime
Promoting Healthy Aging for Older People Living with Chronic Disease by Implementing Community Health Programs: A Randomized Controlled Feasibility Study details	Hill, Anne-Marie; Starling, Trish; Xin, Wei; Naseri, Chiara; Xu, Dan; O'Brien, Geraldine; Etherton-Beer, Christopher; Flicker, Leon; Bulsara, Max; Morris, Meg E.; Vaz, Sharmila	2024	International Journal of Environmental Research and Public Health	Intervention	Inspire 2	Older Adults	Steps
Prospective associations between Sleep, Sensation-Seeking and Mature Screen Usage in Early Adolescents: Findings from the Adolescent Brain Cognitive Development (ABCD) Study details	Zhang, Linhao; Oshri, Assaf; Carvalho, Cory; Uddin, Lucina Q.; Geier, Charles; Nagata, Jason M.; Cummins, Kevin; Hoffman, Elizabeth A.; Tomko, Rachel L.; Chaarani, Bader; Squeglia, Lindsay M.; Wing, David; Mason, Michael J.; Fuemmeler, Bernard; Lisdahl, Krista; Tapert, Susan F.; Baker, Fiona C.; Kiss, Orsolya	2024	Sleep	Case Study	Charge HR	Adolescents	Sleep
Psychological and behavioral responses to daily weight gain during behavioral weight loss treatment details	Hagerman, Charlotte J.; Onu, Michael C.; Crane, Nicole T.; Butryn, Meghan L.; Forman, Evan M.	2024	Journal of Behavioral Medicine	Case Study	Device unspecified	Adults	Steps, Energy Expenditure
Randomized controlled trial of a multiple technology-based physical activity intervention for Latina adolescents: Recruitment strategies and baseline data from the Chicas Fuertes trial details	Naqvi, Jeanean B.; Olesen, Brittany; Greenstadt, Emily; Carson, Jacob; Marcus, Bess; Godino, Job; Zive, Michelle; Meyer, Dawn; Higgins, Michael; Osuna, Lilliana; Gomez, Rubi; Dunsiger, Shira; Larsen, Britta	2024	Contemporary Clinical Trials	Intervention	Inspire HR	Adolescents	Steps, Intensity
Rationale, Design, and Baseline Characteristics of Participants in the Health@NUS mHealth Augmented Cohort Study Examining Student-to-Work Life Transition: Protocol for a Prospective Cohort Study details	Chua, Xin Hui; Edney, Sarah Martine; Müller, Andre Matthias; Petrunoff, Nicholas A.; Whitton, Clare; Tay, Zoey; Goh, Claire Marie Jie Lin; Chen, Bozhi; Park, Su Hyun; Rebello, Salome A.; Low, Alicia; Chia, Janelle; Koek, Daphne; Cheong, Karen; van Dam, Rob M.; Müller-Riemenschneider, Falk	2024	JMIR research protocols	Case Study	Versa Lite	Adults	Steps, Energy Expenditure, Intensity, Heart Rate, Active Minutes/Active Zone Minutes
Real-time biopsychosocial antecedents and correlates of functional neurological symptoms in daily life: A pilot remote monitoring technology study details	Pick, Susannah; Millman, L. S. Merritt; Davies, Jessica; Hodsoll, John; Stanton, Biba; David, Anthony S.; Edwards, Mark J.; Goldstein, Laura H.; Mehta, Mitul A.; Nicholson, Timothy R.; Reinders, A. a. T. S.; Winston, Joel S.; Chalder, Trudie; Hotopf, Matthew	2024	Psychiatry Research	Case Study	Charge 5	Adults	Sleep, Heart Rate, Device Weartime
Real-World Accuracy of Wearable Activity Trackers for Detecting Medical Conditions: Systematic Review and Meta-Analysis details	Singh, Ben; Chastin, Sebastien; Miatke, Aaron; Curtis, Rachel; Dumuid, Dorothea; Brinsley, Jacinta; Ferguson, Ty; Szeto, Kimberley; Simpson, Catherine; Eglitis, Emily; Willems, Iris; Maher, Carol	2024	JMIR mHealth and uHealth	Systematic Review	Device unspecified	Adults	Heart Rate
Reducing the burden of inconclusive smart device single-lead ECG tracings via a novel artificial intelligence algorithm details	Weidlich, Simon; Mannhart, Diego; Kennedy, Alan; Doggart, Peter; Serban, Teodor; Knecht, Sven; Du Fay de Lavallaz, Jeanne; Kühne, Michael; Sticherling, Christian; Badertscher, Patrick	2024	Cardiovascular Digital Health Journal	Case Study	Sense	Adults, Patients	Heart Rate
Relationship Between Heart Rate and Perceived Stress in Intensive Care Unit Residents: Exploratory Analysis Using Fitbit Data details	Wang, Ruijing; Rezaeian, Olya; Asan, Onur; Zhang, Linghan; Liao, Ting	2024	JMIR formative research	Case Study	Charge 3	Adults	Heart Rate
Relationship between physical activity and biomarkers of pathology and neuroinflammation in preclinical autosomal-dominant Alzheimer's disease details	Guzmán-Vélez, Edmarie; Rivera-Hernández, Angelys; Fabrega, Sofia; Oliveira, Gabriel; Martínez, Jairo E.; Baena, Ana; Picard, Glen; Lopera, Francisco; Arnold, Steven E.; Taylor, J. Andrew; Quiroz, Yakeel T.	2024	Alzheimer's \& Dementia (New York, N. Y.)	Case Study	Charge 4	Adults	Steps, Intensity, Heart Rate
Scrolling Your Sleep Away: The Effects of Bedtime Device Use on Sleep Among Young Adults with Poor Sleep details	Chkhaidze, Ana; Millar, Brett M.; Revenson, Tracey A.; Mindlis, Irina	2024	International Journal of Behavioral Medicine	Intervention	Charge 3	Adults	Sleep
Sensor-Based Frailty Assessment Using Fitbit details	Hosseinalizadeh, Mohammad; Asghari, Mehran; Toosizadeh, Nima	2024	Sensors (Basel, Switzerland)	Usability	Sense 2	Adults	Heart Rate
Sleep Behavior in Royal Australian Navy Shift Workers by Shift and Exposure to the SleepTank App details	Devine, Jaime K.; Cooper, Nadine; Choynowski, Jake; Hursh, Steven R.	2024	Military Medicine	Measurement	Versa 2	Adults	Sleep
Step cadence as a novel objective postoperative recovery metric in children who undergo laparoscopic appendectomy details	Carter, Michela; Zeineddin, Suhail; Bai, Iris; Pitt, J. Benjamin; Hua, Rui; Kwon, Soyang; Ghomrawi, Hassan M. K.; Abdullah, Fizan	2024	Surgery	Case Study	Inspire 2, Inspire HR	Patients, Children	Steps
Supervised machine learning to predict smoking lapses from Ecological Momentary Assessments and sensor data: Implications for just-in-time adaptive intervention development details	Perski, Olga; Kale, Dimitra; Leppin, Corinna; Okpako, Tosan; Simons, David; Goldstein, Stephanie P.; Hekler, Eric; Brown, Jamie	2024	PLOS digital health	Case Study	Charge 4	Adults	Steps, Heart Rate
Technological monitoring of motor parameters to assess multidimensional frailty of older people in the PRO-HOME project details	Seminerio, Emanuele; Morganti, Wanda; Barbagelata, Marina; Sabharwal, Sanket Rajeev; Ghisio, Simone; Prete, Camilla; Senesi, Barbara; Dini, Simone; Custureri, Romina; Galliani, Simonetta; Morelli, Simona; Puleo, Gianluca; Berutti-Bergotto, Carlo; Camurri, Antonio; Pilotto, Alberto; PRO-HOME Project Investigators Group	2024	Scientific Reports	Intervention	Sense	Patients	Steps, Distance
Testing the Reliability and Validity of the Korean Version of the Pittsburgh Sleep Quality Index Using Fitbit Devices: A Cross-Sectional Analysis details	Lee, Si-Yeon; Choi, Ja-Eun; Lee, Ji-Won; Lee, Yaeji; Park, Jae-Min; Hong, Kyung-Won	2024	Korean Journal of Family Medicine	Validation	Device unspecified	Adults	Sleep
Text Messages to Promote Physical Activity in Patients With Cardiovascular Disease: A Micro-Randomized Trial of a Just-In-Time Adaptive Intervention details	Golbus, Jessica R.; Shi, Jieru; Gupta, Kashvi; Stevens, Rachel; Jeganathan, V. Swetha E.; Luff, Evan; Boyden, Thomas; Mukherjee, Bhramar; Kohnstamm, Sarah; Taralunga, Vlad; Kheterpal, Vik; Kheterpal, Sachin; Resnicow, Kenneth; Murphy, Susan; Dempsey, Walter; Klasnja, Predrag; Nallamothu, Brahmajee K.	2024	Circulation. Cardiovascular Quality and Outcomes	Intervention	Versa	Adults	Steps
The acceptability of using wearable electronic devices to monitor physical activity of patients with Multiple Myeloma undergoing treatment: a systematic review details	Brown, Tommy; Muls, Ann; Pawlyn, Charlotte; Boyd, Kevin; Cruickshank, Susanne	2024	Clinical Hematology International	Systematic Review	Flex, Alta, Inspire 2	Adults	Sleep, Steps
The Annual Rhythms in Sleep, Sedentary Behavior, and Physical Activity of Australian Adults: A Prospective Cohort Study details	Ferguson, Ty; Curtis, Rachel; Fraysse, François; Olds, Timothy; Dumuid, Dorothea; Brown, Wendy; Esterman, Adrian; Maher, Carol	2024	Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine	Case Study	Charge 3	Adults	Sleep, Intensity
The Association Between Direct Health Costs Related to Non-communicable Diseases and Physical Activity in Elderly People details	Zhang, Junlong; Li, Bo	2024	Journal of Prevention (2022)	Case Study	Flex 2	Older Adults	Steps, Energy Expenditure
The Comprehensive Resilience-building psychosocial Intervention (CREST) for people with dementia in the community: a feasibility and acceptability study details	Casey, Dympna; Doyle, Priscilla; Gallagher, Niamh; O'Sullivan, Grace; Smyth, Siobhán; Devane, Declan; Murphy, Kathy; Clarke, Charlotte; Woods, Bob; Dröes, Rose-Marie; Windle, Gill; Murphy, Andrew W.; Foley, Tony; Timmons, Fergus; Gillespie, Paddy; Hobbins, Anna; Newell, John; Abedin, Jaynal; Domegan, Christine; Irving, Kate; Whelan, Barbara	2024	Pilot and Feasibility Studies	Intervention	Device unspecified	Older Adults	User Friendliness
The Effect of Inhaled Beta-2 Agonists on Heart Rate in Patients With Asthma: Sensor-Based Observational Study details	Khusial, Rishi Jayant; Sont, Jacob K.; Usmani, Omar S.; Bonini, Matteo; Chung, Kian Fan; Fowler, Stephen James; Honkoop, Persijn J.	2024	JMIR cardio	Case Study	Charge HR	Patients	Heart Rate
The effects of COVID-19 lockdown and reopening on rest-activity rhythms in Singaporean working adults: A longitudinal age group comparison study details	Qin, Shuo; Ong, Ju Lynn; Chia, Janelle; Low, Alicia; Lee, Charmaine; Koek, Daphne; Cheong, Karen; Chee, Michael Wei Liang	2024	Sleep Health	Case Study	Versa	Adults, Older Adults	Sleep, Steps
The effects of weather on physical activity and sedentary behaviour in older adults details	Crosby, Kathryn M.; Adams, Brittany; Zambrano Garza, Elizabeth; Bourbonnais, Mathieu L.; Fenton, Melanie; Hoppmann, Christiane; Jakobi, Jennifer M.	2024	Frontiers in Sports and Active Living	Usability	Charge 4	Older Adults	Steps, Intensity
The experiences of people with chronic obstructive pulmonary disease (COPD) using activity monitors in everyday life: an interpretative phenomenological study details	Wilde, Laura J.; Percy, Carol; Ward, Gillian; Clark, Cain; Wark, Petra A.; Sewell, Louise	2024	Disability and Rehabilitation	Usability	Device unspecified	Adults	User Friendliness
The moderating effect of social support on the effectiveness of a web-based, computer-tailored physical activity intervention for older adults details	Alley, Stephanie J.; Schoeppe, Stephanie; Moore, Hayley; To, Quyen G.; van Uffelen, Jannique; Parker, Felix; Duncan, Mitch J.; Schneiders, Anthony; Vandelanotte, Corneel	2024	Journal of Health Psychology	Intervention	Device unspecified	Older Adults	Intensity
The relationship between wearable-derived sleep features and relapse in Major Depressive Disorder details	Matcham, F.; Carr, E.; Meyer, N.; White, K. M.; Oetzmann, C.; Leightley, D.; Lamers, F.; Siddi, S.; Cummins, N.; Annas, P.; de Girolamo, G.; Haro, J. M.; Lavelle, G.; Li, Q.; Lombardini, F.; Mohr, D. C.; Narayan, V. A.; Penninx, B. W. H. J.; Coromina, M.; Riquelme Alacid, G.; Simblett, S. K.; Nica, R.; Wykes, T.; Brasen, J. C.; Myin-Germeys, I.; Dobson, R. J. B.; Folarin, A. A.; Ranjan, Y.; Rashid, Z.; Dineley, J.; Vairavan, S.; Hotopf, M.; RADAR-CNS consortium	2024	Journal of Affective Disorders	Case Study	Charge	Adults	Sleep
The Utility and Limitations of Remotely Delivered Feedback Messages Regarding Physical Activity in a 12-Month Weight Loss Intervention: Insights From the SMARTER Trial Focus Groups details	Kariuki, Jacob Kigo; Burke, Lora E.; Zickmund, Susan; Beatrice, Britney; Kimball, Elisabeth R.; Galyean, Patrick; Cheng, Jessica; Sereika, Susan M.; Bizhanova, Zhadyra; Cedillo, Maribel; Wells, Jessica; Conroy, Molly B.	2024	The Journal of Cardiovascular Nursing	Intervention	Charge 2, Aria 2	Adults	Steps, Weight, User Friendliness
Unlocking the potential of wearable device wear time to enhance postpartum depression screening and detection details	Hurwitz, Eric; Meltzer-Brody, Samantha; Butzin-Dozier, Zachary; Patel, Rena C.; Elhadad, Noémie; Haendel, Melissa A.	2024	medRxiv: The Preprint Server for Health Sciences	Case Study	Device unspecified	Pregnant Women	Steps, Energy Expenditure, Heart Rate, Device Weartime
Use of commercial WAMs for monitoring individual with lung cancer. A systematic review details	Bahadori, Shayan; Hosseini, Mozhdeh	2024	Lung Cancer (Amsterdam, Netherlands)	Systematic Review	Device unspecified	Patients
Using formative process evaluation to improve program implementation and accessibility of competitive group-based physical activity in the TEAM-PA trial details	Sweeney, Allison M.; Wilson, Dawn K.; Zarrett, Nicole; Simmons, Timothy; Mansfield, Makayla; Decker, Lindsay	2024	The International Journal of Behavioral Nutrition and Physical Activity	Intervention	Inspire	Adults	Steps
Using Positive Psychology to Address Emotional Barriers to Physical Activity After Bariatric Surgery: Proof-of-Concept Trial of the Gaining Optimism After Weight Loss Surgery (GOALS) Project details	Feig, Emily H.; Szapary, Claire; Harnedy, Lauren E.; Castillo, Crystal; Thorndike, Anne N.; Psaros, Christina; Millstein, Rachel A.; Huffman, Jeff C.	2024	Cognitive and Behavioral Practice	Intervention	Device unspecified	Adults, Patients
Validation of ActiGraph and Fitbit in the assessment of energy expenditure in Huntington's disease details	Simón-Vicente, Lucía; Rodríguez-Fernández, Alejandro; Rivadeneyra-Posadas, Jéssica; Soto-Célix, María; Raya-González, Javier; Castillo-Alvira, Daniel; Calvo, Sara; Mariscal, Natividad; García-Bustillo, Álvaro; Aguado, Laura; Cubo, Esther	2024	Gait \& Posture	Validation	Charge 4	Adults	Energy Expenditure
Validation of activity trackers to estimate energy expenditure in older adults with cardiovascular risk factors details	Rieckmann, Alina; Jordan, Bas; Burczik, Friederike; Meixner, Jacqueline; Thiel, Christian	2024	PloS One	Validation	Charge 3	Older Adults	Heart Rate
Validity and stability of the international physical activity questionnaire short-form for stroke survivors with preserved walking ability details	de Diego-Alonso, Cristina; Blasco-Abadía, Julia; Doménech-García, Víctor; Bellosta-López, Pablo	2024	Topics in Stroke Rehabilitation	Validation	Inspire 2	Adults	Sleep, Steps
Validity of a Consumer-Based Wearable to Measure Clinical Parameters in Patients With Chronic Obstructive Pulmonary Disease and Healthy Controls: Observational Study details	Hermans, Fien; Arents, Eva; Blondeel, Astrid; Janssens, Wim; Cardinaels, Nina; Calders, Patrick; Troosters, Thierry; Derom, Eric; Demeyer, Heleen	2024	JMIR mHealth and uHealth	Validation	Charge 4	Patients	Steps, Heart Rate
Validity of Wrist-Worn Activity Tracker Heart Rate Detection in Fontan Patients During Exercise details	Pierick, Alyson R.; Burke, Kelly J.; Prusi, Megan; Largent, Bethany; Yu, Sunkyung; Lowery, Ray E.; Duimstra, Ashley; Hansen, Jesse E.	2024	Medicine and Science in Sports and Exercise	Validation	Device unspecified	Patients	Heart Rate
Variations in objectively measured sleep parameters in patients with different premature ejaculation syndromes details	Wu, Xu; Zhang, Yuyang; Jiang, Hui; Zhang, Xiansheng	2024	The Journal of Sexual Medicine	Case Study	Charge 2	Patients	Sleep
A culturally tailored personaliseD nutrition intErvention in South ASIan women at risk of Gestational Diabetes Mellitus (DESI-GDM): a randomised controlled trial protocol details	Stennett, Rosain N.; Adamo, Kristi B.; Anand, Sonia S.; Bajaj, Harpreet S.; Bangdiwala, Shrikant I.; Desai, Dipika; Gerstein, Hertzel C.; Kandasamy, Sujane; Khan, Farah; Lear, Scott A.; McDonald, Sarah D.; Pocsai, Tayler; Ritvo, Paul; Rogge, Andrea; Schulze, Karleen M.; Sherifali, Diana; Stearns, Jennifer C.; Wahi, Gita; Williams, Natalie C.; Zulyniak, Michael A.; de Souza, Russell J.	2023	BMJ open	Intervention	Device unspecified	Pregnant Women	Steps
A Digital Coach (E-Supporter 1.0) to Support Physical Activity and a Healthy Diet in People With Type 2 Diabetes: Acceptability and Limited Efficacy Testing details	Hietbrink, Eclaire A. G.; Oude Nijeweme-d'Hollosy, Wendy; Middelweerd, Anouk; Konijnendijk, Annemieke A. J.; Schrijver, Laura K.; Ten Voorde, Anouk S.; Fokkema, Elise M. S.; Laverman, Gozewijn D.; Vollenbroek-Hutten, Miriam M. R.	2023	JMIR formative research	Intervention	Charge 2	Adults	Steps
A feasibility study to evaluate a purposeful walk intervention with a distance goal using a commercially available activity monitor in elderly people post total hip replacement surgery details	Bahadori, Shayan; Williams, Jonathan Mark; Collard, Sarah; Swain, Ian	2023	Journal of Rehabilitation and Assistive Technologies Engineering	Intervention	Charge 4	Patients	Distance, User Friendliness
A Longitudinal Pilot Study of Stress and Sleep in First-Year Osteopathic Medical Students details	Pattanaik, Sambit; Fastring, Danielle; Bateman, Robert C.	2023	Journal of Medical Education and Curricular Development	Case Study	Charge 3	Adults	Sleep
A multi-site trial of an electronic health integrated physical activity promotion intervention in breast and endometrial cancers survivors: MyActivity study protocol details	Cadmus-Bertram, Lisa; Solk, Payton; Agnew, Megan; Starikovsky, Julia; Schmidt, Christian; Morelli, Whitney A.; Hodgson, Vanessa; Freeman, Hannah; Muller, Laura; Mishory, Abby; Naxi, Sondra; Carden, Lillian; Tevaarwerk, Amye J.; Wolter, Melanie; Barber, Emma; Spencer, Ryan; Sesto, Mary E.; Gradishar, William; Gangnon, Ronald; Spring, Bonnie; Nahum-Shani, Inbal; Phillips, Siobhan M.	2023	Contemporary Clinical Trials	Intervention	Charge 3	Adults	User Friendliness
A Series of Remote Melatonin Supplement Interventions for Poor Sleep: Protocol for a Feasibility Pilot Study for a Series of Personalized (N-of-1) Trials details URL ↗	Butler, Mark; D’Angelo, Stefani; Perrin, Alexandra; Rodillas, Jordyn; Miller, Danielle; Arader, Lindsay; Chandereng, Thevaa; Cheung, Ying Kuen; Shechter, Ari; Davidson, Karina W.	2023	JMIR Research Protocols	Intervention	Charge 5	Adults	Sleep, User Friendliness
A useful tool or a new challenge? Hand-wrist-worn sleep trackers in patients with insomnia details	Ojalvo, Dávid; Pacheco, André Pekkola; Benedict, Christian	2023	Journal of Sleep Research	Usability	Inspire 2	Patients	Sleep
A wearable device perspective on the standard definitions of disability progression in multiple sclerosis details	Dalla Costa, Gloria; Nos, Carlos; Zabalza, Ana; Buron, Mathias; Magyari, Melinda; Sellebjerg, Finn; Guerrero, Ana Isabel; Roselli, Lucia; La Porta, Maria Libera; Martinis, Matteo; Bailon, Raquel; Kontaxis, Spyridon; Laporta, Estela; Garcia, Esther; Pokorny, Florian B.; Schuller, Björn W.; Folarin, Amos; Stewart, Callum; Leocani, Letizia; Vairavan, Srinivasan; Cummins, Nicholas; Dobson, Richard; Hotopf, Matthew; Narayan, Vaibhav; Montalban, Xavier; Sorensen, Per Soelberg; Comi, Giancarlo	2023	Multiple Sclerosis (Houndmills, Basingstoke, England)	Case Study	Charge 3	Adults, Patients	Steps
Accuracy in detecting atrial fibrillation in single-lead ECGs: an online survey comparing the influence of clinical expertise and smart devices details	Weidlich, Simon; Mannhart, Diego; Serban, Teodor; Krisai, Philipp; Knecht, Sven; Du Fay de Lavallaz, Jeanne; Müller, Tatjana; Schaer, Beat; Osswald, Stefan; Kühne, Michael; Sticherling, Christian; Badertscher, Patrick	2023	Swiss Medical Weekly	Case Study	Sense	Adults	Heart Rate
Accuracy of 11 Wearable, Nearable, and Airable Consumer Sleep Trackers: Prospective Multicenter Validation Study details	Lee, Taeyoung; Cho, Younghoon; Cha, Kwang Su; Jung, Jinhwan; Cho, Jungim; Kim, Hyunggug; Kim, Daewoo; Hong, Joonki; Lee, Dongheon; Keum, Moonsik; Kushida, Clete A.; Yoon, In-Young; Kim, Jeong-Whun	2023	JMIR mHealth and uHealth	Validation, Systematic Review	Sense 2	Adults	Sleep
Accuracy of a Standalone Atrial Fibrillation Detection Algorithm Added to a Popular Wristband and Smartwatch: Prospective Diagnostic Accuracy Study details	Selder, Jasper L.; Te Kolste, Henryk Jan; Twisk, Jos; Schijven, Marlies; Gielen, Willem; Allaart, Cornelis P.	2023	Journal of Medical Internet Research	Validation	Ionic	Patients
Addressing the Chronic Pain-Early Cognitive Decline Comorbidity Among Older Adults: Protocol for the Active Brains Remote Efficacy Trial details	Vranceanu, Ana-Maria; Choukas, Nathaniel R.; Rochon, Elizabeth A.; Duarte, Brooke; Pietrzykowski, Malvina O.; McDermott, Katherine; Hooker, Julia E.; Kulich, Ronald; Quiroz, Yakeel T.; Parker, Robert A.; Macklin, Eric A.; Ritchie, Christine; Active Brains Project; Mace, Ryan A.	2023	JMIR research protocols	Intervention	Inspire	Older Adults	Steps, User Friendliness
Advancing Understanding of Just-in-Time States for Supporting Physical Activity (Project JustWalk JITAI): Protocol for a System ID Study of Just-in-Time Adaptive Interventions details	Park, Junghwan; Kim, Meelim; El Mistiri, Mohamed; Kha, Rachael; Banerjee, Sarasij; Gotzian, Lisa; Chevance, Guillaume; Rivera, Daniel E.; Klasnja, Predrag; Hekler, Eric	2023	JMIR research protocols	Intervention	Versa 3	Adults	Steps, Intensity
Ambulation for Latency during Expectant Management of PPROM: A Randomized Controlled Trial (AMBLE) details	Pineles, Beth L.; Vial, Mallory; Castro, Ms Tania; Ghorayeb, Tala; Ajishegiri, Ms Oluwadare; Sadek, Sandra; Pedroza, Claudia; Blackwell, Sean C.; Chauhan, Suneet P.; Sibai, Baha M.	2023	American journal of obstetrics \& gynecology MFM	Case Study	Inspire	Adults	Steps
An online mental health informed physical activity intervention for emergency service workers and their families: A stepped-wedge trial details	McKeon, Grace; Wells, Ruth; Steel, Zachary; Hadzi-Pavlovic, Dusan; Teasdale, Scott; Vancampfort, Davy; Rosenbaum, Simon	2023	Digital Health	Intervention	Inspire	Adults	Steps
An overview of the together everyone achieves more physical activity (TEAM-PA) trial to increase physical activity among African American women details	Sweeney, Allison M.; Wilson, Dawn K.; Zarrett, Nicole; Martin, Pamela; Hardin, James W.; Fairchild, Amanda; Mitchell, Sheryl; Decker, Lindsay	2023	Contemporary Clinical Trials	Intervention	Device unspecified	Adults	Steps, User Friendliness
Applying machine learning to consumer wearable data for the early detection of complications after pediatric appendectomy details	Ghomrawi, Hassan M. K.; O'Brien, Megan K.; Carter, Michela; Macaluso, Rebecca; Khazanchi, Rushmin; Fanton, Michael; DeBoer, Christopher; Linton, Samuel C.; Zeineddin, Suhail; Pitt, J. Benjamin; Bouchard, Megan; Figueroa, Angie; Kwon, Soyang; Holl, Jane L.; Jayaraman, Arun; Abdullah, Fizan	2023	NPJ digital medicine	Usability	Inspire 2, Inspire HR	Patients, Children	Sleep, Steps, Heart Rate
Are Activity Wrist-Worn Devices Accurate for Determining Heart Rate during Intense Exercise? details	Martín-Escudero, Pilar; Cabanas, Ana María; Dotor-Castilla, María Luisa; Galindo-Canales, Mercedes; Miguel-Tobal, Francisco; Fernández-Pérez, Cristina; Fuentes-Ferrer, Manuel; Giannetti, Romano	2023	Bioengineering (Basel, Switzerland)	Validation, Usability	Charge	Adults	Heart Rate
Assessing the Suitability of a Virtual 'Pink Warrior' for Older Breast Cancer Survivors during COVID-19: A Pilot Study details	Swartz, Maria C.; Robertson, Michael C.; Christopherson, Ursela; Wells, Stephanie J.; Lewis, Zakkoyya H.; Bai, Jinbing; Swartz, Michael D.; Silva, H. Colleen; Martinez, Eloisa; Lyons, Elizabeth J.	2023	Life (Basel, Switzerland)	Intervention	Alta HR	Patients	Steps, User Friendliness
Assessment of 24-hour physical behaviour in adults via wearables: a systematic review of validation studies under laboratory conditions details	Giurgiu, Marco; Ketelhut, Sascha; Kubica, Claudia; Nissen, Rebecca; Doster, Ann-Kathrin; Thron, Maximiliane; Timm, Irina; Giurgiu, Valeria; Nigg, Claudio R.; Woll, Alexander; Ebner-Priemer, Ulrich W.; Bussmann, Johannes B. J.	2023	The International Journal of Behavioral Nutrition and Physical Activity	Systematic Review	Classic, One, Flex, Charge 2		Sleep, Steps, Energy Expenditure, Intensity
Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index details	Kashiwagi, Kazuhiro; Inaishi, Jun; Kinoshita, Shotaro; Wada, Yasuyo; Hanashiro, Sayaka; Shiga, Kiko; Kitazawa, Momoko; Tsutsumi, Shiori; Yamakawa, Hiroyuki; Irie, Junichiro; Kishimoto, Taishiro	2023	PloS One	Case Study	Inspire 2	Adults	Steps
Association between sleep quality and nocturnal erection monitor by RigiScan in erectile dysfunction patients: a prospective study using fitbit charge 2 details	Zhang, Yuyang; Zhang, Wei; Feng, Xingliang; Liu, Guodong; Wu, Xu; Jiang, Hui; Zhang, Xiansheng	2023	Basic and Clinical Andrology	Case Study	Charge 2	Patients	Sleep
Association between the use of weight management strategies and weight change among Australian adults over 12 months: an observational study details	Singh, Ben; Olds, Timothy; Curtis, Rachel; Ferguson, Ty; Matricciani, Lisa; Brown, Wendy J.; Dumuid, Dorothea; Esterman, Adrian; Maher, Carol	2023	BMC public health	Case Study	Charge 3, Aria 2	Adults	Weight
Association of self-directed walking with toxicity moderation during chemotherapy for the treatment of early breast cancer details	Nyrop, K. A.; Page, A.; Deal, A. M.; Wagoner, C.; Kelly, E. A.; Kimmick, Gretchen G.; Copeland, Anureet; Speca, JoEllen; Wood, William A.; Muss, H. B.	2023	Supportive Care in Cancer: Official Journal of the Multinational Association of Supportive Care in Cancer	Intervention	Device unspecified	Adults, Patients	Steps
Associations between adverse childhood experiences and early adolescent physical activity in the United States details	Al-Shoaibi, Abubakr A. A.; Iyra, Puja; Raney, Julia H.; Ganson, Kyle T.; Dooley, Erin E.; Testa, Alexander; Jackson, Dylan B.; Gabriel, Kelley Pettee; Baker, Fiona C.; Nagata, Jason M.	2023	Academic Pediatrics	Case Study	Charge HR	Adolescents	Steps
Baseline Nutritional Status and In-Hospital Step Count are Associated with Muscle Quantity, Quality, and Function: Results of an Exploratory Study details	Welch, Carly; Greig, Carolyn; Lewis, Danielle; Majid, Zeinab; Masud, Tahir; Moorey, Hannah; Pinkney, Thomas; Stanley, Benjamin; Jackson, Thomas	2023	Journal of Nutrition in Gerontology and Geriatrics	Methods, Case Study	Inspire	Older Adults	Steps
Blood glucose variance measured by continuous glucose monitors across the menstrual cycle details	Lin, Georgianna; Siddiqui, Rumsha; Lin, Zixiong; Blodgett, Joanna M.; Patel, Shwetak N.; Truong, Khai N.; Mariakakis, Alex	2023	NPJ digital medicine	Case Study	Sense	Adults	Steps
Can we let our patients sleep in the hospital? A randomized controlled trial of a pragmatic sleep protocol in surgical oncology patients details	Kelly, Kathrine; Kolbeinsson, Hordur; Blanck, Lauren M.; Khan, Mariam; Kyriakakis, Roxanne; Assifi, M. Mura; Wright, G. Paul; Chung, Mathew	2023	Journal of Surgical Oncology	Clinical Care	Charge 4	Patients	Sleep, Steps
Challenges of using a Fitbit smart wearable among people with dementia details	O'Sullivan, Grace; Whelan, Barbara; Gallagher, Niamh; Doyle, Priscilla; Smyth, Siobhán; Murphy, Kathleen; Dröes, Rose-Marie; Devane, Declan; Casey, Dympna	2023	International Journal of Geriatric Psychiatry	Usability	Charge 3	Patients	Steps
Chronotype-Dependent Sleep Loss Is Associated with a Lower Amplitude in Circadian Rhythm and a Higher Fragmentation of REM Sleep in Young Healthy Adults details	von Gall, Charlotte; Holub, Leon; Pfeffer, Martina; Eickhoff, Simon	2023	Brain Sciences	Case Study	Inspire	Adults	Sleep
Clinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus details	Lee, Da Young; Kim, Namho; Jung, Inha; Park, So Young; Yu, Ji Hee; Seo, Ji A.; Kim, Jihee; Kim, Kyeong Jin; Kim, Nam Hoon; Yoo, Hye Jin; Kim, Sin Gon; Choi, Kyung Mook; Baik, Sei Hyun; Park, Sung-Min; Kim, Nan Hee	2023	Diabetes \& Metabolism Journal	Case Study	Inspire 2	Patients	Sleep, Steps, Energy Expenditure, Heart Rate
Clinical validation of an artificial intelligence algorithm offering cross-platform detection of atrial fibrillation using smart device electrocardiograms details	Mannhart, Diego; Lefebvre, Baptiste; Gardella, Christophe; Henry, Christine; Serban, Teodor; Knecht, Sven; Kühne, Michael; Sticherling, Christian; Badertscher, Patrick	2023	Archives of Cardiovascular Diseases	Validation	Sense	Patients	Heart Rate
Comparing sleep measures in cancer survivors: Self-reported sleep diary versus objective wearable sleep tracker details	Li, Xiaotong; Mao, Jun J.; Garland, Sheila N.; Root, James; Li, Susan Q.; Ahles, Tim; Liou, Kevin T.	2023	Research Square	Case Study	Charge 4	Adults	Steps
Comparison of Polysomnography, Single-Channel Electroencephalogram, Fitbit, and Sleep Logs in Patients With Psychiatric Disorders: Cross-Sectional Study details	Kawai, Keita; Iwamoto, Kunihiro; Miyata, Seiko; Okada, Ippei; Fujishiro, Hiroshige; Noda, Akiko; Nakagome, Kazuyuki; Ozaki, Norio; Ikeda, Masashi	2023	Journal of Medical Internet Research	Validation	Sense	Adults	Sleep
Considering depression as a secondary outcome in the optimization of physical activity interventions for breast cancer survivors in the PACES trial: a factorial randomized controlled trial details	Rethorst, Chad D.; Carmody, Thomas J.; Argenbright, Keith E.; Mayes, Taryn L.; Hamann, Heidi A.; Trivedi, Madhukar H.	2023	The International Journal of Behavioral Nutrition and Physical Activity	Intervention	Alta HR	Patients	Goals, User Friendliness
Consumer Wearables Define a Normative Recovery Trajectory Following the Modified Nuss Procedure details URL ↗	Carter, M.; Linton, S.; Zeineddin, S.; Jb, Pitt; Figueroa, A.; Perez, A.; Park, E.; DeTella, M.; Kwon, S.; Sd, Goldstein; Ghomrawi, H.; Abdullah, F.	2023	The Journal of surgical research	Measurement	Inspire 2, Inspire HR	Patients, Children	Steps, Heart Rate
Data-driven physical actigraphy patterns relate to cognitive and vascular health in older adults details	Paolillo, Emily W.; Lee, Shannon Y.; VandeBunte, Anna; Saloner, Rowan; Gaynor, Leslie S.; Djukic, Nina; Tsuei, Torie; Cobigo, Yann; Kramer, Joel H.; Casaletto, Kaitlin B.	2023	Experimental Gerontology	Case Study	Flex 2	Older Adults	Steps, Intensity
Data-efficient machine learning methods in the ME-TIME study: Rationale and design of a longitudinal study to detect atrial fibrillation and heart failure from wearables details	Naseri, Arman; Tax, David; van der Harst, Pim; Reinders, Marcel; van der Bilt, Ivo	2023	Cardiovascular Digital Health Journal	Intervention	Inspire 2, Charge 5	Adults	Heart Rate
Daytime Sleep-Tracking Performance of Four Commercial Wearable Devices During Unrestricted Home Sleep details URL ↗	Chinoy, Evan D.; Cuellar, Joseph A.; Jameson, Jason T.; Markwald, Rachel R.	2023	Nature and Science of Sleep	Usability	Inspire HR	Adults	Sleep
Design and rationale of a pilot randomized clinical trial investigating the use of a mHealth app for sarcoidosis-associated fatigue details	Chandler, Jessica; Christon, Lillian M.; Benfield, Katie; Pairet, Samantha; Hoffman, Maria; Treiber, Frank; Mueller, Martina; James, W. Ennis	2023	Contemporary Clinical Trials Communications	Methods	Device unspecified	Patients	Heart Rate
Design of intelligent monitoring of loneliness in the elderly using a serverless architecture with real-time communication API details	Osa-Sanchez, Ainhoa; Jossa-Bastidas, Oscar; Mendez-Zorrilla, Amaia; Oleagordia-Ruiz, Ibon; Garcia-Zapirain, Begonya	2023	Technology and Health Care: Official Journal of the European Society for Engineering and Medicine	Intervention, Methods	Charge 5	Adults	Sleep, Steps, Energy Expenditure, Distance, Heart Rate
Development of a Mobile Health Snacktivity App to Promote Physical Activity in Inactive Adults (SnackApp): Intervention Mapping and User Testing Study details	Sanders, James P.; Gokal, Kajal; Thomas, Jonah J. C.; Rawstorn, Jonathan C.; Sherar, Lauren B.; Maddison, Ralph; Greaves, Colin J.; Esliger, Dale; Daley, Amanda J.; Snacktivity Investigators	2023	JMIR formative research	Measurement, Intervention	Versa Lite	Adults	User Friendliness
Ecological Momentary Assessments and Passive Sensing in the Prediction of Short-Term Suicidal Ideation in Young Adults details	Czyz, Ewa K.; King, Cheryl A.; Al-Dajani, Nadia; Zimmermann, Lauren; Hong, Victor; Nahum-Shani, Inbal	2023	JAMA network open	Case Study	Charge 3	Adults, Patients	Steps, Intensity, Heart Rate
Effect of an Automated Advice Algorithm (CloudConnect) on Adolescent-Parent Diabetes-Specific Communication and Glycemic Management: A Randomized Trial details	DeBoer, Mark D.; Valdez, Rupa; Corbett, John P.; Krauthause, Katie; Wakeman, Christian A.; Luke, Alexander S.; Oliveri, Mary C.; Cherñavvsky, Daniel R.; Patek, Stephen D.	2023	Diabetes Therapy: Research, Treatment and Education of Diabetes and Related Disorders	Case Study	Charge 3	Adults, Adolescents
Effect of digital monitoring and counselling on self-management ability in patients with rheumatoid arthritis: a randomised controlled trial details	Li, Linda C.; Xie, Hui; Feehan, Lynne M.; Shaw, Chris; Lu, Na; Ramachandran, Smruthi; Wang, Ellen; Therrien, Stephanie; Mucha, Julia; Hoens, Alison M.; English, Kelly; Davidson, Eileen; Liu-Ambrose, Teresa; Backman, Catherine L.; Esdaile, John M.; Miller, Kimberly J.; Lacaille, Diane	2023	Rheumatology (Oxford, England)	Intervention	Inspire	Adults	Sleep, Intensity
Effect of exercise intervention using mobile healthcare on blood lipid level and health-related physical fitness in obese women: a randomized controlled trial details	Choi, Jae-Ho; Park, Hun-Young; Sun, Yerin; Seo, Jisoo; Lee, Eunjoo; Kim, Sung-Woo; Kim, Jisu; Lim, Kiwon	2023	Physical Activity and Nutrition	Intervention	Charge 4	Adults
Effects of a Mobile-Health Exercise Intervention on Body Composition, Vascular Function, and Autonomic Nervous System Function in Obese Women: A Randomized Controlled Trial details	Choi, Jae-Ho; Kim, Sung-Woo; Seo, Jisoo; Sun, Yerin; Jung, Won-Sang; Park, Hun-Young; Kim, Jisu; Lim, Kiwon	2023	Journal of Multidisciplinary Healthcare	Measurement, Intervention	Charge 4	Adults	Steps, Energy Expenditure, Heart Rate
Effects of Sleep on Adolescents' Appetite, Dietary Intake, and Weight details	Juelich, Janell; Owens, Rhoda; Denny, Dawn; Raatz, Susan; Lindseth, Glenda	2023	SAGE open nursing	Case Study	Charge 3	Adolescents	Sleep
Effects of sleep-corrected social jetlag on measures of mental health, cognitive ability, and brain functional connectivity in early adolescence details	Yang, Fan Nils; Picchioni, Dante; Duyn, Jeff H.	2023	Sleep	Case Study	Charge HR	Adolescents	Sleep
Efficacy of a Commercial Physical Activity Monitor in Longitudinal Tracking of Patients With Pulmonary Hypertension: A Pilot Study details	Rosenzweig, Eliana; Villeda, Gerson Antonio Valencia; Crook, Sarah; Koli, Fatima; Rosenzweig, Erika B.; Krishnan, Usha S.	2023	Texas Heart Institute Journal	Validation	Charge HR	Adults, Patients	Steps
Efficacy of the Aim2Be Intervention in Changing Lifestyle Behaviors Among Adolescents With Overweight and Obesity: Randomized Controlled Trial details	Tugault-Lafleur, Claire N.; De-Jongh González, Olivia; Macdonald, Janice; Bradbury, Jennifer; Warshawski, Tom; Ball, Geoff D. C.; Morrison, Katherine; Ho, Josephine; Hamilton, Jill; Buchholz, Annick; Mâsse, Louise	2023	Journal of Medical Internet Research	Intervention	Flex 2	Adults, Adolescents	Steps
Evaluation of the effectiveness of sleep hygiene education and FITBIT devices on quality of sleep and psychological worry: a pilot quasi-experimental study among first-year college students details	Bani Issa, Wegdan; Hijazi, Heba; Radwan, Hadia; Saqan, Roba; Al-Sharman, Alham; Samsudin, A. B. Rani; Fakhry, Randa; Al-Yateem, Nabeel; Rossiter, Rachel C.; Ibrahim, Ali; Moustafa, Ibrahim; Naja, Farah; Alameddine, Mohamad; Abbas, Nada; Abdelrahim, Dana N.; Al-Shujairi, Arwa; Awad, Manal	2023	Frontiers in Public Health	Case Study	Flex	Adults	Sleep
Examining changes in vascular function, arterial stiffness and systemic inflammation during hospitalization and recovery from an acute exacerbation of chronic obstructive pulmonary disease details	Fuhr, Desi P.; Brotto, Andrew R.; Rowe, Brian H.; Bhutani, Mohit; Rosychuk, Rhonda J.; Stickland, Michael K.	2023	Scientific Reports	Case Study	Device unspecified	Patients	Steps
Exploratory Validation of Sleep-Tracking Devices in Patients with Psychiatric Disorders details	Ogasawara, Masaya; Takeshima, Masahiro; Kosaka, Shumpei; Imanishi, Aya; Itoh, Yu; Fujiwara, Dai; Yoshizawa, Kazuhisa; Ozaki, Norio; Nakagome, Kazuyuki; Mishima, Kazuo	2023	Nature and Science of Sleep	Usability	Sense	Patients	Sleep
Exploring mechanisms of improvement in the Active Brains intervention for older adults with chronic pain and early cognitive decline details	Choukas, Nathaniel R.; Mace, Ryan A.; Rochon, Elizabeth A.; Brewer, Julie R.; Vranceanu, Ana-Maria	2023	Archives of Gerontology and Geriatrics	Intervention	Alta HR	Older Adults	Steps
Exploring Variations in Sleep Perception: Comparative Study of Chatbot Sleep Logs and Fitbit Sleep Data details	Jang, Hyunchul; Lee, Siwoo; Son, Yunhee; Seo, Sumin; Baek, Younghwa; Mun, Sujeong; Kim, Hoseok; Kim, Icktae; Kim, Junho	2023	JMIR mHealth and uHealth	Case Study	Inspire 2	Adults	Sleep
Feasibility and Preliminary Effectiveness of the INSPIRE Pilot Study for Adolescent Girls details	Voskuil, Vicki R.; Emmanuel, Johanna; Magnuson, Claire; Guidone, Marisa	2023	Journal of Pediatric Health Care: Official Publication of National Association of Pediatric Nurse Associates \& Practitioners	Intervention	Inspire	Adolescents	Heart Rate
Feasibility and preliminary efficacy of a novel web-based physical activity intervention in adults with overweight/obesity: A pilot randomized controlled trial details	Kariuki, Jacob K.; Sereika, Susan; Erickson, Kirk; Burke, Lora E.; Kriska, Andrea; Cheng, Jessica; Milton, Heather; Hirshfield, Sabina; Ogutu, David; Gibbs, Bethany	2023	Contemporary Clinical Trials	Intervention	Charge 2	Adults	Steps
Feasibility and scalability of a fitness tracker study: Results from a longitudinal analysis of persons with multiple sclerosis details	Sieber, Chloé; Haag, Christina; Polhemus, Ashley; Sylvester, Ramona; Kool, Jan; Gonzenbach, Roman; von Wyl, Viktor	2023	Frontiers in Digital Health	Case Study	Inspire HR	Adults	Steps, Intensity, Heart Rate
Feasibility and Utility of a Fitbit Tracker Among Ambulatory Children and Youth With Disabilities details	Bremer, Emily; Arbour-Nicitopoulos, Kelly P.; Tsui, Brianna; Ginis, Kathleen A. Martin; Moore, Sarah A.; Best, Krista L.; Voss, Christine	2023	Pediatric Exercise Science	Usability	Charge HR	Children	Steps, User Friendliness
Feasibility of a wrist-worn wearable device for estimating mental health status in patients with mental illness details	Nakagome, Kazuyuki; Makinodan, Manabu; Uratani, Mitsuhiro; Kato, Masaki; Ozaki, Norio; Miyata, Seiko; Iwamoto, Kunihiro; Hashimoto, Naoki; Toyomaki, Atsuhito; Mishima, Kazuo; Ogasawara, Masaya; Takeshima, Masahiro; Minato, Kazumichi; Fukami, Toshikazu; Oba, Mari; Takeda, Kazuyoshi; Oi, Hideki	2023	Frontiers in Psychiatry	Usability	Sense	Patients	Heart Rate
Feasibility Test of Personalized (N-of-1) Trials for Increasing Middle-Aged and Older Adults' Physical Activity details	Friel, Ciarán P.; Goodwin, Ashley M.; Robles, Patrick L.; Butler, Mark J.; Pahlevan-Ibrekic, Challace; Duer-Hefele, Joan; Vicari, Frank; Gordon, Samantha; Chandereng, Thevaa; Cheung, Ying Kuen Ken; Davidson, Karina W.	2023	Research Square	Intervention	Charge 4	Adults, Older Adults	Steps
Fitbit Data to Assess Functional Capacity in Patients Before Elective Surgery: Pilot Prospective Observational Study details	Angelucci, Alessandra; Greco, Massimiliano; Canali, Stefano; Marelli, Giovanni; Avidano, Gaia; Goretti, Giulia; Cecconi, Maurizio; Aliverti, Andrea	2023	Journal of Medical Internet Research	Usability	Inspire 2	Patients	Steps, Heart Rate
Functional brain connectivity predicts sleep duration in youth and adults details	Mummaneni, Anurima; Kardan, Omid; Stier, Andrew J.; Chamberlain, Taylor A.; Chao, Alfred F.; Berman, Marc G.; Rosenberg, Monica D.	2023	Human Brain Mapping	Case Study	Device unspecified	Children	Sleep
GamerFit-ASD beta test: adapting an evidence-based exergaming and telehealth coaching intervention for autistic youth details	Hatfield, Daniel P.; Must, Aviva; Kennedy, Winston; Staiano, Amanda E.; Slavet, James; Sabelli, Rachael A.; Curtin, Carol; Bandini, Linda G.; Nauta, Phillip; Stuetzle, Christopher; Bowling, April B.	2023	Frontiers in Pediatrics	Intervention	Flex 2	Children	Steps, User Friendliness
Gut microbiota composition and functionality are associated with REM sleep duration and continuous glucose levels details	Arnoriaga-Rodríguez, María; Leal, Yenny; Mayneris-Perxachs, Jordi; Pérez-Brocal, Vicente; Moya, Andrés; Ricart, Wifredo; Fernández-Balsells, Mercè; Fernández-Real, José Manuel	2023	The Journal of Clinical Endocrinology and Metabolism	Case Study	Charge 3	Adults	Sleep
Harnessing digital health to optimise the delivery of guideline-based cardiac rehabilitation during COVID-19: an observational study details	Gibson, Irene; McCrudden, Zoe; Dunne, Denise; Harris, Aisling; Hynes, Lisa; Murphy, Ella; Murphy, Andrew William; Byrne, Molly; McEvoy, John William	2023	Open Heart	Intervention	Device unspecified	Patients	Steps, Heart Rate
Harnessing technology and gamification to increase adult physical activity: a cluster randomized controlled trial of the Columbia Moves pilot details	Monroe, Courtney M.; Cai, Bo; Edney, Sarah; Jake-Schoffman, Danielle E.; Brazendale, Keith; Bucko, Agnes; Armstrong, Bridget; Yang, Chih-Hsiang; Turner-McGrievy, Gabrielle	2023	The International Journal of Behavioral Nutrition and Physical Activity	Intervention	Alta HR	Adults	Steps, Intensity
Health Wearables, Gamification, and Healthful Activity details	Hydari, Muhammad Zia; Adjerid, Idris; Striegel, Aaron D.	2023	Management Science	Usability	Charge HR	Adults	Steps, Heart Rate
Health-related impact of illness associated with excessive daytime sleepiness in patients with obstructive sleep apnea details	Grandner, Michael A.; Min, Jae S.; Saad, Ragy; Leary, Eileen B.; Eldemir, Lev; Hyman, Danielle	2023	Postgraduate Medicine	Case Study	Device unspecified	Adults	Sleep, Steps, Intensity, User Friendliness
Healthy hearts healthy minds: A randomized trial of online interventions to improve physical activity details	Sylvia, Louisa G.; Gold, Alexandra K.; Rakhilin, Marina; Amado, Selen; Modrow, Madelaine Faulkner; Albury, Evan A.; George, Nevita; Peters, Amy T.; Selvaggi, Caitlin A.; Horick, Nora; Rabideau, Dustin J.; Dohse, Heidi; Tovey, Roberta E.; Turner, Jon A.; Schopfer, David W.; Pletcher, Mark J.; Katz, Doug; Deckersbach, Thilo; Nierenberg, Andrew A.	2023	Journal of Psychosomatic Research	Intervention	Charge 2	Adults	Steps
Heart rate responses in critical care trainees during airway intubation: a comparison between the simulated and clinical environments details URL ↗	Ji, Jackson; Langley, Bridget; Zordan, Rachel; van Dijk, Julian; Thies, Heidi Helene Graham; Brahmbhatt, Anjalee; Torcasio, Clarissa; Cunningham, Neil	2023	BMC Emergency Medicine	Case Study	Charge 2	Adults	Heart Rate
How Fitbit data are being made available to registered researchers in All of Us Research Program details	Master, Hiral; Kouame, Aymone; Marginean, Kayla; Basford, Melissa; Harris, Paul; Holko, Michelle	2023	Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
How many days are needed? Measurement reliability of wearable device data to assess physical activity details	Hilden, Patrick; Schwartz, Joseph E.; Pascual, Christian; Diaz, Keith M.; Goldsmith, Jeff	2023	PloS One	Intervention	Flex	Adults	Steps, Intensity
How shoulder immobilization after surgery influences daily activity - a prospective pedometer-based study details	Rickert, Carolin; Ahlich, Stefanie; Gosheger, Georg; Kalisch, Tobias; Liem, Dennis; Schneider, Kristian Nikolaus; Klingebiel, Sebastian	2023	International Orthopaedics	Case Study	Charge	Patients	Steps
'I saw it as a marriage-You can't have one without the other': A qualitative study of patient and physiotherapist experiences with a therapeutic combined strength and aerobic physical activity exercise programme for hip osteoarthritis details	Allison, Kim; Hall, Michelle; Dobson, Fiona; Lawford, Belinda J.; Bennell, Kim; Spiers, Libby; Hinman, Rana S.	2023	Musculoskeletal Care	Intervention	Device unspecified	Patients	Steps, Intensity, Heart Rate, User Friendliness
Identifying Unique Subgroups of Individuals With Stroke Using Heart Rate and Steps to Characterize Physical Activity details	Koffman, Lily J.; Crainiceanu, Ciprian M.; Roemmich, Ryan T.; French, Margaret A.	2023	Journal of the American Heart Association	Intervention	Inspire 2	Adults	Steps, Heart Rate
Influence of sleep duration and sex on age-related differences in heart rate variability: Findings from program 4 of the HAIE study details URL ↗	Gonzales, Joaquin U.; Elavsky, Steriani; Cipryan, Lukáš; Jandačková, Vera; Burda, Michal; Jandačka, Daniel	2023	Sleep Medicine	Measurement	Charge 3, Charge 4	Adults	Sleep
Integrating Genome-wide information and Wearable Device Data to Explore the Link of Anxiety and Antidepressants with Heart Rate Variability details	Friligkou, Eleni; Koller, Dora; Pathak, Gita A.; Miller, Edward J.; Lampert, Rachel; Stein, Murray B.; Polimanti, Renato	2023	medRxiv: The Preprint Server for Health Sciences	Measurement, Case Study	Device unspecified	Adults	Heart Rate
Knee Extension Exercise Effects on Physiological and Psychophysical Performance: Normal Weight Versus Obese Office Workers details	Mohammadian, Mostafa; Choobineh, Alireza; Razeghi, Mohsen; Daneshmandi, Hadi; Ghaem, Haleh; Kazemi, Reza; Jahani, Yunes; Hashemi Nejad, Naser	2023	Workplace Health \& Safety	Case Study	Charge HR	Adults	Energy Expenditure, Heart Rate
Latent Profiles of Sleep Patterns in Early Adolescence: Associations With Behavioral Health Risk details	Zhang, Linhao; Sasser, Jeri; Doane, Leah D.; Peltz, Jack; Oshri, Assaf	2023	The Journal of Adolescent Health: Official Publication of the Society for Adolescent Medicine	Case Study	Charge HR	Adolescents	Sleep
Learning in a Virtual Environment to Improve Type 2 Diabetes Outcomes: A Randomized Controlled Trial details	Johnson, Constance; D'Eramo Melkus, Gail; Reagan, Louise; Pan, Wei; Amarasekara, Sathya; Pereira, Katherine; Hassell, Nancy; Nowlin, Sarah; Vorderstrasse, Allison	2023	JMIR formative research	Intervention	Device unspecified	Adults	Steps
Linking Electronic Health Records With Wearable Technology From the All of Us Research Program details	Epstein, Crystal Modde; McCoy, Thomas P.	2023	Journal of obstetric, gynecologic, and neonatal nursing: JOGNN	Usability	Device unspecified	Pregnant Women	Heart Rate
Linking Sleep and Aggression: Examining the Role of Response Inhibition and Emotional Processing details	Bozzay, Melanie L.; Verona, Edelyn	2023	Clinical Psychological Science: A Journal of the Association for Psychological Science	Case Study	Flex	Adults	Sleep
Links Between Objectively-Measured Hourly Smartphone Use and Adolescent Wake Events Across Two Weeks details	Garrett, Shedrick L.; Burnell, Kaitlyn; Armstrong-Carter, Emma L.; Nelson, Benjamin W.; Prinstein, Mitchell J.; Telzer, Eva H.	2023	Journal of Clinical Child and Adolescent Psychology: The Official Journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53	Case Study	Inspire 2	Adolescents	Sleep
Long-term participant retention and engagement patterns in an app and wearable-based multinational remote digital depression study details	Zhang, Yuezhou; Pratap, Abhishek; Folarin, Amos A.; Sun, Shaoxiong; Cummins, Nicholas; Matcham, Faith; Vairavan, Srinivasan; Dineley, Judith; Ranjan, Yatharth; Rashid, Zulqarnain; Conde, Pauline; Stewart, Callum; White, Katie M.; Oetzmann, Carolin; Ivan, Alina; Lamers, Femke; Siddi, Sara; Rambla, Carla Hernández; Simblett, Sara; Nica, Raluca; Mohr, David C.; Myin-Germeys, Inez; Wykes, Til; Haro, Josep Maria; Penninx, Brenda W. J. H.; Annas, Peter; Narayan, Vaibhav A.; Hotopf, Matthew; Dobson, Richard J. B.; RADAR-CNS consortium	2023	NPJ digital medicine	Survey Research	Charge 2, Charge 3	Adults	Sleep, Steps, Heart Rate
Lower daily steps among U.S. adolescents during the COVID-19 pandemic: Objective findings from the Adolescent Brain Cognitive Development Study details	Nagata, Jason M.; Yu, Jiayue; Dooley, Erin E.; Baker, Fiona C.; Alsamman, Sana; Wing, David; Ganson, Kyle T.; Pettee Gabriel, Kelley	2023	Preventive Medicine Reports	Case Study	Charge	Adolescents	Steps
Machine Learning Approaches to Classify Self-Reported Rheumatoid Arthritis Health Scores Using Activity Tracker Data details	Rao, Kaushal; Speier, William; Meng, Yiwen; Wang, Jinhan; Ramesh, Nidhi; Xie, Fenglong; Su, Yujie; Nowell, Benjamin; Curtis, Jeffrey; Arnold, Corey	2023	JMIR formative research	Intervention	Versa 2	Patients	Sleep, Steps, Energy Expenditure, Heart Rate
Matched and moving: exploring daily social support among women partnered for exercise after a breast cancer diagnosis details	Murray, Ross M.; Smith-Turchyn, Jenna; Vani, Madison F.; McDonough, Meghan H.; Fong, Angela J.; Mina, Daniel Santa; Arbour-Nicitopoulos, Kelly P.; Trinh, Linda; Jones, Jennifer M.; Bender, Jackie L.; Culos-Reed, S. Nicole; Tomasone, Jennifer R.; Sabiston, Catherine M.	2023	Supportive Care in Cancer: Official Journal of the Multinational Association of Supportive Care in Cancer	Case Study	Inspire HR	Adults	Steps, Intensity
Measurement of Physical Activity by Actigraphy in Infants and Young Children with Pulmonary Arterial Hypertension details	Avitabile, Catherine M.; Yung, Delphine; Handler, Stephanie; Hopper, Rachel K.; Fineman, Jeff; Freire, Grace; Varghese, Nidhy; Mullen, Mary P.; Krishnan, Usha S.; Austin, Eric; Silveira, Lori; Ivy, D. Dunbar	2023	The Journal of Pediatrics	Usability	Inspire	Children	Steps, Intensity, Heart Rate
Measurement properties of device-based physical activity instruments in ambulatory adults with physical disabilities and/or chronic diseases: a scoping review details	Brandenbarg, Pim; Hoekstra, Femke; Barakou, Ioulia; Seves, Bregje L.; Hettinga, Florentina J.; Hoekstra, Trynke; van der Woude, Lucas H. V.; Dekker, Rienk; Krops, Leonie A.	2023	BMC sports science, medicine \& rehabilitation	Usability, Systematic Review	Classic, Ultra, One, Zip, Flex, Surge, Charge 2, Flex 2, Alta, Charge 3, Garmin Vivofit 4, Garmin Vivofit 3, Garmin Vivosmart 4		Steps, Energy Expenditure, Intensity
Menstruation-related symptoms are associated with physical activity and midpoint of sleep: a pilot study details	Masuda, Hazuki; Okada, Shima	2023	Frontiers in Global Women's Health	Intervention	Inspire 2	Adults	Sleep, Energy Expenditure
mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED): rationale and study protocol for a pragmatic randomised controlled trial details	Vetrovsky, Tomas; Kral, Norbert; Pfeiferova, Marketa; Kuhnova, Jitka; Novak, Jan; Wahlich, Charlotte; Jaklova, Andrea; Jurkova, Katerina; Janek, Michael; Omcirk, Dan; Capek, Vaclav; Maes, Iris; Steffl, Michal; Ussher, Michael; Tufano, James J.; Elavsky, Steriani; Van Dyck, Delfien; Cimler, Richard; Yates, Tom; Harris, Tess; Seifert, Bohumil	2023	BMC public health	Methods	Inspire 2	Patients	Steps
Mighty Men: A Pilot Test of the Feasibility and Acceptability of a Faith-Based, Individually Tailored, Cluster-Randomized Weight Loss Trial for Middle-Aged and Older African American Men details	Griffith, Derek M.; Pennings, Jacquelyn S.; Jaeger, Emily C.	2023	American Journal of Men's Health	Usability, Intervention	Charge 2	Adults	User Friendliness
Mindfulness Combined with Exercise Online (MOVE) Compared with a Self-Management Guide for Adults with Chronic Pain: A Feasibility Randomised Controlled Trial details	Deegan, Orla; Fullen, Brona M.; Casey, Maire-Brid; Segurado, Ricardo; Hearty, Conor; Doody, Catherine	2023	The Clinical Journal of Pain	Intervention	Device unspecified	Adults	User Friendliness
Minimally invasive versus open pancreatoduodenectomy for pancreatic and peri-ampullary neoplasm (DIPLOMA-2): study protocol for an international multicenter patient-blinded randomized controlled trial details	de Graaf, Nine; Emmen, Anouk M. L. H.; Ramera, Marco; Björnsson, Bergthor; Boggi, Ugo; Bruna, Caro L.; Busch, Olivier R.; Daams, Freek; Ferrari, Giovanni; Festen, Sebastiaan; van Hilst, Jony; D'Hondt, Mathieu; Ielpo, Benedetto; Keck, Tobias; Khatkov, Igor E.; Koerkamp, Bas Groot; Lips, Daan J.; Luyer, Misha D. P.; Mieog, J. Sven D.; Morelli, Luca; Molenaar, I. Quintus; van Santvoort, Hjalmar C.; Sprangers, Mirjam A. G.; Ferrari, Clarissa; Berkhof, Johannes; Maisonneuve, Patrick; Abu Hilal, Mohammad; Besselink, Marc G.; European Consortium on Minimally Invasive Pancreatic Surgery (E-MIPS)	2023	Trials	Case Study	Inspire 2	Patients	Steps, Heart Rate
Minute level smartphone derived exposure to greenness and consumer wearable derived physical activity in a cohort of US women details	Wilt, Grete E.; Roscoe, Charlotte J.; Hu, Cindy R.; Mehta, Unnati V.; Coull, Brent A.; Hart, Jaime E.; Gortmaker, Steven; Laden, Francine; James, Peter	2023	Environmental Research	Case Study	Charge HR, Charge 2, Charge 3	Adults	Steps
Moderate and increased physical activity is not detrimental to live birth rates among women with unexplained infertility and obesity details	Vitek, Wendy S.; Sun, Fangbai; Cardozo, Eden; Hoeger, Kathleen M.; Hansen, Karl R.; Santoro, Nanette; Zhang, Heping; Legro, Richard S.	2023	F\&S Reports	Intervention	Device unspecified	Adults	Steps
Moderating role of physical activity on hippocampal iron deposition and memory outcomes in typically aging older adults details	Lee, Shannon Y.; Paolillo, Emily W.; Saloner, Rowan; Cobigo, Yann; Diaz, Valentina E.; Gontrum, Eva Q.; VandeBunte, Anna; Chatterjee, Ankita; Tucker, Miwa; Kramer, Joel H.; Casaletto, Kaitlin B.	2023	Neurobiology of Aging	Case Study	Flex 2	Older Adults	Steps
Mothers' experiences of a lifestyle intervention for weight reduction 12 months after gestational diabetes mellitus: Qualitative findings from the PAIGE2 study details	Kemp, Bridie J.; Creighton, Rachel M.; Cupples, Gina; Kelly, Bronagh; McAuley, Emma; Fleck, Olwen; Wallace, Helen; Graham, Una; McCance, David R.	2023	Midwifery	Intervention	Device unspecified	Pregnant Women	Steps, User Friendliness
Motivational Message Framing Effects on Physical Activity Dynamics in a Digital Messaging Intervention: Secondary Analysis details	Lee, Alexandra M.; Hojjatinia, Sahar; Courtney, Jimikaye B.; Brunke-Reese, Deborah; Hojjatinia, Sarah; Lagoa, Constantino M.; Conroy, David E.	2023	JMIR formative research	Measurement, Intervention	Versa, Versa Lite	Adults	Steps, Heart Rate
Museum-based art activities to stay young at heart? Results of a randomized controlled trial details	Cami, Margot; Planta, Océane; Matskiv, Jacqueline; Plonka, Alexandra; Gros, Auriane; Beauchet, Olivier	2023	Frontiers in Medicine	Intervention	Alta HR	Older Adults	Heart Rate
Natural patterns of social support for physical activity participation in newly matched breast cancer survivor dyads details	Peck, Serena S.; Vani, Madison F.; Smith-Turchyn, Jenna; Sabiston, Catherine M.	2023	BMC women's health	Case Study	Inspire HR	Adults	Steps, Intensity
Non-equivalent, but still valid: Establishing the construct validity of a consumer fitness tracker in persons with multiple sclerosis details	Polhemus, Ashley; Sieber, Chloé; Haag, Christina; Sylvester, Ramona; Kool, Jan; Gonzenbach, Roman; von Wyl, Viktor	2023	PLOS digital health	Validation	Inspire HR	Adults	Steps, Intensity
Nonlinear, Multicomponent Physical Exercise with Heart Rate Variability-Guided Prescription in Women with Breast Cancer during Treatment: Feasibility and Preliminary Results (ATOPE Study) details	González-Santos, Á.; Lopez-Garzon, M.; Gil-Gutiérrez, R.; Salinas-Asensio, M. M.; Postigo-Martin, P.; Cantarero-Villanueva, I.	2023	Physical Therapy	Intervention	Inspire	Patients	Steps
Online Circuit Training Increases Adherence to Physical Activity: A Randomized Controlled Trial of Men with Obesity details	Keshavarz, Mohammad; Sénéchal, Martin; Bouchard, Danielle R.	2023	Medicine and Science in Sports and Exercise	Intervention	Charge 3	Adults	Heart Rate
Open-Source, Step-Counting Algorithm for Smartphone Data Collected in Clinical and Nonclinical Settings: Algorithm Development and Validation Study details	Straczkiewicz, Marcin; Keating, Nancy L.; Thompson, Embree; Matulonis, Ursula A.; Campos, Susana M.; Wright, Alexi A.; Onnela, Jukka-Pekka	2023	JMIR cancer	Validation	Charge 2		Steps
Opportune warning of COVID-19 in a Mexican health care worker cohort: Discrete beta distribution entropy of smartwatch physiological records details	Aguado-García, Alejandro; Arroyo-Valerio, América; Escobedo, Galileo; Bueno-Hernández, Nallely; Olguín-Rodríguez, P. V.; Müller, Markus F.; Carrillo-Ruiz, José Damián; Martínez-Mekler, Gustavo	2023	Biomedical Signal Processing and Control	Measurement	Charge 3	Adults	Sleep, Steps, Heart Rate
Pain self-management plus activity tracking and nurse-led support in adults with chronic low back pain: feasibility and acceptability of the problem-solving pain to enhance living well (PROPEL) intervention details	Xu, Wanli; Zhang, Yiming; Wang, Zequan; Dorsey, Susan G.; Starkweather, Angela; Kim, Kyounghae	2023	BMC nursing	Usability, Intervention	Flex 2	Adults	Intensity, User Friendliness
Patient Engagement and Provider Effectiveness of a Novel Sleep Telehealth Platform and Remote Monitoring Assessment in the US Military: Pilot Study Providing Evidence-Based Sleep Treatment Recommendations details	Wickwire, Emerson M.; Collen, Jacob; Capaldi, Vincent F.; Williams, Scott G.; Assefa, Samson Z.; Adornetti, Julianna P.; Huang, Kathleen; Venezia, Janet M.; Jones, Rachell L.; Johnston, Christine W.; Thomas, Connie; Thomas, Mary Ann; Mounts, Charles; Drake, Christopher L.; Businelle, Michael S.; Grandner, Michael A.; Manber, Rachel; Albrecht, Jennifer S.	2023	JMIR formative research	Medical	Inspire 2	Patients	Sleep
PCovNet+: A CNN-VAE anomaly detection framework with LSTM embeddings for smartwatch-based COVID-19 detection details	Abir, Farhan Fuad; Chowdhury, Muhammad E. H.; Tapotee, Malisha Islam; Mushtak, Adam; Khandakar, Amith; Mahmud, Sakib; Hasan, Md Anwarul	2023	Engineering Applications of Artificial Intelligence	Review	Device unspecified		Sleep, Steps, Heart Rate
Performance evaluation of Fitbit Charge 3 and actigraphy vs. polysomnography: Sensitivity, specificity, and reliability across participants and nights details	Eylon, Gal; Tikotzky, Liat; Dinstein, Ilan	2023	Sleep Health	Validation	Charge 3	Adults	Sleep
Performance of the Fitbit Charge 2 and Galaxy Watch 2 compared with polysomnography in assessing patients with obstructive sleep apnoea details	Byun, Jung-Ick; Noh, Kyung Chul; Shin, Won Chul	2023	Chronobiology International	Usability	Charge 2	Patients	Sleep
Physical Activity and Social Comparison: The Importance of Group Composition in an Employee Fitbit Intervention details	Wentz, Jennifer R.; Wilhelm Stanis, Sonja	2023	Health Promotion Practice	Intervention	Zip, Flex 2	Adults	Steps
Physical and Mental Health in Adolescence: Novel Insights from a transdiagnostic examination of FitBit data in the ABCD Study details	Damme, Katherine; Vargas, Teresa; Walther, Sebastian; Shankman, Stewart; Mittal, Vijay	2023	Research Square	Case Study	Charge HR	Adolescents	Intensity, Heart Rate
Piloting HealthScore: Feasibility and acceptability of a clinically integrated health coaching program for people living with cancer details	Wood, William A.; Bailey, Carly; Castrogivanni, Brianna; Mehedint, Diana; Bryant, Ashley Leak; Lavin, Kyle; Tan, Xianming; Richardson, Jaime; Qian, Yiqing; Tan, Kelly R.; Kent, Erin E.	2023	Cancer Medicine	Intervention	Device unspecified	Patients	Steps, Heart Rate, User Friendliness
Postponing sleep after a stressful day: Patterns of stress, bedtime procrastination, and sleep outcomes in a daily diary approach details	Schmidt, Laura I.; Baetzner, Anke S.; Dreisbusch, Marina I.; Mertens, Alica; Sieverding, Monika	2023	Stress and Health: Journal of the International Society for the Investigation of Stress	Case Study	Charge HR	Adults	Sleep
Potential limitations of activity tracking devices in monitoring effects of treatment for sarcoidosis details	Klein, Rebecca; Judson, Marc; Barkes, Briana; Maier, Lisa; Zeigler, Joyce; Culver, Daniel; Sweiss, Nadera; Chen, Edward; Hamzeh, Nabeel; Grutters, Jan; Valeyre, Dominique; Singh, Noopur; Spitzer, Ginger; Shivas, Tricha; Baughman, Robert	2023	Sarcoidosis, vasculitis, and diffuse lung diseases: official journal of WASOG	Usability	One	Patients	User Friendliness
Predicting Hospital Readmission among Patients with Sepsis using Clinical and Wearable Data details	Amrollahi, Fatemeh; Shashikumar, Supreeth Prajwal; Yhdego, Haben; Nayebnazar, Arshia; Yung, Nathan; Wardi, Gabriel; Nemati, Shamim	2023	medRxiv: The Preprint Server for Health Sciences	Case Study	Device unspecified	Adults, Patients	Energy Expenditure, Intensity, Heart Rate
Prediction of Unplanned Hospital Readmission using Clinical and Longitudinal Wearable Sensor Features details URL ↗	Yhdego, Haben H.; Nayebnazar, Arshia; Amrollahi, Fatemeh; Boussina, Aaron; Shashikumar, Supreeth; Wardi, Gabriel; Nemati, Shamim	2023	medRxiv	Case Study	Device unspecified	Adults, Patients	Steps, Energy Expenditure, Intensity, Heart Rate
Promoting participation in physical activity through Snacktivity: A qualitative mixed methods study details	Krouwel, Matthew; Greenfield, Sheila M.; Chalkley, Anna; Sanders, James P.; Parretti, Helen M.; Gokal, Kajal; Jolly, Kate; Skrybant, Magdalena; Biddle, Stuart J. H.; Greaves, Colin; Maddison, Ralph; Mutrie, Nanette; Ives, Natalie; Esliger, Dale W.; Sherar, Lauren; Edwardson, Charlotte L.; Yates, Tom; Frew, Emma; Tearne, Sarah; Daley, Amanda J.	2023	PloS One	Intervention	Versa 2	Adults	Steps, User Friendliness
Promoting positive physical activity behaviours in children undergoing acute cancer treatment: feasibility of the CanMOVE intervention details	Grimshaw, Sarah L.; Taylor, Nicholas F.; Conyers, Rachel; Shields, Nora	2023	Brazilian Journal of Physical Therapy	Intervention	Inspire	Children, Adolescents	Steps, User Friendliness
Protocol for randomized personalized trial for stress management compared to standard of care details	Goodwin, Ashley M.; Miller, Danielle; D'Angelo, Stefani; Perrin, Alexandra; Wiener, Ruby; Greene, Brittney; Romain, Anne-Marie N.; Arader, Lindsay; Chandereng, Thevaa; Kuen Cheung, Ying; Davidson, Karina W.; Butler, Mark	2023	Frontiers in Psychology	Intervention	Charge 4, Inspire 2, Sense, Versa 3, Charge 5	Adults	Sleep, Steps
Quantifying physical activity needed to mitigate genetic risk for obesity details	Han, Lide; Annis, Jeffrey; Master, Hiral; Hughes, Andrew; Roden, Dan; Harris, Paul; Ruderfer, Douglas; Brittain, Evan	2023	Research Square	Case Study	Device unspecified	Adults	Steps, Heart Rate
Real-time Assessment of the Bidirectional Relationship Between Affective States and Glucose: Protocol for a 14-Day Observational Study details	Rethorst, Chad D.; Githinji, Phrashiah; Seguin-Fowler, Rebecca A.; MacMillan Uribe, Alexandra L.; Szeszulski, Jacob; Liao, Yue	2023	JMIR research protocols	Methods	Inspire 2	Adults	Sleep, Steps
Resident Sleep During Traditional Home Call Compared to Night Float details	Chowdhary, Apoorva; Davis, John A.; Ding, Leona; Taravati, Parisa; Feng, Shu	2023	Journal of Academic Ophthalmology (2017)	Case Study	Alta HR	Adults	Sleep
Selecting a sleep tracker from EEG-based, iteratively improved, low-cost multisensor, and actigraphy-only devices details	Ong, Ju Lynn; Golkashani, Hosein Aghayan; Ghorbani, Shohreh; Wong, Kian F.; Chee, Nicholas I. Y. N.; Willoughby, Adrian R.; Chee, Michael W. L.	2023	Sleep Health	Validation, Systematic Review	Sense	Adults	Sleep
Selection of and Response to Physical Activity-Based Social Comparisons in a Digital Environment: Series of Daily Assessment Studies details	Arigo, Danielle; Gray, Robert C.; Dallal, Diane H.; Villareale, Jennifer; Zhu, Jichen	2023	JMIR human factors	Systematic Review	Device unspecified	Adults	Steps
Sleep Duration on Workdays Is Correlated with Subjective Workload and Subjective Impact of High Workload on Sleep in Young Healthy Adults details	von Gall, Charlotte; Muth, Thomas; Angerer, Peter	2023	Brain Sciences	Case Study	Inspire	Adults	Sleep

Amblyopia and adult health: a comprehensive analysis of long-term systemic, sensory and mental health comorbidities in a national cohort (2026)

The British Journal of Ophthalmology

Authors: Lee, Kyoung A. Viola; Langholm, Carsten; Lin, Trevor; Jin, Kimberly; Aboobakar, Inas F.; Oke, Isdin; Whitman, Mary C.

Abstract

AIMS: To evaluate the adult health consequences of amblyopia, including sensory deficits, mental health, physical activity and cardiovascular health. METHODS: A cross-sectional study using data from the National Institutes of Health's All of Us Research Program, including 1998 adults with amblyopia (1335 non-strabismic, 663 strabismic) identified by International Classification of Diseases (ICD)-9/ICD-10/Systemized Nomenclature of Medicine (SNOMED) codes, including 187 with Fitbit data. Controls (10:1 ratio) were propensity-score-matched on age, sex, self-reported race, income and healthcare visits. Separate matched control groups were used for Fitbit and subgroup analyses. Data from electronic health records, surveys and Fitbit were used to assess sensory impairments, cardiometabolic conditions, physical activity and neuropsychiatric disorders. Prevalence and ORs with 95\% CIs were calculated to assess associations between amblyopia (total, strabismic and non-strabismic) and health outcomes. RESULTS: Amblyopia was associated with increased odds of bilateral blindness (OR=2.96, 95\% CI 2.54 to 3.44), obesity (OR=1.27, 95\% CI 1.16 to 1.39), type 2 diabetes (OR=1.39, 95\% CI 1.26 to 1.53) and cardiovascular disease (OR=1.92, 95\% CI 1.69 to 2.19). Amblyopic individuals took fewer daily steps (5859 vs 6229; p=0.044), indicating decreased physical activity. Neuropsychiatric disorders were more common, including generalised anxiety (OR=1.57, 95\% CI 1.43 to 1.72), substance use disorder (OR=1.40, 95\% CI 1.25 to 1.55), bipolar disorder (OR=1.35, 95\% CI 1.13 to 1.61), attention-deficit/hyperactivity disorder (OR=1.54, 95\% CI 1.28 to 1.86), obsessive compulsive disorder (OR=1.82, 95\% CI 1.31 to 2.54) and autism (OR=3.27, 95\% CI 1.79 to 5.99). Schizophrenia was not associated (OR=1.00, 95\% CI 0.70 to 1.42). CONCLUSIONS: Amblyopia is associated with long-term systemic health conditions, suggesting either long-term effects of visual impairment or shared underlying risk factors. These findings underscore the need for early detection and intervention. Further research is needed to explore the neurodevelopmental pathways linking amblyopia and its comorbidities.

Assessing Wearable mHealth Adherence in Underserved Adolescents and its Associations With Physical Activity, Sports, and Safety Perceptions: Prospective Cohort Study (2026)

JMIR mHealth and uHealth

Authors: Nunez-Gaunaurd, Annabel, and Michele Raya

Abstract

Background: Adolescents from underserved communities, particularly Black and Hispanic youth, engage in lower levels of physical activity (PA), increasing their risk for chronic disease. Conventional interventions often face barriers such as limited access to safe environments. Wearable mobile health technologies offer scalable and context-sensitive solutions; however, predictors of sustained adherence in school-based settings among high-risk populations remain underexplored. Objective: This study aims to examine the behavioral and contextual predictors of adherence to a consumer-grade wearable PA tracker among underserved high school students. Methods: In this school-based observational study, 63 students (mean age 14.8, SD 1.17 years) enrolled in physical education received Fitbit devices. Adherence was defined as ≥21 valid days of step count data. Measures included self-reported PA behaviors, neighborhood perceptions, physical fitness (including anthropometrics), and device adherence. Group comparisons were conducted using t tests and chi-square tests. Logistic regression was used to identify predictors of adherence. Results: Overall, 73% (46/63) of participants met the adherence threshold. Adherent students reported fewer days of moderate-to-vigorous PA (2 vs 4 days/week; P=.004), lower team sports participation (21/46, 46% vs 12/17, 71%; P=.004), and higher perceived neighborhood safety (P=.02). In adjusted models, lower PA frequency, greater perceived safety, and neighborhood walkability significantly predicted adherence (χ² 6=16.23; P=.01, Nagelkerke R²=0.61). Conclusions: Wearable mobile health technologies show promise for engaging underserved adolescents in PA, particularly those with lower baseline activity and limited access to structured sports. Key predictors of adherence included perceived neighborhood walkability, team sports participation, and prior PA behavior. School-based deployment of wearable devices should emphasize personalized goals and autonomy-supportive strategies to foster sustained engagement and promote PA among high-risk youth. Keywords: adolescents; functional measures; health promotion; mHealth; mobile health; obesity; physical activity; school-based; wearable adherence; wearables.

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Behaviour Change for Physical Activity Is Feasible and Effective in Women Living with Metastatic Breast Cancer: A Pilot Two-Arm Randomised Trial (2026)

Cancers (Basel)

Authors: Mark Liu, Sharon Kilbreath, Jasmine Yee, Jane Beith, and Elizabeth Dylke

Abstract

Background/objectives: Physical activity benefits women with metastatic breast cancer. Past trials are typically well-resourced and supervised, but home-based interventions may be preferable and more accessible. This pilot trial evaluated the feasibility and preliminary efficacy of a remotely delivered behaviour change intervention aiming to increase physical activity for women with metastatic breast cancer. Methods: A 12-week, two-arm trial involved 20 women with metastatic breast cancer randomised 1:1 to a generic recommendation group or behaviour change group. Both groups received a physical activity recommendation, Fitbit® watch, diary, and nine phone/video call sessions. The behaviour change group received individualised advice around physical activity benefits, motivation, barriers, and social support; the generic recommendation group completed a recurring symptom questionnaire. Feasibility outcomes were recruitment, retention and adherence rates. Acceptability was evaluated with a structured interview at trial completion. Preliminary efficacy outcomes included 5-day Actigraph wear, 6 min walk distance, 30 s sit-to-stands, and questionnaires for self-reported physical activity, quality-of-life, fatigue, behavioural factors, and patient-specific function. Results: Recruitment, retention, and adherence rates were 63% (n = 20/32), 80% (n = 16/20), and 76% (137/180 sessions), respectively. Participants across both groups reported that participation was acceptable, and their behaviour change was perceived as sustainable. Preliminary change scores for efficacy measures favoured the behaviour change group, except some quality-of-life and behavioural factor subscales. Conclusions: Participants were receptive to the trial, and feasibility and efficacy measures were positive. This indicates that a behaviour change intervention for unsupervised physical activity is acceptable and can be beneficial to women with metastatic breast cancer, warranting further exploration. Keywords: behaviour change; breast cancer; metastatic cancer; physical activity; physical function; quality of life.

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Comparing methods to measure wearable device adherence for physical activity monitoring for persons with autism: A prospective observational cohort study (2026)

Physiotherapy Theory and Practice

Authors: Tovin, Melissa M.; Madden, Sheila B.; Wu, Kaiwen; Nunez-Gaunaurd, Annabel

Abstract

INTRODUCTION: Individuals with autism spectrum disorder (ASD) have higher rates of obesity and exhibit more sedentary behaviors than neurotypical peers. Use of wearable devices (WD) to target insufficient physical activity (PA) in this population has increased over the past decade. However, standardized methods for assessing WD adherence remain limited among this understudied population. PURPOSE: A prospective observational cohort design was used to compare two methods for determining WD adherence for monitoring PA in adolescents and adults with ASD. METHODS: Subjects were enrolled in an 8-week telehealth program aimed at improving PA among adolescents and adults with ASD. The Fitbit Inspire 3 WD was utilized for PA tracking and self-monitoring. Subject step activity and heart rate (HR) data were collected for an 8-week period via FITABASE management platform. Adherence was calculated using two methods. Method-A was defined as ≥10-hr daily wear-time based on HR monitoring; Method-B was defined as ≥ 500 steps/day. Observational data collected via researcher field notes documented participant-reported factors and/or behaviors that influenced WD adherence. RESULTS: Data from twenty-seven subjects (21 males, 6 females) ages 14 to 28 years (mean: 18.85 years) were analyzed. Adherence was significantly higher when calculated using Method B (mean = 40 days, 5.4 weeks) compared to Method A (mean = 24 days, 2.8 weeks; p {\textless} .001). Observational data identified disability-related behaviors that negatively impacted Method A derived adherence. CONCLUSIONS: Using HR-based measures of adherence may underestimate device use in individuals with ASD, potentially setting unrealistic expectations for continuous wear. Step-based metrics provides a more inclusive and pragmatic approach for assessing WD adherence in this population, with implications for future intervention design and evaluation. This study highlights the need to tailor WD adherence definitions to the behavioral and sensory profiles of neurodiverse populations. Further study is warranted.

Effects of a 90-Min Nap on Time-Motion Metrics and Psychophysiological Responses During Small-Sided Games in Professional Soccer Players (2026)

Scandinavian Journal of Medicine \& Science in Sports

Authors: Kerkeni, Mohamed; Boukhris, Omar; Kerkeni, Manel; Ammar, Achraf; Husain, Waqar; Zmijewski, Piotr; Jahrami, Haitham; Chtourou, Hamdi; Trabelsi, Khaled

Abstract

This study investigated the impact of a 90-min nap (N90) on time-motion metrics and psychophysiological responses during small-sided games (SSGs) in soccer players. In a within-subjects counterbalanced design, 15 professional male soccer players (mean ± SD; age: 22.4 ± 1.2 years; stature: 178 ± 9 cm; body mass: 70.1 ± 4.0 kg; estimated VO2max: 55.9 ± 2.8 mL·min-1·kg-1) completed two SSGs sessions under N90 and no-nap (N0) conditions. N90 was monitored using a Fitbit Charge 6 wristband. Daytime sleepiness was assessed pre- and post-nap. Mood states, the wellness status (Hooper index), and cognitive performance (Go/NoGo task) were evaluated before each SSGs session. Time-motion metrics, obtained via the FieldWiz GPS system, along with exercise heart rate (HR), were continuously monitored throughout the SSGs. Blood lactate concentration ([La]) and ratings of perceived exertion (RPE) were assessed post-SSGs. Compared to N0, the N90 condition resulted in a significantly greater total distance covered during SSGs (p = 0.002, Cohen's {\textbar}d{\textbar} = 0.96), lower presession resting HR (p {\textless} 0.001, {\textbar}d{\textbar} = 1.33), and reduced relative exercise HR (p = 0.03, {\textbar}d{\textbar} = 0.33). Additionally, post-SSGs [La] and RPE were lower following N90 (p = 0.015, {\textbar}d{\textbar} = 0.71 and p = 0.001, {\textbar}d{\textbar} = 1.03 respectively). The N90 also led to higher vigor scores (p = 0.003, {\textbar}d{\textbar} = 1.01), lower Hooper index values (p = 0.02, {\textbar}d{\textbar} = 0.59), and faster reaction time (p = 0.02, {\textbar}r{\textbar} = 0.60) than N0. A 90-min nap before SSGs training increased total distance covered, reduced perceived fatigue, and enhanced mood, wellness, and cognitive alertness. These findings support implementing a 90-min nap as a practical ergogenic aid to optimize recovery status, performance, cognitive alertness and overall well-being in professional soccer players.

Efficacy of Telehealth-Based Coaching to Improve Physical Activity and Overall Experience for Cancer Survivors: Secondary, Mixed Methods Analysis of a Randomized Controlled Trial (2026)

JMIR cancer

Authors: Khairat, Saif; Kent, Erin E.; Geracitano, John; Mendis, Kaushalya; Zhou, Zhaoqiang; Bailey, Carly; Wood, William A.

Abstract

BACKGROUND: Cancer survivors face significant challenges in maintaining adequate physical activity levels, which are essential for overall health and quality of life. Telehealth-based interventions offer promising opportunities to provide accessible support and promote healthier lifestyles throughout the cancer survivorship continuum. HealthScore is a telehealth coaching program designed to optimize the health of cancer survivors. OBJECTIVE: This study assessed the effectiveness of HealthScore in improving physical activity metrics among cancer survivors compared to controls. We also evaluated participants' qualitative experiences with the program to understand its impact on motivation, accountability, and overall health-related quality of life. METHODS: We performed a secondary analysis of a randomized controlled study of cancer survivors who participated in a comprehensive health coaching intervention called HealthScore. Participants in control and intervention groups received a Fitbit activity tracker that collected heart rate, step counts, active minutes, and calories burned. These metrics were analyzed using statistical methods to compare overall averages and temporal trends between intervention and control groups. Eleven exit interviews were conducted with intervention arm participants to ascertain their experiences with HealthScore. Inductive thematic analysis was performed to identify emerging themes. Data were collected between May 2020 and March 2022. RESULTS: Of the 32 participants enrolled, 20 (62\%) were in the intervention group. Compared to the control group, intervention participants had significantly higher average daily steps (mean 3660, SD 3344; 95\% CI 3557-3764 vs mean 3408, SD 3288; 95\% CI 3299-3518; P=.001) and more moving average daily steps (mean 4813, SD 1723; 95\% CI 4680-4946 vs mean 4581, SD 1224; 95\% CI 4494-4669; P=.003). Moving average daily step counts in the intervention arm showed an increasing trend, which was significantly higher than that of the control group (regression slope=5.89 vs 2.80; P{\textless}.001). Compared to the control group, the intervention participants had significantly higher average daily walking distance (mean 2.6, SD 2.5; 95\% CI 2.5-2.7 vs mean 2.4, SD 2.3; 95\% CI 2.3-2.5; P{\textless}.001) and more moving average daily walking distance (mean 3.5, SD 1.3; 95\% CI 3.4-3.6 vs mean 3.2, SD 0.8; 95\% CI 3.1-3.3; P{\textless}.001). Moving average daily walking distances among intervention participants increased, which was also significantly higher than that of the control group (regression slope=0.0046 vs 0.0017; P{\textless}.001). Participants in the intervention group reported a growing sense of accountability and motivation. One barrier was completing weekly monitoring of patient-reported outcome surveys, which focused on symptoms and physical function and did not always align with participants' goals. CONCLUSIONS: The HealthScore telehealth coaching program improved physical activity levels among cancer survivors and enhanced motivation and accountability. These findings support the integration of telehealth-based health coaching into posttreatment care, promoting healthier lifestyles and improved quality of life for cancer survivors. TRIAL REGISTRATION: ClinicalTrials.gov NCT04923997; https://clinicaltrials.gov/study/NCT04923997.

Health outcomes after national acute sleep deprivation events among the American public (2026)

JCI insight

Authors: Kelly, Neil J.; Chaudhary, Rahul; El Khoury, Wadih; Kalepalli, Nishita; Wang, Jesse; Patel, Priya; Chan, Irene N.; Rahman, Haris; Saiyed, Aisha; Shah, Anisha N.; McClung, Colleen A.; Okawa, Satoshi; Nouraie, Seyed Mehdi; Chan, Stephen Y.

Abstract

BACKGROUNDSleep is increasingly recognized as essential to human health, yet the adverse health consequences of acute sleep deprivation are unknown. We hypothesized that acute sleep deprivation is associated with health outcomes and modulated by sleep-associated genotypes.METHODSLocally estimated scatterplot smoothing (LOESS) was performed on sleep estimates from Fitbit users (n = 14,681) between June 1, 2016, and July 1, 2022. Dates when population minutes slept were less than the 90\% confidence interval of the LOESS regression were named acute sleep deprivation events (ASDEs). Phenome-wide disease incidence among the All of Us Research Program population (n = 287,012) in the 10 days after ASDE was compared with a preceding reference period by McNemar's test. Circadian rhythm-associated and sleep duration-associated SNPs were screened to identify genotypes associated with shorter ASDE sleep duration. Influences of sleep and circadian genotype on post-ASDE influenza risk were modeled using binomial family generalized estimating equations.RESULTSWe identified 32 ASDEs spanning major national events. A phenome-wide screen found increased risk of influenza (odds ratio = 1.54 [1.40, 1.70], P = 1.00 × 10-18) following ASDEs. Fifty-six SNPs were associated with decreased sleep duration on ASDEs. Higher quantiles of ASDE-related SNP genotype burden were associated with less ASDE sleep duration and a greater risk of influenza-associated health care visits.CONCLUSIONMajor national events are associated with acute sleep deprivation and greater influenza risk, which is amplified by sleep genotypes. These findings should inform public health vigilance surrounding major national events.FUNDINGWoodNext Foundation; NIH grants T32HL129964, K08ES037420, R01HL124021, R01HL122596, and R01HL151228; American Heart Association grants 24SFRNCCN1276089 and 24SFRNPCN1280228; and the United Therapeutics Jenesis Innovative Research Awards, the Pulmonary Hypertension Association, the McKamish Family Foundation, the Hemophilia Center of Western Pennsylvania, and the Institute for Transfusion Medicine.

Implementation of wearable activity trackers in hospital rehabilitation: a feasibility study tailored to local settings (2026)

BMC health services research

Authors: Szeto, Kimberley; Arnold, John; Singh, Ben; Diestel-Feddersen, Peter; Edwards, Dominique; Cheary, Shannon; Lo Basso, Matthew; Maher, Carol

Abstract

BACKGROUND: Physical inactivity during and after hospitalisation is associated with poorer outcomes. Wearable activity trackers (WATs) are effective in promoting physical activity in healthcare settings, however, their successful implementation remains a challenge, and evidence for how this can be achieved is so far limited. OBJECTIVE: This feasibility study evaluated WAT implementation in inpatient and outpatient rehabilitation by assessing: (1) feasibility metrics including uptake and retention rates; (2) patient and clinician perceptions; (3) challenges and factors contributing to success; and (4) changes in PA. METHODS: A single-arm, feasibility study was conducted in two rehabilitation settings at a major teaching hospital. Patients were provided with a WAT (Fitbit Inspire 3) to wear throughout their admission, which was used to set step goals with clinicians, monitor daily step counts and support efforts and encouragement to meet step goals. Feasibility was assessed based on recruitment, retention, and data completeness rates. Patient and clinician experiences, satisfaction and perceptions were evaluated through surveys. Effect sizes for change in physical activity from baseline to follow-up were assessed for daily step counts, light physical activity, moderate-vigorous physical activity, and sedentary behaviour, were calculated using Cohen’s d and matched-pairs rank-biserial correlation (r). RESULTS: Of 36 invited patients, 26 participated, (mean age 72 years; SD: 13; range 33–93; 72\% uptake rate). Data completeness was high (92\%), with no devices lost or broken. Most patients perceived WATs helped increase walking (68\%) and achieve rehabilitation goals (64\%), with 84\% willing to use WATs again in rehabilitation. All clinicians (n = 6) found WATs easy to use, though perspectives on therapy enhancement varied. Large effect sizes were observed for increased daily steps in both the inpatient (1050 to 1366 steps/day, (r) = 0.595) and outpatient (4749 to 5986 steps/day, (r) = 0.532) rehabilitation settings. The simplicity of the approach and patient and clinician resources were identified as factors contributing to the success of implementation, though the recruitment approach revealed challenges related to inviting individual patients to participate. CONCLUSION: WAT implementation was feasible in both rehabilitation settings. Future research should evaluate larger scale implementation and effectiveness of such approaches through service-level enrolment and larger controlled trials, and exploring applications across diverse clinical settings. TRIAL REGISTRATION: This trial was registered with the Australian New Zealand Clinical Trials Registry (ANZCTR) (Trial ID: ACTRN12624000447550; registration date: 11 April 2024). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-026-14066-4.

Improving sleep health through sleep hygiene education in adults aged 50-80 years (2026)

Frontiers in sleep

Authors: Ashley M Pfeiffer, Craig Triplett, and Olivia Schaefers

Abstract

Introduction: Sleep plays a critical role in maintaining physical and cognitive health in older adults, yet sleep problems are highly prevalent in this population. Conventional management strategies often rely on pharmacological interventions, which may cause adverse side effects, evidencing the need for safe, low-cost alternatives. Sleep hygiene education offers a promising approach, and this study evaluates the efficacy of a strategy combining a one-time educational video and daily automated text messages in improving sleep quality, daytime sleepiness, and overall sleep hygiene practices among older adults. Methods: Participants completed an electronic survey that collected demographic information and included the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), Sleep Hygiene Index (SHI), Perceived Stress Scale, and Numeric Pain Rating Scale. Each participant wore a Fitbit sleep tracker for 2 weeks to establish baseline data on total sleep time, time awake, time in rapid eye movement (REM)/light/deep sleep, and sleep efficiency. Participants were then randomly assigned to a control group, a video-only group, or a video-plus-text group. Sleep tracking continued for 4 additional weeks, and all assessments were repeated at the end of the study. Results: A total of 119 participants (mean age 66.5 ± 7.2 years; 77 females) completed the study. Paired t-tests compared pre- and post-intervention scores. Both the video-only and video-plus-text groups showed significant improvements on the PSQI, ESS, and SHI compared to the control. No significant changes were found in measured objective sleep parameters. Discussion: Findings indicate that video-based sleep hygiene education, with or without supplemental text messaging, was associated with improvements in subjective sleep quality, daytime sleepiness, and sleep hygiene behaviors. However, these improvements were not reflected in objective sleep measures, highlighting a discrepancy commonly reported in sleep research. Conclusion: Brief, low-cost sleep hygiene education interventions, delivered through video or a combination of video and text messaging, may improve perceived sleep quality and sleep-related behaviors in older adults.

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Neighborhood disadvantage and adolescent sleep health: a longitudinal population-based study (2026)

Lancet Regional Health. Americas

Authors: Niu, Li; Tan, Luyao; Diaz, Angela; Xiao, Yunyu; Li, Yan; Wang, Yijie

Abstract

BACKGROUND: Neighborhood disadvantage may adversely affect adolescent sleep health, yet causal evidence is limited and whether these effects differ by sex and pubertal development remain unclear. This study examined the potential causal effect of neighborhood disadvantage on adolescent sleep duration and variability over a two-year period. METHODS: This cohort study analyzed data from 5045 adolescents (mean age 9.96 years at baseline) in the Adolescent Brain Cognitive Development (ABCD) Study, a longitudinal, population-based sample in the United States. Three indicators of neighborhood disadvantage were assessed: Area Deprivation Index (ADI), air pollution, and nighttime noise, each dichotomized at the 80th percentile to indicate high exposure. Sleep outcomes were derived from Fitbit devices worn continuously for 21 days two years after baseline, including sleep duration and night-to-night variability (defined as the standard deviation of sleep duration across nights). Bayesian causal forests were used to estimate average treatment effects (ATEs) and subgroup-specific effects by sex and pubertal status. Analyses adjusted for the propensity to reside in a high-advantage neighborhood, accounting for individual and household factors including income-to-needs ratio, parental education, and race/ethnicity. FINDINGS: Adolescents living in neighborhoods with high ADI (ATE -0.11, 10th percentile: -0.18, 90th percentile: -0.05), high air pollution (ATE -0.08, -0.14 to -0.02), and high nighttime noise (ATE -0.07, -0.13 to -0.01) had shorter sleep duration two years after baseline. High ADI was also associated with greater night-to-night sleep variability (ATE 0.17, 0.10-0.23). Stratified analyses revealed that boys were more susceptible to reduced sleep duration, girls to greater sleep variability, and adolescents with more advanced pubertal status were more affected across both outcomes. INTERPRETATION: Neighborhood disadvantage has lasting adverse effects on adolescent sleep health, with differential vulnerability by sex and pubertal stage. These findings underscore the need for developmentally tailored policies and interventions that address neighborhood environments to promote healthy sleep during adolescence. FUNDING: This study was supported by the National Natural Science Foundation of China, the Fundamental Research Funds for the Central Universities, the National Institute of Mental Health, and the American Foundation for Suicide Prevention.

Older breast cancer survivors' exercise and support group program experiences and recommendations from the IMPROVE trial: a qualitative study (2026)

BMC cancer

Authors: Hundal, Jasmin; Williams, Dionne; Nock, Nora L.; Austin, Kristina; Bennet, Elizabeth; Cerne, Stephen; Moore, Halle C. F.; Petkac, Jean; Schmitz, Kathryn H.; Berger, Nathan A.; Owusu, Cynthia

Abstract

BACKGROUND: Physical activity is critical for older breast cancer survivors. We explored the experiences and recommendations of older breast cancer survivors from the IMPROVE trial, including a sizable number of older African American and socioeconomically disadvantaged survivors, to inform future implementation and dissemination of sustainable programs. METHODS: Participants included women, ≥ 65 years, within five years of treatment completion for stage I-III breast cancer who were enrolled into a randomized controlled trial of supervised group moderate-intensity exercise for 20-weeks followed by 32 weeks of unsupervised exercise versus support group (SG) plus Fitbit intervention. Semi-structured exit interviews were conducted at study completion. Interviews were audio-recorded, transcribed verbatim, and analyzed using thematic analysis with constant comparison. Two researchers independently coded transcripts, discussing discrepancies to enrich interpretation. The Social Cognitive Theory and the Transtheoretical Model guided interpretation of results. RESULTS: Between 2016 and 2020, 213 older breast cancer survivors were randomized into the exercise arm, (n = 108) or a SG + Fitbit arm, (n = 105). At study completion, 145 (68\%) opted to participate in exit interviews. This included 75 Exercise and 70 Support Group participants. Participants described a range of experiences and recommendations that clustered into five broad themes: program experiences, transition challenges, Fitbit experiences, program impact, and recommendations. Survivors consistently highlighted camaraderie, peer bonding, and accountability as central benefits of participation, with enjoyment of activities and staff support further enriching their experience. Many described difficulties sustaining activity after program completion, underscoring the need for ongoing group-based support. Experiences with Fitbit were mixed: some found it motivating, while others reported technical barriers. Survivors also noted increased energy, health awareness, and reduced isolation. Recommendations included extending program duration, adding nutrition content, reducing survey burden, and addressing transportation challenges. CONCLUSION: Older breast cancer survivors, including those underrepresented in survivorship research, emphasized the importance of social support, structured exercise, and wearable technology in sustaining physical activity. Their recommendations highlight strategies for tailoring future interventions to enhance accessibility, sustainability, and long-term impact. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02763228.

Short-Term Effects of a Mobile Health Intervention on Healthy Behaviors and Cardiometabolic Health in Sedentary Employees: A Quasi-Experimental Study (2026)

MIR mHealth and uHealth

Authors: Lin, Y., Lu, S., Lee, K., Ma, W., Ho, Y, Liao, W., Yang, H., and Hong, O.

Abstract

Background: Sedentary employees face increased chronic health risks due to physical inactivity, immobility, and unhealthy eating behavior. Although mobile health (mHealth) interventions have shown promise in improving lifestyle behaviors, their effectiveness in occupational settings remains underexplored. Building on our previous workplace interventions, this study developed and evaluated a mobile-enabled web app-SIMPLE HEALTH-integrating activity tracking, healthy eating, and behavioral support for sedentary employees. Objective: This study evaluated the short-term effects of a 12-week mHealth intervention on physical activity, sedentary behavior, dietary habits, and cardiometabolic health indicators among sedentary employees in Taiwan. Methods: A 2-arm quasi-experimental study was conducted at two aerospace industrial workplaces. A total of 101 sedentary employees (mean age 46.9, SD 12.2 years; 51.5% female) were allocated by coin toss to either the intervention group (n=50) or control group (n=51). The intervention group participated in the SIMPLE HEALTH program, an mHealth intervention grounded in Social Cognitive Theory and the Ecological Model, consisting of eight components: activity tracking, goal setting, behavior logging, reminders, personalized advice, educational and motivational e-booklets, and individual and team challenges. The control group received six print educational booklets. Cardiometabolic biomarkers, objectively measured physical activity (Fitbit Charge 3), occupational sitting (occupational sitting and physical activity questionnaire), and dietary behavior (3-day photographic food records and the healthy eating behavior inventory) were assessed at baseline and 12 weeks. Data were analyzed using generalized estimating equations following the intention-to-treat principle. Results: At 12 weeks, the intervention group showed significant improvements in step counts (B 1227.13, 95% CI 2.90 to 2451.36; P=.049), moderate physical activity (B 0.17, 95% CI 0.01 to 0.33; P=.04), and dietary behaviors-reduced intake of calories (B -144.59, 95% CI -276.57 to -12.60), carbohydrates (B -19.88, 95% CI -37.99 to -1.78), fats (B -6.99, 95% CI -13.69 to -0.29), and grains (B -1.46, 95% CI -2.43 to -0.50), and increased vegetable intake (B 0.47, 95% CI 0.06 to 0.88), compared to the control group (all P<.05). Favorable trends were noted in diastolic blood pressure (B -2.38, 95% CI -4.99 to 0.22; P=.07) and soft lean mass (B 0.34, 95% CI -0.06 to 0.75; P=.097). Both groups showed significant within-group improvements in low-density lipoprotein cholesterol, body fat percentage, waist circumference, and occupational sitting and walking (all P<.05), but between-group differences were nonsignificant. Conclusions: The 12-week mHealth intervention effectively improved physical activity and dietary behaviors and showed favorable trends in cardiometabolic indicators among sedentary employees. These findings support integrating mHealth programs into employee wellness initiatives to promote healthy behaviors, mitigate productivity loss, and reduce chronic disease burden. Further research should assess long-term sustainability, scalability, and cost-effectiveness in diverse occupational settings.

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¡Mi Vida Saludable!: Results of a Randomized, Controlled, 2x2 Factorial Trial of an In-Person and eHealth Diet and Physical Activity Intervention in Latina Breast Cancer Survivors (2025)

Journal of the Academy of Nutrition and Dietetics

Authors: Greenlee, Heather; Santiago-Torres, Margarita; Contento, Isobel; Koch, Pamela A.; Rillamas-Sun, Eileen; Gray, Heewon L.; Brickman, Adam M.; Ogden Gaffney, Ann; Thomson, Cynthia A.; Crane, Tracy E.; Dominguez, Naxielly; Sepulveda, Jhack; Marín-Chollom, Amanda M.; Paul, Rachel; Shi, Zaixing; Ulanday, Kathleene T.; Accordino, Melissa; Camacho, Fernando J.; Crew, Katherine D.; Kalinsky, Kevin; Taback, Brett; Trivedi, Meghna S.; Hale, Christiane; Reaves, Brieyona; Beauchemin, Melissa P.; Castellano, Marisol; Fuentes, Yanette; Eddy, Martha; Bella, Ana Leon; Meisner, Allison; Hershman, Dawn L.

Abstract

BACKGROUND: Latina breast cancer (BC) survivors experience health disparities. Effective lifestyle interventions are sparse. OBJECTIVE: This trial tested the effectiveness of a culturally-tailored diet and physical activity (PA) intervention in Latina BC survivors. DESIGN: Using a 2x2 factorial design, women were randomized to receive: 1) 4 weekly in-person group sessions, 2) 11 months of eHealth communications, 3) in-person sessions and eHealth, or 4) control. Follow-up data were collected at months 6 and 12. PARTICIPANTS/SETTING: Eligibility criteria were self-identification as Latina, post-treatment for early-stage BC, and consuming {\textless}5 daily servings of fruits and vegetables (F/V) and/or engaging in {\textless}150 minutes/week of moderate-to-vigorous PA (MVPA). A total 167 women from New York City were enrolled from July 2016 to October 2018 with 93.4\% retention at 12-month follow-up (n=156). INTERVENTION: All participants received a Fitbit and one 1:1 health coaching session. In-person group sessions included nutrition and PA education, cooking classes, fitness classes or grocery store visit, and social activities. The eHealth communications included motivational text messaging, emailed newsletters, and study website access. Activities were conducted in Spanish and English. MAIN OUTCOME MEASURES: Primary outcomes were 12-month change in F/V servings/day and energy density of food. Secondary outcomes were 12-month change in MVPA and anthropometry. STATISTICAL ANALYSIS: Outcomes comparing intervention arms with the control were examined using generalized estimating equations. RESULTS: At baseline (n=167), mean age was 56.7 years; 82.3\% had overweight/obesity. At month 12, daily F/V intake for women in the in-person sessions increased by 10\% and decreased by 44\% for women in the control, a +96\% group difference (p=0.01); no other between-group differences were observed. At month 12, women in the control had a 53\% increase in minutes/week of MVPA while women in the in-person plus eHealth group had a 34\% decrease, a -57\% group difference (p=0.01); no other between-group differences were noted. No changes in energy density or weight between groups were observed. CONCLUSION: Women randomized to the in-person ¡Mi Vida Saludable! classes modestly increased F/V intake at 12 months relative to control. Those receiving eHealth communication did not have diet, MVPA, or weight change. More research is needed to understand how to support Latina BC survivors make sustained diet and PA changes.

A 10-week remote monitoring study of sleep features and their variability in individuals with and without ADHD (2025)

BMC psychiatry

Authors: Denyer, Hayley; Carr, Ewan; Deng, Qigang; Asherson, Philip; Bilbow, Andrea; Folarin, Amos; Groom, Madeleine J.; Hollis, Chris; Sankesara, Heet; Dobson, Richard Jb; Kuntsi, Jonna

Abstract

Background: People with attention deficit hyperactivity disorder (ADHD) often report disturbed sleep, as well as co-occurring symptoms of anxiety and depression. Yet studies employing objective assessments often do not show as many sleep disturbances compared to subjective measures. These discrepancies may relate to subjective reports capturing problematic nights, which may not be captured in a single night's sleep or by averaging objective measurements over several nights. Given that variability in behaviours is in general strongly linked to ADHD, individuals with ADHD could have greater sleep variability than individuals without ADHD. Using active and passive remote monitoring, we investigate differences in the level and variability of daily sleep behaviours between individuals with and without ADHD and explore if sleep is associated with changes in anxiety and depressive symptoms across a 10-week remote monitoring period. Methods: Forty individuals (20 with ADHD, 20 without) took part in a 10-week remote monitoring study. Active monitoring involved participants completing questionnaires on ADHD and co-occurring psychiatric symptoms at weeks 2, 6 and 10. Passive monitoring involved participants wearing a wearable device (Fitbit) that measured sleep each night. Results: Individuals with and without ADHD were similar in the levels of sleep recorded each night. However, compared to those without ADHD, participants with ADHD had more variable sleep duration, sleep onset and offset, and sleep efficiency over 10 weeks. Within-individual associations of co-occurring anxiety and depressive symptoms with the sleep features were non-significant. Conclusions: In a 10-week remote monitoring study of sleep using a wearable device, we show that what distinguishes individuals with ADHD from those without is their greater variability in sleep features: participants with ADHD had a more variable sleep duration, sleep onset and offset, and sleep efficiency. Inconsistency and high variability are hallmarks of ADHD, and we show that this characteristic extends also to sleep among adolescents and adults with ADHD. Trial registration: Clinical trial number: not applicable. Keywords: ADHD; Attention deficit hyperactivity disorder; Remote measurement technology; Sleep variability; Wearable devices; mHealth.

A Culturally Tailored mHealth Intervention (MobileMen App) to Promote Physical Activity in African American Men: Protocol for a Comparative Effectiveness Trial (2025)

JMIR research protocols

Authors: Nuss, Kayla; Brice, Amanda; Hebert, Callie; Nauta, Phillip; Stull, April J.; Swift, Damon L.; Griffith, Derek M.; Buller, David B.; Newton, Robert L.

Abstract

Background: African American men are at a higher risk for serious health conditions such as cardiovascular disease, diabetes, and stroke compared to non-Hispanic White men. Physical activity (PA) is a modifiable health behavior that has been shown to decrease chronic disease risk; yet, PA engagement is alarmingly low in African American men. Interventions to improve PA engagement are effective in a number of populations; however, very few have been tailored to the unique needs of African American men. Even fewer have leveraged mobile health apps, despite African American men's interest in and willingness to use such technologies for health improvement. Objective: This comparative effectiveness trial aims to evaluate MobileMen, a PA promotion app tailored to the needs and preferences of African American men. This trial will compare the MobileMen app to a commercially available PA promotion app with similar features but lacks culturally tailored components. Methods: We will recruit a sample of "low active" (accumulating <7500 steps per day) African American men (n=100) aged >30 years from Baton Rouge, Louisiana, and the surrounding communities. All participants are given a Fitbit Charge 6 wearable activity tracker to assess daily PA and steps and are randomized to either the MobileMen intervention app or the comparator app, which is a commercially available PA tracking app called Stridekick. The Stridekick app has features similar to those in the MobileMen app but was not intentionally designed for African American men. The intervention period is 6 months during which participants will interact with their assigned mobile app. MobileMen includes features such as digital badges earned for PA; tangible prizes like exercise equipment; challenges among participants; goal setting; nutrition; PA; and behavior change educational information in text, audio, and video formats. Participants will complete assessments at baseline and at 6 months post randomization. Assessments include objective measurements of daily steps and minutes of moderate to vigorous PA, quality of life, dietary measures, self-efficacy for fruit and vegetable consumption and PA, and autonomous motivation for PA. Results: This trial is in the start-up phase. The MobileMen app development and usability testing was completed in August 2024. Participant recruitment efforts began in October 2024. The trial and associated data analyses and interpretation are planned to be completed by fall 2025. Conclusions: Mobile apps are a widely accessible means to disseminate culturally tailored PA promotion interventions to various populations, including African American men. MobileMen has the potential to impact PA engagement in African American men, which would dramatically improve the overall health and chronic disease risk in this underrepresented group.

A Dual In-Person and Remote Assessment Approach to Developing Digital End Points Relevant to Autism and Co-Occurring Conditions: Protocol for a Multisite Observational Study (2025)

JMIR Research Protocols

Authors: Yorke, Isabel; Boatman, Charlotte A.; Roy Choudhury, Akash; Oakley, Bethany; Conde, Pauline; Sankesara, Heet; Ranjan, Yatharth; Rashid, Zulqarnain; Dineley, Judith; Downs, Johnny; Chatham, Christopher H.; Cummins, Nicholas; Folarin, Amos; Loth, Eva; Buitelaar, Jan; Murphy, Declan; Dobson, Richard; Simonoff, Emily

Abstract

Background Research priorities for autistic people include developing effective interventions for the numerous challenges affecting their daily living, for example, mental health problems, sleep difficulties, and social well-being. However, clinical research progress is limited by a lack of validated objective measures that represent target outcomes for improvement. Digital technologies, including wearable devices and smartphone apps, provide opportunities to develop novel measures that may reflect everyday experience and complement key clinical assessments. However, little is known about the acceptability and feasibility of implementing digital data collection in this population. Objective The primary objective of this study is to evaluate the usability, acceptability, adherence, and feasibility of a dual in-person and remote (ie, at-home) protocol. Secondarily, we aim to explore the properties of certain resulting data with a view to developing novel digital end points for key target outcomes, including social communication, sleep, and mental health. Methods Eligible autistic and nonautistic in the AIMS Longitudinal European Autism Project were invited to participate in a digitally augmented in-person Autism Diagnostic Observation Schedule-2 (ADOS-2) and a 28-day remote measurement (RM) protocol involving wearing a Fitbit device, downloading a passive smartphone data collection app, and using 2 active reporting apps. Results The first AIMS Longitudinal European Autism Project study participants were enrolled in September 2021 (in-person component) and March 2022 (RM component). To date, 190 participants have taken part in the digitally augmented ADOS-2 component, and 86 participants have been enrolled for the RM protocol. Recruitment is now complete with some RM data collection ongoing until August 2025. Data analysis has commenced, including qualitative framework analysis of feedback interview data coproduced with autism community members, exploration of acceptability and feasibility metrics, pipeline development for ADOS-2 speech analysis, and RM sleep measures. Conclusions This study lays important groundwork in understanding the acceptability and feasibility of in-person and remotely implemented digital measurement procedures to capture meaningful outcomes in domains important to improving everyday life for autistic people. International Registered Report Identifier (IRRID) DERR1-10.2196/71145

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A Multiple Technology-Based Physical Activity Intervention for Latina Adolescents: Results From the Chicas Fuertes Randomized Controlled Trial (2025)

JMIR mHealth and uHealth

Authors: Carson, Jacob R.; Greenstadt, Emily; Olivera, Brittany; Dunsiger, Shira; Zive, Michelle; Higgins, Michael; Godino, Job; Marcus, Bess; Meyer, Dawn; Larsen, Britta

Abstract

BACKGROUND: Latina adolescents report low levels of moderate-vigorous physical activity (MVPA) and high lifetime risk of lifestyle-related diseases. There is a lack of MVPA interventions targeted at this demographic despite documented health disparities. Given their high rates of mobile technology use, interventions delivered through mobile devices may be effective for this population. OBJECTIVE: This paper examines the efficacy of the Chicas Fuertes intervention in increasing MVPA across 6 months in Latina adolescents. METHODS: Participants were Latina adolescents (aged 13-18 years) in San Diego County who reported being underactive ({\textless}150 min/wk of MVPA). All participants received a wearable fitness tracker (Fitbit Inspire HR); half were randomly assigned to also receive the multimedia intervention. Intervention components included a personally tailored website, personalized texting based on Fitbit data, and social media. The primary outcome was change in minutes of weekly MVPA from baseline to 6 months, measured by ActiGraph accelerometers and the 7-Day Physical Activity Recall Interview. Changes in daily steps using Fitbit devices were also examined to test intervention efficacy. RESULTS: Participants (N=160) were 15.85 (SD 1.71) years old on average, and mostly second generation in the United States. For ActiGraph-measured MVPA, participants in the intervention group (n=83) increased from a median of 0 (IQR 0-24) minutes/week at baseline to 64 (IQR 19-72) minutes/week at 6 months compared to control participants, who showed increases from a median of 0 (IQR 0-26) at baseline to 41 (IQR 7-76) minutes/week at 6 months (P=.04). Self-reported MVPA increased in the intervention group from a median of 119 (IQR 62.5-185) minutes/week at baseline to 147 (IQR 96-181) minutes/week at 6 months compared to control participants, who showed increases from a median of 120 (IQR 48.8-235) at baseline to 124 (IQR 100-169) minutes/week at 6 months (P=.03). Steps also increased in both groups, with the intervention group showing significantly greater increases (P=.03). CONCLUSIONS: This intervention was successful in using a tailored technology-based strategy to increase MVPA in Latina adolescents and provides a promising approach for addressing a key health behavior. Given the scalable technology used, future studies should focus on broad-scale dissemination to address health disparities.

A Personalized, Texting-Based Conversational Agent to Address Sleep Disturbance in Individuals Who Have Survived Breast Cancer: Protocol for a Pilot Waitlist Randomized Controlled Trial (2025)

JMIR research protocols

Authors: Tsai, Chi-Shan; Szewczyk, Warren; Drerup, Michelle; Liao, Jason; Vasbinder, Alexi; Greenlee, Heather; Heffner, Jaimee L.; Yung, Rachel; Reding, Kerryn W.

Abstract

Background: Sleep disturbance is one of the most common health concerns reported by individuals who have survived breast cancer (BC) and is associated with poor quality of life (QoL) and greater mortality after treatment. Cognitive behavioral therapy for insomnia (CBTi) has shown efficacy for improving sleep and QoL for this population. Considered the gold standard for insomnia treatment, CBTi can be delivered remotely, including via digital intervention. Despite the potential for wider dissemination of CBTi via digital means, these modalities have unique challenges, including technology barriers and poor adherence. We developed a conversational agent (CA) to deliver CBTi via a SMS text messaging intervention, supported by mobile-ready web content. Named "Cecebot," this CA delivers sleep education, implements sleep compression, provides just-in-time interventions for sleep-disrupting behaviors, and includes enhanced support for physical activity (PA) beyond what is typically included in CBTi. This represents a novel modality for a CBTi and PA intervention among individuals who have survived BC. Objective: We aim to examine the safety and acceptability of the Cecebot intervention, developed by an academic partnership between Dr Reding's research team and Moby Inc, for individuals who have survived BC and experience symptoms of insomnia, and to explore its efficacy. Methods: This trial will recruit 60 individuals who have survived BC and are experiencing moderate to severe sleep disturbance. Participants will be assigned to the Cecebot intervention or waitlist control group at a 1:1 ratio. The treatment group will receive the Cecebot intervention during weeks 1-6 of the study, while the waitlist control condition will receive the Cecebot intervention during weeks 6-12. The Cecebot intervention uses SMS text messaging technology paired with a Fitbit. Participants will be assessed at baseline, week 6, and week 12. Measurements will include feasibility and acceptability and will explore the effect of the Cecebot intervention. Feasibility will be assessed through recruitment, enrollment, and retention rates. Acceptability will be evaluated using a satisfaction survey and open-ended responses. Quantitative analysis, such as t test, Fisher exact tests, and generalized linear models, will be used to assess feasibility, baseline group differences, and the outcomes of the intervention. Results: Recruitment of participants began in Fall 2024. The completion of data collection is anticipated to be by Fall 2025. Conclusions: The study results will give insight into the potential for an SMS text messaging-based CA to improve sleep in individuals who have survived BC and experience sleep disturbances.

A pilot exercise intervention to evaluate the role of cardiorespiratory fitness in modulating cardiotoxicity among childhood cancer survivors exposed to anthracycline therapy (2025)

Cardio-Oncology (London, England)

Authors: Toro-Salazar, Olga H.; Pescatello, Linda S.; Mah, May Ling; Wilhelm, Carolyn; Orsey, Andrea D.; Berthod, Tiffany; Mosha, Maua H.; Brimacombe, Michael; Fan, Tongyao; Wanner, Corbinian; Slawinski, Michelle; Hor, Kan N.

Abstract

BACKGROUND: Childhood cancer survivors (CCS) often experience cancer treatment-related cardiotoxicity, leading to reduced cardiorespiratory fitness (CRF), an integrated marker of cardiovascular, respiratory, and musculoskeletal function. Furthermore, low CRF is a strong predictor of mortality. OBJECTIVE: This study investigates the effects of a 16-week aerobic exercise intervention on CRF changes, as measured by peak oxygen consumption (VO2peak) and parameters of cardiac structure and function by cardiac magnetic resonance imaging (CMR). METHODS: Anthracycline-treated CCS were enrolled {\textgreater} 2 years post-treatment and underwent cardiotoxicity risk stratification, cardiopulmonary stress test (CPET) to determine CRF, and CMR before and after a 16-week aerobic exercise intervention. The intervention consisted of individualized sessions performed 3–5 days per week, with duration progressively increasing from 15 to 45 min at 50–80\% of age-predicted maximal heart rate. Exercise adherence and intensity were objectively measured throughout the intervention using a Fitbit tracker. Subclinical myocardial dysfunction was assessed by segmental strain abnormality, with specific focus on the number of segments showing peak circumferential strain magnitude (εcc) ≤ 10\% and εcc ≤ 17\%. Descriptive and comparative statistics, including Pearson’s correlation and chi-square/Fisher’s exact and Mann-Whitney tests, were performed using SAS 9.4, with significance set at p {\textless} 0.05. RESULTS: Forty-seven subjects (median age 22.0 years [IQR 8.5], 10–25 years), 57.4\% male, and 75\% white were enrolled. Thirty patients (63.8\%) completed the exercise intervention, 56.7\% male, and 83.3\% white, with a median age of 24.0 years (IQR 9.8 years). Twenty participants (42.6\%) met the predefined adherence criterion of achieving ≥ 100\% of the prescribed fairly active plus very active minutes. There was no statistically significant change in VO₂peak (mL/kg/min) for the study cohort (median [IQR]: 34.0 [13.7] vs. 34.4 [13.3]; p = 0.76). Total active minutes were positively correlated with change in VO2peak (mL/kg/min) (r = 0.71, p {\textless} 0.005), and VO2peak (L/min) (r = 0.64, p = 0.03). VO2peak increased ≥ 1 mL/kg/min in 16/30 (53.3\%) of subjects. These subjects labeled “responders”, demonstrated a median increase in VO2peak of 3.6 mL/kg/min and significant increase in right ventricular end diastolic volume index (p = 0.035), left ventricular stroke volume index (p = 0.014) and ejection fraction (EF) (p = 0.045). At baseline, 12 subjects met high-risk definition based on segmental strain abnormalities (i.e., ≥ 2 segments with εcc ≤ 10\% or ≥ 9 segments ≤ 17\%). High risk subjects showed significant improvement in εcc with a post-intervention reduction in number of segments ≤ 10\% from 2.0 to 0.0 (p = 0.017). CONCLUSIONS: Overall CCS did not show a significant change in VO₂peak in response to a 16-week exercise intervention. Those with higher adherence to the exercise prescription were more likely to experience meaningful improvements in post-intervention VO2peak and improvement in CMR parameters of structure and function. Participants classified as high-risk, based on εcc abnormalities, derived the greatest benefit. TRIAL REGISTRATION: Retrospectively registered: https://classic.clinicaltrials.gov/ct2/show/NCT04036032, Registration date: July 25, 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40959-025-00388-5.

A Series of Personalized Melatonin Supplement Interventions for Poor Sleep: Feasibility Randomized Crossover Trial for Personalized N-of-1 Treatment (2025)

JMIR Formative Research

Authors: Butler, Mark J.; Chandereng, Thevaa; Ahn, Heejoon; Slotnick, Stefani; Miller, Danielle; Perrin, Alexandra; Rodillas, Jordyn; Friel, Ciaran P.; Goodwin, Ashley M.; Cheung, Ying Kuen; Davidson, Karina W.

Abstract

Background Poor sleep (defined by short sleep duration or poor quality) is a common condition with potential serious health consequences. Exogenous melatonin supplements have been found to effectively improve poor sleep but have also been shown to have heterogeneity of treatment effects (HTEs) between individuals. Personalized N-of-1 trials, in which each participant is the unit of analysis, are ideal for identifying whether a treatment with high HTE is beneficial for each individual patient. Objective This study aimed to identify the feasibility, acceptability, and effectiveness of a series of personalized N-of-1 trials of melatonin for poor sleep. Methods This study consisted of 60 digital, personalized N-of-1 crossover trials comparing the effects of 3.0 mg and 0.5 mg of melatonin versus placebo for poor sleep with randomization to 1 of 2 orders. The trial comprised a 2-week baseline period and a 12-week intervention period. The primary outcomes were usability of the personalized trial system (measured using the System Usability Scale [SUS]) and participant satisfaction with the trial. Effectiveness outcomes included sleep duration (measured using a Fitbit activity tracker [Google]) and sleep quality (measured using the consensus sleep diary). Results Participants rated the usability of the personalized trial as acceptable (average SUS score 76.3, SD 17.1), and 96\% (55/57) of those who completed satisfaction surveys stated that they would recommend the trial to others. Importantly, indices of HTE were low for 3.0 mg and 0.5 mg doses of melatonin, indicating that the effect of these treatments on sleep duration and sleep quality did not substantially vary between participants and that averaged treatment responses are appropriate. Averaged participant sleep duration did not significantly differ between the 3.0 mg (P=.70) and 0.5 mg (P=.90) melatonin intervention periods and the baseline period. In addition, regression models did not show differences between different levels of melatonin and placebo periods for sleep duration or quality. Conclusions Participant ratings of the usability of and satisfaction with this series of personalized N-of-1 trials of melatonin for sleep suggest these trials are both feasible and acceptable. However, our results show that melatonin supplements did not significantly improve sleep duration or sleep quality. Furthermore, the treatment effects’ lack of heterogeneity among participants suggests that future use of N-of-1 trials of melatonin for poor sleep is not needed.

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Accelerometers can correctly count orthopaedic patients' early post-operative steps while using walking aids (2025)

Journal of Experimental Orthopaedics

Authors: Tsamassiotis, Spiros; Schwarze, Michael; Gehring, Philipp; Karkosch, Roman F.; Tücking, Lars-René; Einfeldt, Ann-Kathrin; Jakubowitz, Eike

Abstract

Purpose: Effective rehabilitation after orthopaedic surgery is critical. The early post-operative phase is increasingly managed in outpatient settings, necessitating objective measures such as step counts to monitor rehabilitation progress. However, it remains unclear if commercially available wearables or accelerometers using simple algorithms can accurately count steps in early post-operative conditions. We hypothesised that only accelerometers could accurately determine the number of steps under these conditions. Methods: This case series involved 20 healthy subjects, 7 female and 13 males, walking in a circle at varying speeds under partial loading with three different walking aids (forearm crutches, walking frame and rolling walker) and four wearables (Vivofit 4, Fenix 3HR, Fitbit Charge 3 and Omron HJ-325) and one accelerometer (AX6) worn on the wrist, hip and ankle. The two-point and modified three-point gait patterns commonly used post-operatively were simulated. The primary end point was the relative error (RE), defined as RE = (manual count - automated count)/manual count, of each wearable measurement compared to visual and video step counting, the gold standard. Results: The RE of AX6 and Fitbit was less than 0.1 for all walking aids except the rolling walker, with AX6 showing the lowest standard deviation (SD) compared to other wearables. Other wearables had significantly higher RE. Increased gait speed generally improved accuracy, reducing RE in most devices, except for the AX6, which showed the opposite trend. At 0.6 m/s, only AX6 achieved an RE below 0.1. The ankle was identified as the best measuring location. Conclusion: During the early post-operative period, commercial wearables can only accurately count steps under specific conditions and should be used cautiously for monitoring steps in the early post-operative phase. However, accelerometers with appropriate coding appear suitable for this purpose. Level of evidence: Level III diagnostic study. Keywords: accelerometer; accuracy; assistive device; early post‐operative period; orthopaedic rehabilitation; speed; step count; walking aid; wearable; weight‐bearing.

Acceptability and Preliminary Efficacy of a Novel Web-Based Physical Activity for the Heart (PATH) Intervention Designed to Promote Physical Activity in Adults With Obesity: Protocol for a Pilot Randomized Controlled Trial (2025)

JMIR research protocols

Authors: Kariuki, Jacob; Burke, Lora; Erickson, Kirk; Sereika, Susan; Paul, Sudeshna; Cheng, Jessica; Biza, Heran; Abdirahman, Amjad; Wilbraham, Katherine; Milton, Heather; Brown, Cornelius; Sells, Matthew; Osei Baah, Foster; Wells, Jessica; Chandler, Rasheeta; Barone Gibbs, Bethany

Abstract

Background: Even in the absence of weight loss, any level of physical activity (PA) can reduce the risk of cardiovascular disease among individuals with obesity. However, these individuals face multifaceted barriers that reduce their motivation and engagement in PA. They prefer programs that are convenient, fun to engage in, and feature people who they can relate to. Yet, there is a paucity of PA interventions that are designed to incorporate these preferences. We designed the web-based PA for The Heart (PATH) intervention to address this gap. Objective: This study aimed to describe the protocol of a study that aims to examine the acceptability and preliminary efficacy of PATH intervention among insufficiently active adults with obesity aged at least 18 years. Methods: This is a 6-month pilot randomized controlled trial (RCT), using a parallel design with 1:1 allocation to intervention or control group. The PATH intervention group is given access to the PATH platform, but the resources each participant can access are tailored according to their baseline fitness level. Control group receives a self-help PA handout. Both groups self-monitor their PA using Fitbit (Google) and have Zoom (Zoom Video Communications) meetings twice a month with either the health coach (intervention) or study coordinator (control). The outcomes at 6-months include acceptability, changes in PA, and cardiometabolic risk from baseline to 6-months. Results: We screened 763 individuals for eligibility and 89 participants were enrolled and randomized to the intervention (45/504, 50.6%) and control arms (44/504, 49.4%). The average age was 48.7 (SD 12.17) years, and most participants were female (81/504, 90.1%), Black (45/504, 50.6%), and non-Hispanic (83/504, 93.3%). No systematic differences in baseline characteristics were observed between the study arms. The 6-month intervention is currently underway, and the completion of follow-up data collection is expected in February 2025, with results to be published soon after. Conclusions: The PATH intervention offers a promising, evidence-based approach to overcoming the barriers that have hindered previous PA programs for adults with obesity. It can support new and existing programs to foster long-term maintenance of health-enhancing PA.

Acceptability of the Fit2ThriveMB mHealth physical activity promotion intervention in women with metastatic breast cancer (2025)

Supportive Care in Cancer: Official Journal of the Multinational Association of Supportive Care in Cancer

Authors: Starikovsky, Julia; Solk, Payton; Desai, Ria; Reading, Jean M.; Hasanaj, Kristina; Wang, Shirlene D.; Carden, Lillian B.; Wolter, Melanie; Hickey, Brendan; Lee, Jungwha; Song, Jing; Freeman, Hannah; Alexander, Jacqueline; Spring, Bonnie; Gradishar, William; Phillips, Siobhan M.

Abstract

Purpose: Increasing physical activity (PA) is safe and associated with improved health outcomes in patients with metastatic breast cancer (MBC). Mobile health (mHealth) PA interventions that allow for remote monitoring and tailoring to abilities may be particularly useful for MBC patients. However, limited data exist on the acceptability of these interventions for MBC patients. This study examined the acceptability of Fit2ThriveMB, a highly tailored mHealth intervention targeting increased daily steps in MBC patients. Methods: Insufficiently active women with MBC ((N = 25) Mage = 57.2, SD = 11.9) received the Fit2ThriveMB intervention (Fit2ThrviveMB app, Fitbit, weekly coaching calls) for 12 weeks. Participants completed an online questionnaire (n = 22) and semi-structured interview (n = 23) at 12 weeks to assess intervention acceptability. Quantitative data were analyzed using descriptive statistics. Interviews were analyzed and coded using thematic content analysis and consensus review. Results: All (n = 23) participants indicated they were satisfied with the intervention, Fit2ThriveMB app design, and Fitbit usability via questionnaire. Four themes emerged from qualitative interview data: (1) Overall satisfaction with implementation, (2) Social interaction is important, but within-app social features need improvement, (3) Fit2ThriveMB was encouraging and enhanced accountability, (4) Fit2ThriveMB helped form sustainable habits. Participants were generally satisfied with the intervention. However, areas for improvement were identified for some study features. Conclusions: Findings indicate Fit2ThriveMB was acceptable among people with MBC. Further refinement of Fit2ThriveMB social feed features and step count goals is warranted for future testing in fully powered trials with a larger sample size. Keywords: Acceptability; Behavioral medicine; Exercise; MHealth; Metastatic breast cancer.

Activity tracking devices in pregnancy: Understanding the participant experience in a longitudinal birth cohort (2025)

Women's Health (London, England)

Authors: Redding, Ashley; Coates, Dionne; Cassidy-Bushrow, Andrea E.; Straughen, Jennifer K.; Santarossa, Sara

Abstract

Background: Improving understanding of physical activity (PA) during pregnancy can inform future interventions and support the delivery of high-quality prenatal care. Objectives: Within the longitudinal birth cohort Research Enterprise to Advance Children's Health (REACH), the sub-study REACH-Fitbit sought to understand the prenatal experiences of utilizing an activity monitoring device and best practices for receiving PA information. Design: REACH recruits gravid patients ⩾18 years old receiving prenatal care and planning to deliver at predefined hospitals. REACH-Fitbit participants had to be <20 weeks gestation with access to a Bluetooth-enabled device. Recruitment (self-selection) for focus groups occurred from completed REACH-Fitbit participants (e.g., delivered their baby). Methods: A semi-structured moderator guide was utilized to capture feedback on experiences, adherence to protocols, resources, and best practices for measuring PA during pregnancy. Two groups of six participants participated virtually, which included conversations about the overall participant experience, compliance with protocols, and opportunities for knowledge dissemination about PA. Results: The majority of focus group participants identified as Black, were between 20 and 29 years of age, and had positive feelings about the Fitbit, finding it usable and functional. Participants felt protocol compliance was facilitated by text message reminders and research team support, while barriers included Fitbit application problems, busy schedules, and forgetting. Participants preferred to receive PA information from a trusted healthcare source (e.g., doctor, nurse, or other healthcare provider), though most participants (57%) did not receive PA information during prenatal care. Participants were interested in learning about the safety, type, and amount of prenatal PA in which to engage. Conclusion: Findings presented here can support compliance in future studies or PA interventions utilizing similar technology. Incentives for compliance with study protocols and enhanced communication with the research team can improve participant engagement. Future work will address the need to communicate the interests of pregnant persons to clinical care teams, specifically, improvements to how providers share information on PA.

Adherence to Accelerometer Use in Older Adults Undergoing mHealth Cardiac Rehabilitation: Secondary Analysis of a Randomized Clinical Trial (2025)

Journal of Medical Internet Research

Authors: Barua, Souptik; Upadhyay, Dhairya; Pena, Stephanie; McConnell, Riley; Varghese, Ashwini; Adhikari, Samrachana; LeRoy, Erik; Schoenthaler, Antoinette; Dodson, John A.

Abstract

BACKGROUND: Wearable accelerometers, which continuously record physical activity metrics, are commonly used in mobile health-enabled cardiac rehabilitation (mHealth-CR). The association between adherence to accelerometer use during mHealth-CR and improvement in clinical outcomes, such as functional capacity, is understudied. The emergence of artificial intelligence (AI) technology provides novel opportunities to investigate accelerometry use patterns in relation to mHealth-CR outcomes. OBJECTIVE: In this study, we sought to use an AI clustering framework to identify distinct behavioral phenotypes of adherence to accelerometer use. We then aimed to quantify the association of these adherence phenotypes with functional capacity improvements in older adults undergoing mHealth-CR. METHODS: We analyzed data from the RESILIENT (Rehabilitation at Home Using Mobile Health in Older Adults After Hospitalization for Ischemic Heart Disease) trial, the largest randomized clinical study to date comparing mHealth-CR versus usual care in older adults (aged ≥65 years). Intervention arm participants were instructed to wear a Fitbit accelerometer for the 3-month study duration. Adherence to accelerometer use was quantified as overall adherence (percentage of days worn) via k-means clustering AI-derived measures and compared with changes in 6-minute walk distance (6-MWD), adjusted for demographic and clinical covariates. RESULTS: Among 271 participants with a mean age of 71 years (SD 8), of whom 198 (73\%) were male, accelerometers were worn for an average of 76 days (95\% confidence limits 73,78) over 3 months. Adjusted analyses showed a weak association between days of wear and improvement in 6-MWD, with every 30 additional days associated with an 11-meter improvement (P=.08). Our k-means clustering framework identified adherence phenotypes at two resolutions: low resolution (k=2 clusters) and high resolution (k=8 clusters). The consistently high adherence cluster trended toward a 24.6-meter improvement in 6-MWD compared to the low and declining adherence clusters (n=39; 95\% CI 0.7-49.9; P=.06). The 8-cluster phenotyping revealed a richer set of adherence patterns, with the consistently high adherence cluster in this analysis having a 38.5-meter (95\% CI 2.2-74.7; P=.04) improvement in 6-MWD than the low adherence cluster, as well as greater average daily steps over the 3-month intervention (mean 7518, SD 3415 vs mean 4800, SD 2920 steps; P=.008). CONCLUSIONS: A time-series AI clustering framework identified a range of behavioral phenotypes representing different degrees of adherence to accelerometer use. Regression analysis identified a weak association between the higher adherence phenotype and functional capacity improvement in older adults undergoing mHealth-CR. Our AI-derived accelerometry adherence phenotypes may offer a new approach to tailor mHealth-CR regimens to individual patients, potentially leading to better outcomes in this high-risk population. TRIAL REGISTRATION: ClinicalTrials.gov NCT03978130; https://clinicaltrials.gov/study/NCT03978130. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/32163.

Adolescent smartphone use, sleep, and physical activity: daily associations between sensor-based measures in the adolescent brain cognitive development (ABCD) study (2025)

Psychiatry Research

Authors: Alexander, Jordan D.; Nguyen-Louie, Tam T.; Gupta, Suhaani; Cummins, Kevin M.; Wade, Natasha E.

Abstract

PURPOSE: Potential health consequences of adolescent smartphone use are a growing public concern. Improving upon existing, largely self-report-based research, this study investigated relationships between adolescent smartphone use, sleep, and physical activity using passive sensor measures. METHODS: Over three weeks, 791 Adolescent Brain Cognitive Development (ABCD) Study participants (Mage=14.12, 53 \% female) provided smartphone application and keyboard use data via the Effortless Assessment Research System (EARS) application, and sleep and physical activity data via Fitbit device. RESULTS: Mixed-effects models found that daytime/evening application use (6:00AM-7:59PM) predicted reduced exercise, more time sedentary, and fewer daily steps (Standardized β=-0.21-0.07, P{\textless}.001). Late-evening use (8:00PM-9:59PM) modestly predicted increased sedentary time and reduced steps (Standardized β=-0.05-0.02, P{\textless}.001). Late-night use (10:00PM-5:59AM) predicted reduced sleep, delayed sleep onset, delayed waking, increased sedentary time, and fewer daily steps (Standardized β=-0.16-0.27, P{\textless}.001). After disaggregating within and between-person smartphone use, within-person relationships remained significant, with associations of similar magnitude to the initial analyses (daytime/evening use: standardized ꞵ=-0.22-0.07, P{\textless}.001; late-evening use: standardized ꞵ=-0.05-0.02, P{\textless}.001; late-night use: standardized ꞵ=-0.16-0.24, P≤.002), indicating daily-level relationships unattributable to between-subject differences. Examining smartphone use effects by hour relative to sleep onset indicated that only use recorded after initial sleep onset significantly predicted sleep, while use recorded 3-12 hours before sleep onset significantly predicted step counts. CONCLUSIONS: Using passive sensor data, we found significant associations between adolescent smartphone use, physical activity, and sleep which differed by time of day and remained significant within subjects. Experimental replication is recommended to strengthen tentative causal claims.

American Life in Realtime: Benchmark, publicly available person-generated health data for equity in precision health (2025)

PNAS Nexus

Authors: Chaturvedi, Ritika R.; Angrisani, Marco; Troxel, Wendy M.; Jain, Monika; Gutsche, Tania; Ortega, Eva; Boch, Adrien; Liang, Citina; Sima, Shiyang; Mezlini, Aziz; Daza, Eric J.; Boodaghidizaji, Miad; Suen, Sze-chuan; Chaturvedi, Alok R.; Ghasemkhani, Hossein; Ardekani, Arezoo M.; Kapteyn, Arie

Abstract

Person-generated health data (PGHD) from smartphones/wearables are invaluable for precision health, a field promoting health equity through tailored disease prevention, detection, and intervention strategies. However, pervasive convenience sampling in extant PGHD research introduces selection biases that systematically underrepresent disadvantaged groups, limit model generalizability, and risk exacerbating health disparities. Benchmark PGHD (representative, validated, longitudinal, and frequently repeated) are urgently needed to support model equity. To address this fieldwide limitation, we established American Life in Realtime (ALiR), a longitudinal population health study involving PGHD collected from a probability-based, nationally representative cohort using study-provided Fitbits and (as needed) 4G tablets. As a result, ALiR's 1,038 participants are broadly representative across comprehensive sociodemographic, behavioral, and health-related US population norms, overcoming disparities in established convenience samples (e.g. NIH's All of Us; AoU). Only two sources of differential enrollment remained: older age (odds ratio [OR]: 1.27, 99\% CI: 1.12–1.45) during consent, lower education (OR: 0.86, 99\% CI: 0.79–0.94) during enrollment, though oversampling individuals without bachelor's degrees sufficiently counterbalanced the latter. An illustrative coronavirus disease 2019 classification model—chosen for global significance, known disparities in experience and outcomes, and methodological relevance—trained using ALiR performed equivalently when tested in sample (area under the curve [AUC] = 0.84, 95\% CI: 0.79–0.89) and out of sample on AoU (AUC = 0.83, 95\% CI: 0.78–0.89) overall, and in historically underserved subgroups (AUC = 0.82–1.0). Conversely, an identically trained classification model using AoU underperformed by 35\% out of sample on ALiR (overall AUC = 0.68, 95\% CI: 0.61–0.75 vs. AUC = 0.93, 95\% CI: 0.91–0.96 in sample), with worse performance in older female and non-White subgroups (by 22–40\%). Our results suggest that probability sampling and hardware provisioning enabled cohort inclusivity and generalizable model performance, supporting ALiR's benchmarking potential for equitable recruitment, PGHD collection, and precision health application.

URL

An approach to boost adherence to self-data reporting in mHealth applications for users without specific health conditions (2025)

BMC medical informatics and decision making

Authors: Aguiar, Maria; Cejudo, Ander; Epelde, Gorka; Chaves, Deisy; Trujillo, Maria; Artola, Garazi; Ayala, Unai; Bilbao, Roberto; Tueros, Itziar

Abstract

Background: The popularization of mobile health (mHealth) apps for public health or medical care purposes has transformed human life substantially, improving lifestyle behaviors and chronic condition management. The objective of this study is to evaluate the effect of gamification features in a mHealth app that includes the most common categories of behavior change techniques for the self-report of lifestyle data. The data reported by the user can be manual (i.e., diet, activity, and weight) and automatic (Fitbit wearable devices). As a secondary objective, this work aims to explore the differences in the adherence when considering a longer study duration and make a comparative analysis of the gamification effect. Methods: In this study, the effectiveness of various behavior change techniques strategies is evaluated through the analysis of two user groups. With a first group of users, we perform a comparative analysis in terms of adherence and system usability scale of two versions of the app, both including the most common categories of behavior change techniques but the second version having added gamification features. Then, with a second group of participants and the best mHealth app version, a longer study is carried out and user adherence, the system usability scale and user feedback are analyzed. Results: In the first stage study, results have shown that the app version with gamification features has achieved a higher adherence, as the percentage of days active was higher for most of the users and the system usability scale score is 80.67, which is categorized as rank A. The app also exceeded the expectations of the users by about 70% for the app version with gamification functionalities. In the second stage of the study, an adherence of 76.25% is reported after 8 weeks and 58% at the end of the pilot for the mHealth app. Similarly, for the wearable device, an adherence of 74.32% is achieved after 8 weeks and 81.08% is obtained at the end of the pilot. We hypothesize that these specific wearable devices have contributed to a decreased system usability scale score, reaching 62.89 which is ranked as C. Conclusion: This study evidences the effectiveness of the gamification category of behavior change techniques in increasing the overall user adherence, expectations, and perceived usability. In addition, the results provide quantitative results on the effect of the most common categories of behavior change techniques for the self-report of lifestyle data. Therefore, a higher duration in the study has shown several limitations when capturing lifestyle data, especially when including wearable devices such as Fitbit.

Associations between objective and self-perceived physical activity and participation in everyday activities in mild stroke survivors (2025)

PloS One

Authors: de Diego-Alonso, Cristina; Alegre-Ayala, Jorge; Blasco-Abadía, Julia; Doménech-García, Víctor; Part\&Sed-Stroke collaborators’; Bellosta-López, Pablo

Abstract

BACKGROUND AND PURPOSE: Stroke survivors present limited levels of physical activity (PA) and participation in everyday activities although the specific interaction between PA and participation in these individuals is still uncertain. This study aimed to analyse the relationship between PA and participation in everyday activities among Spanish mild stroke survivors. METHODS: A total of 130 mild stroke survivors (61.3 ± 12.4 years, 35\% female) with preserved walking ability and without cognitive and communication impairments participated in this cross-sectional study involving several rehabilitation centres from Spain. Self-reported levels of PA were reported by the International Physical Activity Questionnaire - short form (IPAQ-SF). Objective PA measures were monitored with the wristband Fitbit Inspire 2, recording the average steps/day and kilocalories/day. Participation and activity satisfaction levels were measured with the Satisfaction with Daily Occupations-Occupational Balance (SDO-OB) and participation retention through Activity Card Sort (ACS). RESULTS: ACS total score showed a weak correlation with self-reported PA (rho = 0.324) and moderate correlations with kilocalories/day and average steps/day (rho ≥ 0.581), while stronger correlations were found for the ACS subdomain of instrumental activities (rho ≥ 0.640) compared to the subdomains of leisure activities and social participation (rho ≤ 0.454). SDO-OB participation showed moderate correlations with kilocalories/day, and average steps/day (rho ≥ 0.647), and a weak correlation with self-reported PA (rho = 0.303). Weaker correlations were found for SDO-OB satisfaction with objective PA measures (rho = 0.407) and self-reported PA (rho = 0.254). Relationships between variables were explored by calculating Spearman correlation coefficients. DISCUSSION AND CONCLUSIONS: The objective and self-reported measures of PA in mild stroke survivors have a bilateral relationship with their current participation levels and the retained instrumental activities of daily living. However, the weaker correlations with leisure and social participation may suggest that promoting PA alone without integrating it into daily activities relevant to the stroke survivor may be insufficient to achieve comprehensive goals during rehabilitation programs.

At-home Breast Oncology care Delivered with EHealth solutions (ABODE) study protocol: a randomised controlled trial (2025)

BMJ open

Authors: Mac, Amanda; Kalia, Mohini; Reel, Emma; Amir, Eitan; Isenberg, Adina; Kim, Raymond H.; Kennedy, Erin; Koch, C. Anne; Li, Madeline; McCready, David; Metcalfe, Kelly; Okrainec, Allan; Papadakos, Janet; Rotstein, Sarah; Rodin, Gary; Xu, Wei; Zhong, Toni; ABODE Study Group; Cil, Tulin D.

Abstract

INTRODUCTION: The COVID-19 pandemic disrupted healthcare delivery for patients with breast cancer. eHealth solutions enable remote care and may improve patient activation, which is defined as having the knowledge, skills and confidence to manage one's health. Thus, we developed the Breast Cancer Treatment Application (app) for patients and practitioners to use throughout the cancer care continuum. The app facilitates virtual assistance, delivers educational resources, collects patient-reported outcome measures and provides individualised support via volunteer e-coaches. Among newly diagnosed patients with breast cancer, we will compare changes in patient activation, other patient-reported outcomes and health service outcomes over 1 year between those using the app and Fitbit, and those receiving standard care and Fitbit only. METHODS AND ANALYSIS: This randomised controlled trial will include 200 patients with breast cancer seen at a tertiary care cancer centre in Ontario, Canada. The intervention group (n=100) will use the app in addition to standard care and Fitbit for 13 months following diagnosis. The control group (n=100) will receive standard care and Fitbit only. Patients will complete questionnaires at enrolment, 6 and 12 months post-diagnosis to measure patient activation (Patient Activation Measure-13 score), distress, anxiety, quality of life and experiences with their care and information received. All patients will also receive Fitbits to measure activity and heart rate. We will also measure wait times and number of visits to ambulatory care services to understand the impact of the app on the use of in-person services. ETHICS AND DISSEMINATION: Ethics approval was obtained on 6 January 2023. Protocol version 2.0 was approved on 6 January 2023. The trial is registered with ClinicalTrials.gov. Study findings will be disseminated via publication in a peer-reviewed journal and shared with participants, patient programmes and cancer awareness groups. The app has also been approved as a secure communication method at our trial institution, thus we are well-positioned to support future integration of the app into standard care through collaboration with our hospital network. TRIAL REGISTRATION NUMBER: NCT05989477.

Capturing Real-World Habitual Sleep Patterns With a Novel User-Centric Algorithm to Preprocess Fitbit Data in the All of Us Research Program: Retrospective Observational Longitudinal Study (2025)

Journal of Medical Internet Research

Authors: Master, Hiral; Annis, Jeffrey; Ching, Jack H.; Gleichauf, Karla; Han, Lide; Coleman, Peyton; Full, Kelsie M.; Zheng, Neil; Ruderfer, Douglas; Hernandez, John; Schneider, Logan D.; Brittain, Evan L.

Abstract

Background: Commercial wearables such as Fitbit quantify sleep metrics using fixed calendar times as default measurement periods, which may not adequately account for individual variations in sleep patterns. To address this limitation, experts in sleep medicine and wearable technology developed a user-centric algorithm designed to more accurately reflect actual sleep behaviors and improve the validity of wearable-derived sleep metrics. Objective: This study aims to describe the development of a new user-centric algorithm, compare its performance with the default calendar-relative algorithm, and provide a practical guide for analyzing All of Us Fitbit sleep data on a cloud-based platform. Methods: The default and user-centric algorithms were implemented to preprocess and compute sleep metrics related to schedule, duration, and disturbances using high-resolution Fitbit sleep data from 8563 participants (median age 58.1 years, 6002/8341, 71.96%, female) in the All of Us Research Program (version 7 Controlled Tier). Variations in typical sleep patterns were calculated by examining the differences in the mean number of primary sleep logs classified by each algorithm. Linear mixed-effects models were used to compare differences in sleep metrics across quartiles of variation in typical sleep patterns. Results: Out of 8,452,630 total sleep logs collected over a median of 4.2 years of Fitbit monitoring, 401,777 (4.75%) nonprimary sleep logs identified by the default algorithm were reclassified as primary sleep by the user-centric algorithm. Variation in typical sleep patterns ranged from -0.08 to 1. Among participants with the greatest variation in typical sleep patterns, the user-centric algorithm identified significantly more total sleep time (by 17.6 minutes; P<.001), more wake after sleep onset (by 13.9 minutes; P<.001), and lower sleep efficiency (by 2.0%; P<.001), on average. Differences in sleep stage metrics between the 2 algorithms were modest. Conclusions: The user-centric algorithm captures the natural variability in sleep schedules, providing an alternative approach to preprocess and evaluate sleep metrics related to schedule, duration, and disturbances. A publicly available R package facilitates the implementation of this algorithm for clinical and translational research. Keywords: All of Us Research Program; Fitbit; R package; algorithms; metrics; sleep.

Changing User Experience of Wearable Activity Monitors Over 7 Years: Repeat Cross-Sectional Survey Study (2025)

Journal of Medical Internet Research

Authors: Beckett, Darcy; Curtis, Rachel; Szeto, Kimberley; Maher, Carol

Abstract

Background: Lifestyle behaviors, including physical inactivity, sedentary behavior, poor sleep, and unhealthy diet, significantly impact global population health. Wearable activity trackers (WATs) have emerged as tools to enhance health behaviors; however, their effectiveness and continued use depend on their user experience. Objective: This study aims to explore changes in user experiences, preferences, and perceived impacts of WATs from 2016 to 2023. Methods: We conducted a cross-sectional online survey among an international cohort of adults (n=475, comprising 387 current and 88 former WAT users). Results were compared with a 2016 cross-sectional online survey (n=237, comprising 200 current and 37 former WAT users) using descriptive statistics and chi-square tests. The survey examined brand preference, feature usefulness, motivations, perceived health behavior change, social sharing behaviors, and technical issues. Results: In 2023, Apple (210/475, 44%) and Fitbit (101/475, 21%) were the most commonly used devices, compared with the 2016 survey where Fitbit (160/237, 68%) and Garmin devices (39/237, 17%) were most common. The median usage duration in 2023 was 18 months, significantly longer than the 7 months reported in 2016, with most users planning ongoing use. Users in both survey years reported greater improvements in physical activity than diet or sleep, despite lower improvement in physical activity in 2023 compared with 2016, contrasted with greater perceived improvements in diet and sleep. Social media sharing of WAT data notably rose to 73% (283/387) in 2023 from 35% (70/200) in 2016. However, reports of technical issues and discomfort increased, alongside a decrease in overall positive experiences. There was also a noticeable shift in discontinuation reasons, from having learned everything possible in 2016 to dissatisfaction in 2023. Conclusions: The study highlights significant shifts in WAT usage, including extended use and evolving preferences for brands and features. The rise in social media sharing indicates a deeper integration of WATs into everyday life. However, user feedback points to a need for enhanced design and functionality despite technological progress. These findings illustrate WAT's potential in health promotion, emphasizing the need for user-focused design in diverse populations to fully realize their benefits in enhancing health behaviors. Keywords: Apple; Fitbit; accessibility; activity tracker; cohort; cross-sectional survey; diet; health behaviour; lifestyle; mobile phone; physical activity; preferences; reliability; sleep; user experience; wearable activity trackers.

Characterization and clustering of intra-day physical activity patterns using accelerometry among sexual and gender minority adults (2025)

BMC public health

Authors: Lopez-Veneros, David; Caceres, Billy A.; Jackman, Kasey; Belloir, Joseph A.; Sharma, Yashika; Bakken, Suzanne; Ensari, Ipek

Abstract

Background: Sexual and gender minority (SGM) adults experience significant health disparities linked to chronic exposure to minority stressors (e.g., discrimination), and could be reciprocally associated with physical activity (PA) behavior. While PA is a health-protective factor, research on PA patterns in SGM adults is limited. Identifying potential latent PA profiles can inform tailored behavior change approaches. Objective: To investigate latent profiles (i.e., clusters) of daily PA trajectories among sexual and gender minority (SGM; lesbian, gay, bisexual, transgender, queer) adults using functional latent block models (FLBMs), a co-clustering technique that simultaneously accounts for variation at the individual- and day-level. Study sample: The study included 42 Black and Latinx SGM adults who wore Fitbit trackers for up to 30 days of PA data collection as a part of a sleep health study, yielding 1,209 person-level days of step count data. Methods: Each 24-h period of step counts was smoothed using Fourier-transform to create the functional data matrix and fit the FLBMs. The optimal number of clusters was determined using the integrated completed likelihood (ICL) criterion. Results: The best-fitting model identified 3 individual-level clusters (K) based on the daily step count patterns (ICL = -88,495.88). Low activity cluster (n = 11) was characterized with the lowest overall PA, slightly later bedtimes, and the least intra-day and hourly variability. Steady moderate activity cluster (n = 23) was characterized by a gradual increase in step counts that spread over the course of the day, with a small peak in the afternoon. Fluctuating high activity cluster was characterized by a peak in activity earlier in the day, compared to other clusters. Cluster 3 membership was also associated with the highest volume of PA overall, along with hourly and daily variability in step counts and higher intensities of PA. The model secondarily identified 2 day-level clusters (L), representing weekday and weekend PA patterns. Conclusions: We identified distinct habitual daily PA trajectories among SGM adults based on daily volume and variability. Analyzing individual PA variances can help identify inactive periods and individuals at higher risk, which can inform the design of tailored interventions and self-management strategies to promote PA.

Characterization of Post-Viral Infection Behaviors Among Patients With Long COVID: Prospective, Observational, Longitudinal Cohort Analyses of Fitbit Data and Patient-Reported Outcomes (2025)

JMIR formative research

Authors: Zhang, Tianmai M.; Sharp, Sydney P.; Scott, John D.; Taren, Douglas; Samaniego, Jane C.; Unger, Elizabeth R.; Bertolli, Jeanne; Lin, Jin-Mann S.; Ramers, Christian B.; Godino, Job G.

Abstract

BACKGROUND: Long COVID encompasses a range of health problems that can be highly debilitating. While some research has relied on self-reported measures of symptoms and functioning, few studies have characterized symptoms in relation to behaviors and physiology measured objectively through wearable devices. OBJECTIVE: The primary aim of this study was to identify longitudinal patterns in physical activity, physiology, and patient-reported outcomes (PROs) among patients with long COVID at a Federally Qualified Health Center in the United States. The secondary aim was to identify meaningful subgroups or phenotypes within this cohort and examine how PROs and symptoms overlay with physical activity characteristics. METHODS: This was a prospective, observational, longitudinal cohort study recruiting a subset of low-income patients enrolled in the Long COVID and Fatiguing Illness Recovery Program. From March 2022 to May 2023, a total of 172 patients with long COVID or myalgic encephalomyelitis/chronic fatigue syndrome were given Fitbit Charge 5 (Fitbit Inc) devices and instructed to wear them continuously for up to a year. Patients completed PRO questionnaires (PROMIS-29 [Patient-Reported Outcomes Measurement Information System-29] and symptom questionnaires, etc) at baseline, 3, and 6 months. Inclusion in longitudinal analysis required at least 20 hours of valid wear data per day for a minimum of 7 days. The World Health Organization guideline on moderate to vigorous physical activity (MVPA) was used to differentiate MPVA-active and MVPA-inactive patients. Linear mixed effects regression was performed to assess longitudinal associations between physical activity levels and PROs. RESULTS: Among 172 patients, 80.2\% (n=138) were female, 75.6\% (n=130) were White, 45.3\% (n=78) were unemployed, and 94.8\% (n=163) had estimated annual income below US \$50,000. Of these patients, 82 (47.7\%) met valid wear criteria, providing 50.5 days of Fitbit data on average. At baseline, MVPA-inactive patients (n=41) reported statistically more severe problems regarding physical function, fatigue, and dyspnea than MVPA-active patients (n=41) on both continuous and categorical scales, with P{\textless}.05 from both Student t tests (2-tailed) and chi-squared tests. Longitudinal analysis found that MVPA-inactive patients showed a decreased ability to participate in social roles (estimated group difference=-4.21 T-score points over 3 months, 95\% CI -6.64 to -1.78, P{\textless}.001) and a higher intensity of sleep symptoms (estimated group difference=2.06 severity score points over 3 months, 95\% CI 0.40 to 3.71, P=.02) over time. CONCLUSIONS: This study showed that patients with long COVID could remain MVPA-active despite experiencing symptoms. These findings provide insights into the relationship between PROs, physical activity, and long COVID, which suggests the importance of considering individual activity profiles when tailoring treatment plans, especially in a low-income population. The findings of this study should be interpreted as hypothesis-generating, considering its exploratory nature and limitations, including high attrition rates and missing data.

Characterizing proximal risk for depressive symptoms and suicidal ideation with acute cannabis use and withdrawal among adolescents using ecological momentary assessment: Study protocol (2025)

PloS One

Authors: Feibus, Isabella; Mahiques, Marta Borrego; Costello, Meghan; Potter, Kevin; Bentley, Kate H.; Hoeppner, Bettina B.; Liu, Luwei; Evohr, Bryn; Yan, Lynn; Gilman, Jodi; Evins, A. Eden; Kossowsky, Joe; Schuster, Randi M.

Abstract

BACKGROUND: Heavy cannabis use often co-occurs with symptoms of depression in adolescents. Adolescents with past-year cannabis use are at increased risk of major depressive episodes and cannabis use is more than twice as common in adolescents with depression compared to those without. This study seeks to disentangle relationships between acute cannabis use, withdrawal, and abstinence on proximal depression and suicide risk using ecological momentary assessment (EMA) within the context of a randomized controlled trial comparing the effects of cannabis abstinence to cannabis use as usual. METHODS: This study will enroll 200 adolescents aged 12-18 who have daily or near-daily cannabis use and current depressive symptoms. Participants will complete 12 study visits over a 10-week period. At visit 2, participants will be randomized (1:1) to either 8 weeks of sustained cannabis abstinence encouraged through contingency management (CB-Abst) or a monitoring control group (CB-Mon). All participants will complete self-report and interview-based measures of substance use and symptom severity, along with 3 phases of EMA data collection (4 total weeks), involving 8 daily surveys that inquire about past-hour substance use, mood, and situational context. Phases will take place during baseline cannabis use, immediately after randomized abstinence, and following 8 weeks of sustained abstinence. The primary outcomes will be EMA-measured depressive symptoms and suicidal ideation across the 3 EMA phases, by randomized group. Exploratory outcomes will include Fitbit-derived measures of sleep, circadian rhythms, and step count. DISCUSSION: This is the first study, to our knowledge, to evaluate the acute effects of cannabis use, withdrawal, and sustained abstinence on mood among adolescents with heavy cannabis use and co-morbid symptoms of depression. Results will characterize periods of risk for fluctuations in mood and suicidal ideation across the withdrawal period and aim to guide intervention development to reduce depression and suicide risk among adolescents. TRIAL REGISTRATION: ClinicalTrials.gov NCT06576076.

Comparing the Accuracy of Different Wearable Activity Monitors in Patients With Lung Cancer and Providing Initial Recommendations: Protocol for a Pilot Validation Study (2025)

JMIR research protocols

Authors: Benzo, Roberto M.; Singh, Rujul; Presley, Carolyn J.; Tetrick, Macy K.; Chaplow, Zachary L.; Hery, Chloe M.; Yu, Jane; Washington, Peter; Penedo, Frank J.; Paskett, Electra D.; Lugade, Vipul; Fortune, Emma

Abstract

BACKGROUND: Wearable activity monitors (WAMs) provide insights into physical activity (PA) and are widely used in behavioral interventions and cancer survivorship research. However, validation studies of wearable devices in populations with cancer are scarce, and existing studies using activity monitors in patients with cancer lack standardization. This gap is particularly significant in patients with lung cancer (LC), who often experience unique mobility challenges and gait impairments that may affect device accuracy. This study addresses this gap by validating the Fitbit Charge 6, ActiGraph LEAP, and activPAL3 micro in patients with LC in both laboratory and free-living conditions and developing a standardized framework for assessing wearable devices in populations with cancer and impaired mobility. OBJECTIVE: This study aims to validate and compare the accuracy of consumer-grade (Fitbit Charge 6) and research-grade (activPAL3 micro and ActiGraph LEAP) WAMs in patients with LC under both laboratory and free-living conditions. Moreover, this protocol aims to establish standardized procedures that can be adapted for validating current and future generations of wearable devices while accounting for disease-specific factors that may impact measurement accuracy. METHODS: In total, 15 adults diagnosed with LC (stages 1-4) will participate in laboratory and free-living protocols, wearing Fitbit Charge 6, activPAL3 micro, and ActiGraph LEAP devices simultaneously. The laboratory protocol will consist of a series of structured activities, including variable-time walking trials, sitting and standing tests, posture changes, and gait speed assessments. Activities will be video recorded for validation. In the free-living protocol, participants will wear the devices continuously for 7 days except during water-based activities. WAM-based outcome measures will include step count; time spent at light, moderate, and vigorous PA intensity levels; posture; and posture changes (only the activPAL3 micro measured posture). Validated survey instruments will be administered both before and after WAM data collection to control for potential confounding factors that may influence movement patterns and device accuracy. Laboratory-based validity measures will compare WAM data to video-recorded observations. Sensitivity, specificity, positive predictive value, and agreement will also be determined. Free-living agreement between devices will be assessed using Bland-Altman plots, intraclass correlation analysis, and 95\% limits of agreement. RESULTS: Data collection is ongoing, with 11 participants enrolled and 7 (64\%) having completed both in-laboratory and free-living protocols. On average, enrolled participants are aged 63.0 (SD 7.8; range 50.0-73.0) years, with 8 (73\%) participants being women. Participant enrollment is expected to conclude in mid-2025, and initial findings are expected to be disseminated by the end of 2025. CONCLUSIONS: This is the first study that validates WAM accuracy for populations with LC while providing comprehensive recommendations for future validation studies. This study will provide critical insights into the accuracy and reliability of WAMs for assessing PA in LC survivors, which are essential for interpreting clinical research and informing future interventions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/70472.

Concurrent Validity of a Physical Activity Vital Sign Used in an Adult Preventive Cardiology Clinic (2025)

Nursing Research

Authors: McCarthy, Margaret; Fletcher, Jason; Melkus, Gail; Vorderstrasse, Allison; Chehade, Mireille; Katz, Stuart

Abstract

BACKGROUND: In clinical settings, counseling patients on physical activity starts by assessing patients' current physical activity levels. Self-report measures of PA are generally easy to administer; however, they may be too long to be convenient and are known to correlate poorly with objective measures of physical activity. OBJECTIVE: To assess the concurrent validity of a self-report three-question physical activity vital sign with objective Fitbit step counts and the distance walked during a 6-min walk test. METHODS: This pilot study tested a best practice advisory embedded in the Epic electronic health record, which was designed to prompt providers in a preventive cardiology clinic to counsel patients reporting low levels of physical activity . Patients were invited to participate in the remote patient monitoring phase to assess the change in their physical activity by wearing a Fitbit for 12 weeks and completing a 6-min walk test at baseline and 12 weeks. This analysis used the cross-sectional data collected in this phase. Pearson correlations were conducted between self-reported physical activity, Fitbit step counts, and the distance walked during the 6-min walk-a measure associated with current physical activity levels. Kappa coefficients were calculated to assess agreement between the self-reported physical activity and step counts. RESULTS: Participants who enrolled in the Fitbit monitoring were approximately 50\% female, with the majority identified as White non-Hispanic adults. Their most common cardiovascular risk factor was hypertension. The self-reported physical activity vital signs were significantly associated with step counts at baseline and 12 weeks but were not associated with the distance during the 6-min walk test. However, the distance walked was significantly associated with step counts at baseline and 12 weeks. The Kappa results demonstrate a poor level of agreement between two categories (meeting or not meeting current physical activity guidelines) of self-report physical activity vitals and the objective Fitbit step counts. DISCUSSION: There were moderate correlations between the self-reported physical activity vital signs and the Fitbit step counts, but there was lack of agreement when they were categorized. Further validation of this physical activity vital sign is warranted.

Contexts, affective and physical states and their variations during physical activity in older adults: an intensive longitudinal study with sensor-triggered event-based ecological momentary assessments (2025)

The International Journal of Behavioral Nutrition and Physical Activity

Authors: Delobelle, Julie; Compernolle, Sofie; Vetrovsky, Tomas; Van Cauwenberg, Jelle; Van Dyck, Delfien

Abstract

BACKGROUND: To design effective tailored interventions to promote physical activity (PA) among older adults, insights are needed into the contexts in which older adults engage in PA and their affective and physical experiences. Sensor-triggered event-based ecological momentary assessment (EMA) is an innovative method for capturing real-life contexts, as well as affective and physical states, during or immediately after specific events, such as PA. This study aimed to (1) describe the physical and social contexts, and the affective and physical states during PA among older adults, (2) evaluate how these constructs fluctuate during PA episodes, and (3) describe affective states during PA according to the context. METHODS: An intensive longitudinal sensor-triggered event-based EMA study was conducted with 92 Belgian older adults (65 + years). During seven days, participants were monitored using a Fitbit, which triggered a smartphone-based questionnaire on the event-based EMA platform 'HealthReact' after a five-minute walk. Participants reported on contexts and affective (positive/negative valence) and physical states (pain and fatigue) during the PA event. Descriptive statistics and generalized mixed models were used for data analysis. RESULTS: Older adults predominantly engaged in daily physical activities, such as walking for transport, leisure walking, and gardening, rather than structured exercise. They consistently reported high positive affect, low negative affect, and minimal physical complaints during PA. Furthermore, older adults mainly engage in physical activities alone, particularly in outdoor settings. Variations in contexts, affect, and fatigue were mostly driven by within-subject differences. The model showed significant differences across times of day, with negative affect being highest in the evening and fatigue lowest in the morning. Additionally, the physical and social context influenced negative affect (but not positive affect), with outdoor activities performed alone and indoor activities performed with others being associated with lower negative affect. CONCLUSIONS: While these findings could enhance the effectiveness of tailored PA interventions, it remains unclear whether the observed affective and physical states are causes or effects of PA, and whether the contexts in which the activities were performed align with older adults' preferences. Further research is needed to explore these relationships and to better understand older adults' preferred PA contexts.

Cross-evaluation of wearable data for use in Parkinson's disease research: a free-living observational study on Empatica E4, Fitbit Sense, and Oura (2025)

Biomedical Engineering Online

Authors: Reithe, Haakon; Marty, Brice; Torrado, Juan C.; Førsund, Elise; Husebo, Bettina S.; Erdal, Ane; Kverneng, Simon U.; Sheard, Erika; Tzoulis, Charalampos; Patrascu, Monica

Abstract

Background: Established assessment scales used for Parkinson's disease (PD) have several limitations in tracking symptom progression and fluctuation. Both research and commercial-grade wearables show potential in improving these assessments. However, it is not known whether pervasive and affordable devices can deliver reliable data, suitable for designing open-source unobtrusive around-the-clock assessments. Our aim is to investigate the usefulness of the research-grade wristband Empatica E4, commercial-grade smartwatch Fitbit Sense, and the Oura ring, for PD research. Method: The study included participants with PD (N = 15) and neurologically healthy controls (N = 16). Data were collected using established assessment scales (Movement Disorders Society Unified Parkinson's Disease Rating Scale, Montreal Cognitive Assessment, REM Sleep Behavior Disorder Screening Questionnaire, Hoehn and Yahr Stage), self-reported diary (activities, symptoms, sleep, medication times), and 2-week digital data from the three devices collected simultaneously. The analyses comprised three steps: preparation (device characteristics assessment, data extraction and preprocessing), processing (data structuring and visualization, cross-correlation analysis, diary comparison, uptime calculation), and evaluation (usability, availability, statistical analyses). Results: We found large variation in data characteristics and unsatisfactory cross-correlation. Due to output incongruences, only heart rate and movement could be assessed across devices. Empatica E4 and Fitbit Sense outperformed Oura in reflecting self-reported activities. Results show a weak output correlation and significant differences. The uptime was good, but Oura did not record heart rate and movement concomitantly. We also found variation in terms of access to raw data, sampling rate and level of device-native processing, ease of use, retrieval of data, and design. We graded the system usability of Fitbit Sense as good, Empatica E4 as poor, with Oura in the middle. Conclusions: In this study we identified a set of characteristics necessary for PD research: ease of handling, cleaning, data retrieval, access to raw data, score calculation transparency, long battery life, sufficient storage, higher sampling frequencies, software and hardware reliability, transparency. The three analyzed devices are not interchangeable and, based on data features, none were deemed optimal for PD research, but they all have the potential to provide suitable specifications in future iterations. Keywords: Cross-evaluation; Multi-modal sensing; Parkinson’s disease; Smart wearables; System usability; Wearable devices.

Daily Heart Rate per Step: A Wearables Metric Associated With Cardiovascular Disease in a Cross-Sectional Study of the All of Us Research Program (2025)

Journal of the American Heart Association

Authors: Chen, Zhanlin; Wang, Charles T.; Hu, Carolyn J.; Ward, Kendra; Kho, Abel; Webster, Gregory

Abstract

Background: Simple biometrics such as peak heart rate and exercise duration remain core predictors of cardiovascular disease (CVD). Commercial wearable devices track physical and cardiac electrical activity. Detailed, longitudinal data collection from wearables presents a valuable opportunity to identify new factors associated with CVD. Methods and results: This cross-sectional study analyzed 6947 participants in the Fitbit Bring-Your-Own-Device Project, a subset of the All of Us Research Program. The primary exposure daily heart rate per step (DHRPS) was defined as the average daily heart rate divided by steps per day. Our analysis correlated DHRPS with established CVD factors (type 2 diabetes, hypertension, stroke, heart failure, coronary atherosclerosis, myocardial infarction) as primary outcomes. We also performed a DHRPS-based phenome-wide association study on the spectrum of human disease traits for all 1789 disease codes across 17 disease categories. Secondary outcomes included maximum metabolic equivalents achieved on cardiovascular treadmill exercise stress testing. We examined 5.8 million person-days and 51 billion total steps of individual-level Fitbit data paired with electronic health record data. Elevated DHRPS was associated with type 2 diabetes (odds ratio [OR], 2.03 [95% CI, 1.70-2.42]), hypertension (OR, 1.63 [95% CI, 1.32-2.02]), heart failure (OR, 1.77 [95% CI, 1.00-3.14]), and coronary atherosclerosis (OR, 1.44 [95% CI, 1.14-1.82]), even after adjusting for daily heart rate (DHR) and step count. DHRPS also had stronger correlations with maximum metabolic equivalents achieved on exercise stress testing compared with steps per day (∆ρ=0.04, P<0.001) and heart rate (∆ρ=0.31, P<0.001). Lastly, DHRPS-based phenome-wide association study demonstrated stronger associations with CVD factors (P<1×10-55) compared with daily heart rate or step count. Conclusions: In the All of Us Research Program Fitbit Bring-Your-Own-Device Project, DHRPS was an easy-to-calculate wearables metric and was more strongly associated with cardiovascular fitness and CVD outcomes than DHR and step count. Keywords: biomarkers; cardiovascular disease; heart rate; physical activity; step count; wearables.

Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study (2025)

JMIR medical informatics

Authors: Kim, Jeong-Kyun; Mun, Sujeong; Lee, Siwoo

Abstract

Background: Wearable devices are increasingly used for monitoring health and detecting digital biomarkers related to chronic diseases such as metabolic syndrome (MetS). Although circadian rhythm disturbances are known to contribute to MetS, few studies have explored wearable-derived circadian biomarkers for MetS identification. Objective: This study aimed to detect and analyze sleep and circadian rhythm biomarkers associated with MetS using step count and heart rate data from wearable devices and to identify the key biomarkers using explainable artificial intelligence (XAI). Methods: Data were analyzed from 272 participants in the Korean Medicine Daejeon Citizen Cohort, collected between 2020 and 2023, including 88 participants with MetS and 184 without any MetS diagnostic criteria. Participants wore Fitbit Versa or Inspire 2 devices for at least 5 weekdays, providing minute-level heart rate, step count, and sleep data. A total of 26 indicators were derived, including sleep markers (midsleep time and total sleep time) and circadian rhythm markers (midline estimating statistic of rhythm, amplitude, interdaily stability, and relative amplitude). In addition, a novel circadian rhythm marker, continuous wavelet circadian rhythm energy (CCE), was proposed using continuous wavelet transform of heart rate signals. Statistical tests (t test and the Wilcoxon rank sum test) and machine learning models-Shapley Additive Explanations, explainable boosting machine, and tabular neural network-were applied to evaluate marker significance and importance. Results: Circadian rhythm markers, especially heart rate-based indicators, showed stronger associations with MetS than sleep markers. The newly proposed CCE demonstrated the highest importance for MetS identification across all XAI models, with significantly lower values observed in the MetS group (P<.001). Other heart rate-based markers, including relative amplitude and low activity period, were also identified as important contributors. Although sleep markers did not reach statistical significance, some were recognized as secondary predictors in XAI-based analyses. The CCE marker maintained a high predictive value even when adjusting for age, sex, and BMI. Conclusions: This study identified CCE and relative amplitude of heart rate as key circadian rhythm biomarkers for MetS monitoring, demonstrating their high importance across multiple XAI models. In contrast, traditional sleep markers showed limited significance, suggesting that circadian rhythm analysis may offer additional insights into MetS beyond sleep-related indicators. These findings highlight the potential of wearable-based circadian biomarkers for improving MetS assessment and management. Keywords: circadian rhythm; digital biomarker; explainable artificial intelligence; metabolic syndrome; wearable device.

Dialysis-Imposed Patterns of Nocturnal Sleep Duration: A Multi-Center Prospective Study in Patients Using a Wearable Activity Tracker (2025)

Kidney360

Authors: Han, Maggie; van der Sande, Frank M.; Kooman, Jeroen P.; Tao, Xia; Preciado, Priscila; Tisdale, Lela; Thwin, Ohnmar; Kotanko, Peter

Abstract

BACKGROUND: In patients on hemodialysis, the effects of determinants of sleep duration are not widely studied. Using wearable activity trackers, we aimed to characterize natural and hemodialysis-imposed temporal patterns of nocturnal sleep. METHODS: In this yearlong prospective observational study, patients on in-center hemodialysis were equipped with activity trackers (Fitbit® Charge 2™). Nocturnal sleep duration was assessed according to dialysis start time (early starters: before 8 a.m., late starters: others), dialysis versus interdialytic days (post-dialysis day and 2nd interdialytic day), weekdays, and seasons. Clinical, laboratory, and hemodialysis treatment data were extracted from electronic medical records. Linear mixed-effects models were constructed to determine the effect of various time patterns and predictors of nocturnal sleep duration. RESULTS: 109 patients contributed data (age 54±12 years, 73\% males, 23\% diabetic). Sleep duration was 276±91 minutes; 102 (94\%) patients slept on average less than the recommended 420 minutes per night. On dialysis days, participants slept 55 (95\% CI [51,59]) and 48 (95\% CI [43,54]) minutes less compared to post-dialysis and 2nd interdialytic days, respectively. Early starters slept on average 40 (95\% CI [6,74]) minutes less compared to late starters. On dialysis days, early starters slept 86 (95\% CI [55,118]) minutes less compared to late starters. We observed greater sleep-wake disturbance in early starters. Irrespective of dialysis schedule, patients slept on average 26 (95\% CI [19,33]) to 32 (95\% CI [24,40]) minutes longer on Sunday. In winter, sleep was 7 (95\% CI [1,13]) to 10 (95\% CI [5,16]) minutes shorter. In multivariate analysis, higher blood pressure and higher serum creatinine were significantly associated with shorter sleep duration. CONCLUSIONS: On average, patients on hemodialysis slept less than the recommended amount of time. The timing of hemodialysis treatment has pronounced effects on sleep duration and could be considered in patient care.

Digital Health Intervention to Reduce Malnutrition Among Individuals With Gastrointestinal Cancer Receiving Cytoreductive Surgery Combined With Hyperthermic Intraperitoneal Chemotherapy: Feasibility, Acceptability, and Usability Trial (2025)

JMIR cancer

Authors: Lin, Yu Chen; Hagen, Ryan; Powers, Benjamin D.; Dineen, Sean P.; Milano, Jeanine; Hume, Emma; Sprow, Olivia; Diaz-Carraway, Sophia; Permuth, Jennifer B.; Deneve, Jeremiah; Alishahi Tabriz, Amir; Turner, Kea

Abstract

BACKGROUND: Cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC) can improve survival outcomes for individuals with gastrointestinal (GI) cancer and peritoneal disease (PD). Individuals with GI cancer and PD receiving CRS-HIPEC are at increased risk for malnutrition. Despite the increased risk for malnutrition, there has been limited study of nutritional interventions for individuals receiving CRS-HIPEC. OBJECTIVE: We aimed to test the feasibility, acceptability, and usability of Support Through Remote Observation and Nutrition Guidance (STRONG), a multilevel digital health intervention to improve nutritional management among individuals with GI cancer and PD receiving CRS-HIPEC. We also assessed patient-reported outcomes, including malnutrition risk, health-related quality of life, and weight-related measures. METHODS: STRONG is a 12-week digital intervention in which participants received biweekly nutritional counseling with a dietitian, logged food intake using a Fitbit tracker, and reported nutrition-related outcomes. Dietitians received access to a web-based dashboard and remotely monitored patients' reported food intake and nutrition-impact symptoms. Implementation outcomes were assessed against prespecified benchmarks consistent with benchmarks used in prior studies. Changes in patient-reported outcomes at baseline and follow-up were assessed using linear and ordered logistic regressions. RESULTS: Participants (N=10) had a median age of 57.5 (IQR 54-69) years. Feasibility benchmarks were achieved for recruitment (10/17, 59\% vs benchmark: 50\%), study assessment completion (9/10, 90\% vs benchmark: 60\%), dietitian appointment attendance (7/10, 70\% vs benchmark: 60\%), daily food intake logging adherence (6/10, 60\% vs benchmark: 60\%), and participant retention (10/10, 100\% vs benchmark: 60\%). Most participants rated the intervention as acceptable (8/10, 80\% vs benchmark: 70\%) and reported a high level of usability for dietitian services (10/10, 100\%). The benchmark usability for the Fitbit tracker to log food intake was not met. Compared to baseline, participants saw on average a 6.0 point reduction in malnutrition risk score (P=.01), a 20.5 point improvement in general health-related quality of life score (P=.002), and a 5.6 percentage point increase in 1-month weight change (P=.04) at the end of the study. CONCLUSIONS: The STRONG intervention demonstrated to be feasible, acceptable, and usable among individuals with GI cancer and PD receiving CRS-HIPEC. A fully powered randomized controlled trial is needed to test the effectiveness of STRONG for reducing malnutrition and improving patient outcomes.

Digital, Personalized Clinical Trials Among Older Adults, Lessons Learned From the COVID-19 Pandemic, and Directions for the Future: Aggregated Feasibility Data From Three Trials Among Older Adults (2025)

Journal of Medical Internet Research

Authors: Arader, Lindsay; Miller, Danielle; Perrin, Alexandra; Vicari, Frank; Friel, Ciaran P.; Vrany, Elizabeth A.; Goodwin, Ashley M.; Butler, Mark

Abstract

BACKGROUND: The COVID-19 pandemic was extremely disruptive to clinical practice and research. Given older adults' increased likelihood of chronic health concerns, limited resources, and greater risk for adverse outcomes of COVID-19, access to research participation during this time was critical, particularly to interventions that may impact health conditions or behaviors. Fortunately, the implementation of personalized, digital research trials during the pandemic allowed for research and intervention delivery for older adults to continue remotely, resulting in feasibility findings that can benefit researchers, practitioners, and the broader older adult population. OBJECTIVE: This study discusses 3 digital, remote, and personalized intervention trials implemented during the pandemic to increase physical activity (2 trials) or to reduce back pain (1 trial). METHODS: We identified measures used for all 3 trials including Fitbit activity monitor use and self-reported participant satisfaction. Participant levels of Fitbit activity monitor use and satisfaction ratings of the digital trials were compared between younger (younger than 55 years) and older adults (older than 55 years). Differences between these cohorts were analyzed using chi-square tests for categorical outcomes and 2-tailed independent-sample t tests for continuous outcomes. RESULTS: Across the 3 trials, the majority of participants reported high satisfaction with the usability of the trials' digital systems including SMS text message interventions and surveys (≥62\% satisfied) and the use of wearable devices such as Fitbits (≥81\% satisfied). In addition, the use of the Fitbit device was shown to be feasible, as older adults across all trials wore their Fitbits for the majority of the day (mean 20.3, SD 3.6 hours). Furthermore, consistent Fitbit wear was common; 100\% of participants older than 55 years wore their Fitbit an average of 10 or more hours per day. These trials highlight that digital, remote intervention delivery may be successfully implemented among older adults by way of personalized trials. Across the 3 digital interventions, feasibility and acceptability were high among older adults, and comparable to younger adults. CONCLUSIONS: Given the success of the current trials amid pandemic restrictions, we argue that these trials serve as a useful framework to aid in designing personalized, digital, remote interventions in other areas of clinical care among older adults and in planning for future disruptions including new pandemics.

Dog Owners Exhibit Better Diet Quality but Similar Physical Activity Compared to Non-Owners: A Case-Control Study (2025)

Nutrients

Authors: Margaritis, Konstantinos Lazaridis; Perantonaki, Marilena; Pyrga, Katerina; Pardali, Eleni C.; Poulimeneas, Dimitrios; Goulis, Dimitrios G.; Tsigga, Maria; Grammatikopoulou, Maria G.

Abstract

Introduction: "The dog is a man's best friend" and research has showed that this idea is extended beyond the degree of loyalty. Dog ownership has been linked to several positive health outcomes for the owner. The aim of the present cross-sectional case-control study was to assess differences in the physical activity level (PAL), body composition, quality of life (QoL), and diet quality and dietary knowledge between dog owners and non-owners. Methods: A total of 55 dog owners and an equal amount of non-dog owners (all aged between 18 and 60 years old) formed the case and control groups, respectively. Basic anthropometric measurements were performed, including body fat (BF) and diet, assessed with the Mediterranean Diet Score (MedDietScore) and the Eating Assessment Table (EAT). Physical activity was recorded for 3 consecutive days using activity monitors. QoL was evaluated using the brief version of the World Health Organization QoL (WHOQOL-BREF) tool. Results: The two groups demonstrated a similar PAL, but lower BF\% (p = 0.009), hip circumference (p {\textless} 0.001), triceps (p = 0.012), and subscapular skinfolds (p = 0.003) were recorded among dog owners. The EAT score was greater among dog owners (p = 0.0023), indicating improved dietary intake and knowledge, even after adjustment for education attained and BMI (p = 0.026). On the other hand, greater adherence to the Mediterranean diet was exhibited among those not having dogs (p = 0.018). Regarding dog measurements and their owners' anthropometry, dog neck circumference was negatively correlated to the owners' biceps and triceps skinfolds (r = -0.327, p = 0.016; r = -0.320, p = 0.018, respectively). Additionally, dog breed size was negatively correlated to the owners' triceps skinfold (r = -0.325, p = 0.015), sum of skinfolds (r = -0.311, p = 0.021), hip circumference (r = -0.341, p = 0.011), body fat (r = -0.357, p = 0.007), and fat mass index (r = -0.307, p = 0.023). Conclusions: Dog ownership is associated with improved body composition and smaller skinfold thickness at specific body sites, as well as with a more health-conscious lifestyle, including better diet quality and knowledge.

Ecological momentary assessment of physical and eating behaviours: The WEALTH feasibility and optimisation study with recommendations for large-scale data collection (2025)

PloS One

Authors: Janek, Michael; Kuhnova, Jitka; Cardon, Greet; Van Dyck, Delfien; Cimler, Richard; Elavsky, Steriani; Fezeu, Leopold K.; Oppert, Jean-Michel; Buck, Christoph; Hebestreit, Antje; Harrington, Janas; Sigcha, Luis; Van de Ven, Pepijn; Donnelly, Alan; Vetrovsky, Tomas; WEALTH consortium

Abstract

Ecological Momentary Assessment (EMA) enables the real-time capture of health-related behaviours, their situational contexts, and associated subjective experiences. This study aimed to evaluate the feasibility of an EMA targeting physical and eating behaviours, optimise its protocol, and provide recommendations for future large-scale EMA data collections. The study involved 52 participants (age 31±9 years, 56% females) from Czechia, France, Germany, and Ireland completing a 9-day free-living EMA protocol using the HealthReact platform connected to a Fitbit tracker. The EMA protocol included time-based (7/day), event-based (up to 10/day), and self-initiated surveys, each containing 8 to 17 items assessing physical and eating behaviours and related contextual factors such as affective states, location, and company. Qualitative insights were gathered from post-EMA feedback interviews. Compliance was low (median 49%), particularly for event-based surveys (median 34%), and declined over time. Many participants were unable or unwilling to complete surveys in certain contexts (e.g., when with family), faced interference with their daily schedules, and encountered occasional technical issues, suggesting the need for thorough initial training, an individualised protocol, and systematic compliance monitoring. The number of event-based surveys was less than desired for the study, with a median of 2.4/day for sedentary events, when 4 were targeted, and 0.9/day for walking events, when 3 were targeted. Conducting simulations using participants' Fitbit data allowed for optimising the triggering rules, achieving the desired median number of sedentary and walking surveys (3.9/day for both) in similar populations. Self-initiated reports of meals and drinks yielded more reports than those prompted in time-based and event-based EMA surveys, suggesting that self-initiated surveys might better reflect actual eating behaviours. This study highlights the importance of assessing feasibility and optimising EMA protocols to enhance subsequent compliance and data quality. Conducting pre-tests to refine protocols and procedures, including simulations using participants' activity data for optimal event-based triggering rules, is crucial for successful large-scale data collection in EMA studies of physical and eating behaviours.

Effect of Intraoperative Intravenous Infusion of Esketamine Combined with Dexmedetomidine on Postoperative Sleep Disturbance in Patients Undergoing Radical Mastectomy (2025)

Drug Design, Development and Therapy

Authors: Geng, Xingyu; Pu, Yutian; Hu, Ziwei; Zhang, Heling; Wang, Maosan; Fang, Can; Lv, Gaochao; Li, Wanting; Zhang, Xinyue; Fan, Xiaoxuan; Liu, Su; Chen, Xiuxia; Wu, Jingru

Abstract

Objective Postoperative sleep disturbance(POSD) is a problem in breast cancer patients after surgery. Little is known about the differences in the treatment of POSD with esketamine combined with dexmedetomidine under the same circumstances. We investigated the effects of intraoperative esketamine combined with intravenous dexmedetomidine on the incidence of POSD and postoperative sleep architecture. Methods A single-center, randomized, double-blind controlled trial was conducted. A total of 100 participants were randomly assigned to four groups: the esketamine group (Group E), the dexmedetomidine group (Group D), the esketamine combined with dexmedetomidine group (Group ED), and the control group (Group S) (n=25 each). The intervention drugs were continuously infused until the placement of the drainage tube. The primary outcome measure was the incidence of POSD, defined as an Athens Insomnia Scale (AIS) score {\textgreater}6 on at least one of the first three postoperative days. The secondary outcome measure was the duration of sleep structure, which was collected using the Fitbit Charge 2® smartwatch (Fitbit, Inc. San Francisco, California, USA). Results In the first three postoperative days, the incidence of POSD was similar across the four groups (P=0.947). However, on postoperative day 3 (POD3), there was a significant interaction between esketamine and dexmedetomidine (P=0.004). Further simple effect analysis revealed that, in the absence of esketamine, dexmedetomidine had a significant effect on POSD on POD3 (OR=0.196, [0.056–0.691]; P=0.019). In the absence of dexmedetomidine, esketamine had a significant effect on POSD on POD3 (OR=0.248, [0.074–0.833]; P=0.042). Dexmedetomidine reduced rapid eye movement (REM) sleep on postoperative day 1 (P=0.042). Esketamine reduced nighttime awakening time on POD1 (P=0.036) and POD3 (P=0.020). Conclusion Intraoperative infusion of esketamine combined with dexmedetomidine had no significant effect on POSD, but dexmedetomidine reduced REM sleep, and esketamine reduced the nocturnal awakening time.

URL

Effectiveness of an mHealth-based impact exercise program for bone health in postmenopausal women: a randomised controlled trial protocol (2025)

BMC public health

Authors: Sañudo, Borja; Reverte-Pagola, Gonzalo; Maher, Carol; Godino, Job; Carrasco, Luis; Oviedo, Miguel Ángel; Feria, Adrián; Sánchez-Trigo, Horacio; Gamboa, Hugo; Domingo-Molina, Raquel; Sánchez-Arteaga, Alejandro; Giráldez, Miguel Ángel; Martínez-Maestre, Mª Ángeles; Cepeda, Elena; Ladrón-de-Guevara, Carmen; Rangel, Carlos; Pecci, Javier; Farrahi, Vahid; Tejero, Sergio

Abstract

Background: Osteoporosis, a major global health concern, increases fracture risk due to reduced bone mineral density (BMD), particularly in postmenopausal women. Weight-bearing and high-impact exercises are recommended for bone health, yet accurately quantifying mechanical loading outside the laboratory remains a challenge. Without precise tools, it is difficult to assess whether individuals engage in sufficient osteogenic activity. Moreover, poor adherence to structured exercise programs limits their effectiveness. Mobile health (mHealth) technologies offer a promising solution by enabling real-time mechanical loading monitoring in free-living conditions and providing personalized feedback to improve adherence. This study evaluates the effectiveness of an individualized mHealth-based intervention in optimizing exercise adherence and promoting bone health in postmenopausal women through real-time quantification of mechanical loading. Methods: A single-blind randomized controlled trial (RCT) will include 120 postmenopausal women (≤ 10 years since menopause, < 150 min/week of moderate-to-vigorous physical activity). Participants will be randomly assigned (1:1) to an intervention group (mHealth-based impact exercise program) or a control group (usual care). The 9-month intervention will use wearable activity monitors (Fitbit Versa 3) to track step cadence, impact frequency, and intensity. Exercise targets include fast walking (≥ 100 steps/min), progressive jump training (≥ 3.9 G impact forces), and wrist wall strikes for radius bone adaptation. Primary outcomes include changes in BMD (DXA) at the lumbar spine, proximal femur, and distal radius. Secondary outcomes include bone geometry, and bone turnover markers (β-CTX, P1 NP). Functional mobility, muscle strength, physical activity levels, quality of life and adherence will also be assessed. Discussion: This study will provide insights into optimal mechanical loading for osteoporosis prevention and assess the feasibility of mHealth solutions for improving adherence to osteogenic exercise programs. Findings may inform future guidelines on digital health applications for musculoskeletal health.

Effectiveness of PEER Intervention on Older Adults' Physical Activity Time Series Using Smoothing Spline ANOVA (2025)

Mathematics (Basel, Switzerland)

Authors: Liu, Yi; Liu, Chang; Ni, Liqiang; Zhang, Wei; Chen, Chen; Lopez, Janet; Zheng, Hao; Thiamwong, Ladda; Xie, Rui

Abstract

Falls are a major cause of injury among older adults. The Physio-fEedback Exercise pRogram (PEER) combines physio-feedback, cognitive reframing, and guided exercises to reduce fall risk. However, its impact on physical activity (PA) over time is underexplored. Functional time-series analysis offers insight into behavior patterns and sustainability. This preliminary study assessed PEER's effectiveness in improving PA levels immediately and over time. A total of 64 community-dwelling older adults were cluster-randomized into PEER ( N = 33 ) or control groups ( N = 31 ) . Participants wore Fitbit trackers, generating time-series data on activity. The PEER group completed an 8-week program, while the control group received CDC fall prevention pamphlets. PA data were analyzed using smoothing spline analysis of variance (SSANOVA), chosen for its flexibility in modeling complex, non-linear relationships in time-series data and its ability to handle skewed distributions and repeated measures. Unlike traditional parametric models, SSANOVA decomposes temporal trends into interpretable components, capturing both smooth trends and abrupt changes, such as those occurring on group workout days. This capability ensures robust and nuanced analysis of intervention effects. Results showed PEER participants significantly increased evenly and had very active minutes and reduced sedentary behavior during the intervention. No significant effect was found for light active minutes. Specifically, during the intervention period, PEER participants engaged in an average of 6.7% fewer sedentary minutes per day, 13.8% additional fairly active minutes per day, and 2.8% additional very active minutes per day compared to the control group. While the reduction in sedentary minutes and increase in fairly active minutes were not statistically significant, the increase in very active minutes was significant. However, our functional time-series analysis revealed these improvements diminished over the 15-week follow-up, indicating challenges in maintaining PA. In conclusion, PEER boosts PA and reduces sedentary behavior short-term, but strategies are needed to sustain these benefits. In conclusion, PEER boosts PA and reduces sedentary behavior short-term, but strategies are needed to sustain these benefits. Public health policies should emphasize technology-driven fall risk assessments, community-based prevention programs, and initiatives that promote physical activity, home safety, and chronic condition management.

Engagement of African American Women With Fitness Trackers and Mobile Technology for Shared Physical Activity Goals: Mixed Methods Study (2025)

JMIR mHealth and uHealth

Authors: Sweeney, Allison; Simmons, Timothy; Nair, Anika; Decker, Lindsay

Abstract

BACKGROUND: While there is growing evidence demonstrating the usefulness of integrating social features within mobile health approaches, little research has explored how African American women use mobile platforms to facilitate physical activity within the context of a group-based physical activity intervention. OBJECTIVE: The primary aim of this study was to qualitatively describe how African American women used private group messaging boards on the Fitbit mobile app (eg, the type of social and motivational strategies) during a 10-week group-based physical activity intervention. The secondary aim of this study was to quantitatively test whether greater engagement on the Fitbit mobile app (number of posts per week) was associated with greater daily physical activity (ie, steps and total minutes of physical activity) across 10 weeks. METHODS: Data were collected from 54 African American women who participated in the Together Everyone Achieves More Physical Activity trial (mean age 51.57, SD 13.89 y). Participants completed weekly in-person group sessions, set group-based weekly physical activity goals, and used the Fitbit mobile app for ongoing group communication and support, including posting in a private group. This study used a QUAN-qual mixed methods design to describe how participants used the private group messaging boards on the Fitbit mobile app and to evaluate whether engagement on the Fitbit app was associated with greater physical activity (ie, steps and total minutes of physical activity) across the 10-week intervention. RESULTS: The mean number of posts per week ranged from 1.79 (SD 2.95) in week 1 to 1.11 (SD 2.49) in week 10, with a maximum of 5.06 (SD 7.62) posts in week 5. A thematic content analysis revealed that the private groups reflected numerous topics, including motivational strategies, cognitive strategies, group strategies, informal positive communication, and sharing pictures. The quantitative analyses revealed that participants who posted at least once per week engaged in more steps (P=.006) and total minutes of physical activity (P=.02). CONCLUSIONS: Participants engaged in ongoing social support, positive communication, and vicarious learning through the Fitbit app, suggesting several important directions for future research, including potential interpersonal mechanisms and best practices for enhancing social support and physical activity among African American women.

Enhancing Interpretable, Transparent, and Unobtrusive Detection of Acute Marijuana Intoxication in Natural Environments: Harnessing Smart Devices and Explainable AI to Empower Just-In-Time Adaptive Interventions: Longitudinal Observational Study (2025)

Jmir Ai

Authors: Bae, Sang Won; Chung, Tammy; Zhang, Tongze; Dey, Anind K.; Islam, Rahul

Abstract

Background: Acute marijuana intoxication can impair motor skills and cognitive functions such as attention and information processing. However, traditional tests, like blood, urine, and saliva, fail to accurately detect acute marijuana intoxication in real time. Objective: This study aims to explore whether integrating smartphone-based sensors with readily accessible wearable activity trackers, like Fitbit, can enhance the detection of acute marijuana intoxication in naturalistic settings. No previous research has investigated the effectiveness of passive sensing technologies for enhancing algorithm accuracy or enhancing the interpretability of digital phenotyping through explainable artificial intelligence in real-life scenarios. This approach aims to provide insights into how individuals interact with digital devices during algorithmic decision-making, particularly for detecting moderate to intensive marijuana intoxication in real-world contexts. Methods: Sensor data from smartphones and Fitbits, along with self-reported marijuana use, were collected from 33 young adults over a 30-day period using the experience sampling method. Participants rated their level of intoxication on a scale from 1 to 10 within 15 minutes of consuming marijuana and during 3 daily semirandom prompts. The ratings were categorized as not intoxicated (0), low (1-3), and moderate to intense intoxication (4-10). The study analyzed the performance of models using mobile phone data only, Fitbit data only, and a combination of both (MobiFit) in detecting acute marijuana intoxication. Results: The eXtreme Gradient Boosting Machine classifier showed that the MobiFit model, which combines mobile phone and wearable device data, achieved 99% accuracy (area under the curve=0.99; F1-score=0.85) in detecting acute marijuana intoxication in natural environments. The F1-score indicated significant improvements in sensitivity and specificity for the combined MobiFit model compared to using mobile or Fitbit data alone. Explainable artificial intelligence revealed that moderate to intense self-reported marijuana intoxication was associated with specific smartphone and Fitbit metrics, including elevated minimum heart rate, reduced macromovement, and increased noise energy around participants. Conclusions: This study demonstrates the potential of using smartphone sensors and wearable devices for interpretable, transparent, and unobtrusive monitoring of acute marijuana intoxication in daily life. Advanced algorithmic decision-making provides valuable insight into behavioral, physiological, and environmental factors that could support timely interventions to reduce marijuana-related harm. Future real-world applications of these algorithms should be evaluated in collaboration with clinical experts to enhance their practicality and effectiveness. Keywords: Fitbit; JITAI; XAI; XGBoost; algorithmic decision-making process; artificial intelligence; cannabis; data collection; decision support; digital phenotyping; eXtreme Gradient Boosting Machine classifier; experience sampling; explainable artificial intelligence; intoxication; just-in-time adaptive interventions; mHealth; machine learning; marijuana; passive sensing; smart devices; smartphone-based sensors; wearables.

Enhancing Physical Activity in Older Adults More Than 6 Months Post Total Hip or Knee Replacement Through Telerehabilitation: A Pilot Randomized Controlled Trial (2025)

Journal of Aging and Physical Activity

Authors: Takenaka, Hiroto; Ida, Kunio; Goto, Shin; Suzuki, Junya

Abstract

Background: Physical activity levels often remain suboptimal in older adults undergoing total hip replacement or total knee replacement after surgery, which can affect functional independence and quality of life. Purpose: To explore the feasibility and potential effects of a telerehabilitation delivery mode that combines activity tracking with remote physical therapist counseling on physical activity levels in older adults post total hip replacement or total knee replacement. Methods: The participants were randomly allocated to receive either a 12-week telerehabilitation program involving brief weekly telephone counseling from a physical therapist (n = 19) or a control group (n = 18). Activity trackers (Fitbit Sense) were used in both groups to objectively measure daily step counts, sedentary time (in minutes per day), low-intensity physical activity (in minutes per day), and moderate to vigorous physical activity (in minutes per day). These measures, along with physical function tests, were assessed at baseline and Weeks 12 and 24. The primary outcome was the change in physical activity levels across these parameters. Results: No adverse events were reported among the 37 participants. The telerehabilitation group demonstrated a significant increase in low-intensity physical activity at Weeks 12 and 24 compared with the control group (mean between-group difference: +30.9 min/day at 12 week and +29.0 min/day at 24 week; p = .04, effect size r = .33 at 12 week, r = .34 at 24 weeks). No significant differences emerged in step count, sedentary time, or moderate to vigorous physical activity. Conclusions: This pilot study showed telerehabilitation’s potential to promote active lifestyles in post total hip replacement or total knee replacement older adults, particularly for increasing low-intensity physical activity. Future research should develop more intensive programs to improve moderate to vigorous physical activity and physical functions.

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Evaluating Fitbits for Assessment of Physical Activity and Sleep in Pediatric Pain: Feasibility and Acceptability Pilot Study (2025)

JMIR formative research

Authors: Nestor, Bridget A.; Baumer, Andreas M.; Chimoff, Justin; Delecourt, Benoit; Koike, Camila; Tacugue, Nicole; Brusseau, Roland; Roy, Nathalie; Gaytan-Fuentes, Israel A.; Sethna, Navil; Wallace, Danielle; Kossowsky, Joe

Abstract

Background: Consumer-grade wearables, such as Fitbits, are a promising, cost-effective methodology for objectively assessing sleep and physical activity in youth with pain. Objective: This study investigated the acceptability and feasibility of implementing Fitbits for youth with acute and chronic pain in and out of hospital settings while maintaining data security and patient confidentiality. Methods: We investigated participant experience of Fitbit use over 3 to 4 weeks for a sample of youth with acute pain undergoing either orthopedic or cardiac surgical procedures (N=34, mean age 14.46, SD 3.70 years, 47.06% [n=36] female) and a sample of youth with chronic pain enrolled in an intensive interdisciplinary pain treatment program (N=28, mean age 15.00, SD 2.33 years, 82.14% [n=23] female). We assessed the acceptability of Fitbit use through survey items probing comfort (0=extremely uncomfortable to 10=extremely comfortable), perceived burdensomeness (0=not burdensome at all to 10=extremely burdensome), and open-ended issues or concerns. Feasibility was assessed by tracking the daily compliant wear of the Fitbit device, which was operationalized as more than 600 minutes of daily wear time. We tested for group differences in acceptability and feasibility between orthopedic and cardiac patients within the acute pain sample and between the acute pain and chronic pain samples. We created an automated data pipeline to ensure data security, patient confidentiality, and quality. Results: Acceptability findings revealed high levels of reported comfort (acute pain: mean 8.56, SD 1.43; chronic pain: mean 8.27, SD 1.69) and low levels of perceived burdensomeness (acute: mean 0.68, SD 1.17; chronic: mean 1.15, SD 1.38) related to Fitbit wearing in both samples. No significant differences in these acceptability outcomes emerged between orthopedic and cardiac patients or between the acute pain and chronic pain groups (P values>.10). Transient concerns of mild wrist irritation and sleep discomfort were occasionally reported across both samples (15.79% [n=9] of participants). Feasibility findings indicated high feasibility (acute: median compliance rate of 86.67%; chronic: median compliance rate of 96.65%) for the study duration in both samples. Mann-Whitney U tests indicated significantly higher median compliance rates per participant among orthopedic as compared with cardiac patients (U=146.5, P=.04) and significantly higher median compliance rates per participant among the chronic pain group as compared with the acute pain group (U=186, P<.001), including significantly higher median compliant days (U=162, P<.001) and study days (U=234.5, P<.001) per participant. Conclusions: These findings support the use of Fitbits as an acceptable and feasible method for collecting objective data on sleep and physical activity for youth experiencing pain. Findings also highlight the logistics of implementing consumer-grade wearable devices throughout all stages of the clinical research process. Keywords: Fitbit; acceptability; feasibility; pediatric; pediatric pain; physical activity; sleep; wearable devices; youth.

Evaluating the role of interpersonal support on daily physical activity across systems, contexts, and time among African American women: an ecological momentary assessment study (2025)

Annals of Behavioral Medicine

Authors: Sweeney, Allison M.; Prine, Halle; Yang, Chih-Hsiang; Wilson, Dawn K.; Forthofer, Melinda; Martin, Pamela

Abstract

Many studies have found that various aspects of the social environment, such as social support, promote greater physical activity among African American women. However, few studies have evaluated how these social factors vary across time, contexts, and relationships. This study examined the associations between various social factors and physical activity across an ongoing 10-week group-based physical activity program for African American women. We found that social support from both participants’ family and friends and their treatment groups varied and positively impacted their daily physical activity.Extensive research demonstrates the importance of the social environment for physical activity (PA) among African American (AA) women. Such studies rarely evaluate the simultaneous impact of interpersonal factors across multiple systems or fluctuations across time.This study used Ecological Momentary Assessment (EMA) within a group-based PA intervention to evaluate how interpersonal factors impacted daily PA.Data were collected from 45 AA women (Mage = 52.7 ± 14) in the Together Everyone Achieves More Physical Activity randomized controlled trial. Participants used a smartphone-based EMA application and received two daily prompts across three 7-day phases of the intervention period while simultaneously wearing a Fitbit. Participants answered questions about interpersonal factors within their intervention group (social support given and received, relatedness, collective efficacy, and group cohesion) and external social support.Participants engaged in greater steps on days with higher than usual external social support (relative to one’s usual level) (B = 535.25, P \<.001) and higher than usual social support given to others in the intervention group (B = 673.10, P = .003). Participants were more likely to engage in any moderate to vigorous PA (MVPA) on days with higher than usual social support received from the intervention group (OR = 1.59, P = .014) and engaged in greater overall MVPA on days with higher than usual external social support (B = 0.18, p \<.001).By evaluating within-person changes over time and with a systems-level focus, this study provides novel insights into the role of interpersonal support for promoting PA among AA women.

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Evening preference with evening-type rest-activity rhythm: a risk for poor quality of life (2025)

Health and Quality of Life Outcomes

Authors: Mun, Sujeong; Kim, Jeong-Kyun; Baek, Younghwa; Park, Kihyun; Lee, Siwoo

Abstract

BACKGROUND: Chronotype reflects an individual’s intrinsic preference for the timing of activity and rest; however, perceived circadian preference may differ from actual behavioral rhythms due to external demands. Both chronotype and rest–activity rhythm have been linked to adverse health outcomes, but their combined association with health-related quality of life (HRQoL) has been less explored. This study investigated how combinations of circadian preference and objectively measured rest–activity timing relate to HRQoL. METHODS: We analyzed data from the Korean Medicine Daejeon Citizen Cohort, including participants who wore a Fitbit for ≥ 7 consecutive days. Chronotype was determined from the Morningness–Eveningness Questionnaire score quintiles, and rest–activity rhythm type from quintiles of the 5-h lowest activity period (L5 start time). Participants in intermediate quintiles were excluded. Four chronotype–rhythm groups were defined: MM (morning preference/morning rhythm), ME (morning preference/evening rhythm), EM (evening preference/morning rhythm), and EE (evening preference/evening rhythm). HRQoL was assessed using the SF-12 Physical Component Summary (PCS) and Mental Component Summary (MCS), the EQ-5D index, and the EQ Visual Analog Scale (VAS). Multiple linear and logistic regression analyses were conducted, adjusting for sociodemographic, lifestyle, and circadian rhythm variables. RESULTS: In total, 458 adults were included in the analysis. Compared with the MM group, the EE group had significantly lower scores for PCS, MCS, EQ-5D index, and EQ VAS (all P {\textless} 0.05), which persisted after full adjustment. The EM group had lower MCS but no significant differences in other HRQoL measures. In SF-12 subscales, both EM and EE groups reported lower general health and vitality, while only the EE group had lower role-physical and role-emotional scores. In EQ-5D dimensions, the EE group was more likely to report moderate to extreme pain/discomfort. CONCLUSIONS: Evening preference combined with an evening-type rhythm was associated with consistently poor HRQoL across physical, mental, and health utility domains, independent of confounders including activity levels, circadian robustness, social jetlag, and variability in sleep onset timing. Alignment between preference and rhythm did not confer benefit in the context of eveningness and may be disadvantageous in morning-oriented societies. Future longitudinal studies should examine underlying mechanisms and potential intervention strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12955-025-02463-y.

Exploring the Psychological and Physiological Insights Through Digital Phenotyping by Analyzing the Discrepancies Between Subjective Insomnia Severity and Activity-Based Objective Sleep Measures: Observational Cohort Study (2025)

JMIR mental health

Authors: Yeom, Ji Won; Kim, Hyungju; Pack, Seung Pil; Lee, Heon-Jeong; Cheong, Taesu; Cho, Chul-Hyun

Abstract

BACKGROUND: Insomnia is a prevalent sleep disorder affecting millions worldwide, with significant impacts on daily functioning and quality of life. While traditionally assessed through subjective measures such as the Insomnia Severity Index (ISI), the advent of wearable technology has enabled continuous, objective sleep monitoring in natural environments. However, the relationship between subjective insomnia severity and objective sleep parameters remains unclear. OBJECTIVE: This study aims to (1) explore the relationship between subjective insomnia severity, as measured by ISI scores, and activity-based objective sleep parameters obtained through wearable devices; (2) determine whether subjective perceptions of insomnia align with objective measures of sleep; and (3) identify key psychological and physiological factors contributing to the severity of subjective insomnia complaints. METHODS: A total of 250 participants, including both individuals with and without insomnia aged 19-70 years, were recruited from March 2023 to November 2023. Participants were grouped based on ISI scores: no insomnia, mild, moderate, and severe insomnia. Data collection involved subjective assessments through self-reported questionnaires and objective measurements using wearable devices (Fitbit Inspire 3) that monitored sleep parameters, physical activity, and heart rate. The participants also used a smartphone app for ecological momentary assessment, recording daily alcohol consumption, caffeine intake, exercise, and stress. Statistical analyses were used to compare groups on subjective and objective measures. RESULTS: Results indicated no significant differences in general sleep structure (eg, total sleep time, rapid eye movement sleep time, and light sleep time) among the insomnia groups (mild, moderate, and severe) as classified by ISI scores (all P{\textgreater}.05). Interestingly, the no insomnia group had longer total awake times and lower sleep quality compared with the insomnia groups. Among the insomnia groups, no significant differences were observed regarding sleep structure (all P{\textgreater}.05), suggesting similar sleep patterns regardless of subjective insomnia severity. There were significant differences among the insomnia groups in stress levels, dysfunctional beliefs about sleep, and symptoms of restless leg syndrome (all P≤.001), with higher severity associated with higher scores in these factors. Contrary to expectations, no significant differences were observed in caffeine intake (P=.42) and alcohol consumption (P=.07) between the groups. CONCLUSIONS: The findings demonstrate a discrepancy between subjective perceptions of insomnia severity and activity-based objective sleep parameters, suggesting that factors beyond sleep duration and quality may contribute to subjective sleep complaints. Psychological factors, such as stress, dysfunctional sleep beliefs, and symptoms of restless legs syndrome, appear to play significant roles in the perception of insomnia severity. These results highlight the importance of considering both subjective and objective assessments in the evaluation and treatment of insomnia and suggest potential avenues for personalized treatment strategies that address both psychological and physiological aspects of sleep disturbances. TRIAL REGISTRATION: Clinical Research Information Service KCT0009175; https://cris.nih.go.kr/cris/search/detailSearch.do?seq=26133.

Feasibility and Cultural Adaptation of a Community-Engaged Physical Activity Intervention for Hispanic Older Adults: Pilot Study (2025)

JMIR Formative Research

Authors: Zlatar, Zvinka Z.; Greenwood-Hickman, Mikael Anne; Lujan, Lazaro N. Martinez; Cooper, Julie; Florez-Acevedo, Stefani; Marquez, David X.; Aceves, Rosa Gutierrez; Vargas, Andrea Paula; Rosenberg, Dori E.

Abstract

Background The adult Hispanic population of the United States faces an increased risk of dementia compared to non-Hispanic White adults. Physical activity (PA) can help reduce dementia risk, but culturally adapted interventions for Hispanic populations are lacking. Culturally adapted interventions are needed to increase uptake and adherence to brain health promotion strategies in the Hispanic community. Objective The De Pie y a Movernos intervention aims to reduce barriers to participation in clinical research by culturally adapting a remotely based PA intervention for middle-aged and older Hispanic adults and establish its feasibility and acceptability through a pre-post pilot study. Findings from the cultural adaptation process will inform a stage II PA randomized controlled trial. Methods The adaptation process followed Barrera and Castro’s 2006 cultural adaptation framework and included a literature review, translation of intervention materials, review by a Hispanic-comprised community advisory board and bilingual staff, and a pre-post pilot study (N=10) with subsequent focus groups to refine the intervention. The pilot intervention included the use of Fitbit activity trackers and 2 individualized goal-setting calls with a health coach over a period of 3 weeks. Feasibility and acceptability were assessed using both quantitative methods and qualitative focus groups. Primary quantitative outcomes included enrollment, recruitment, and completion rates, as well as acceptability (predetermined satisfaction survey scores ≥3). Focus groups were thematically coded to identify themes for participants’ opinions about several aspects of the intervention and explore key barriers and facilitators to PA engagement to improve the planned stage II trial. Results Ten Hispanic adults (age: mean 62.7, SD 5.3 years; education: mean 11.8, SD 3.8 years; n=9, 90\% female; n=9, 90\% Spanish-speaking) participated in the pre-post pilot, with a 100\% completion rate, 50\% enrollment rate, and a recruitment rate of 5 participants per month. Acceptability was high (mean score 4.6, SD 0.3; range 1‐5). Qualitative analyses indicated that participants had high satisfaction with the intervention. They expressed a preference for adding group-based activities and increased interaction with study staff. Key barriers to PA included lack of awareness about the benefits of PA, low self-efficacy, time constraints, health conditions, and weather, while facilitators included awareness of PA’s cognitive benefits, social support from family or friends, accountability, enjoyable activities, self-efficacy, and Fitbit use. Insights from participants and community advisory board recommendations led to modifications for the larger trial, such as incorporating group-based elements for those who want them and adding an option for teleconference coaching calls. Conclusions The cultural adaptation process was essential in refining the intervention to align with the preferences of older Hispanic adults, which resulted in a feasible and acceptable intervention. Findings will inform a planned stage II randomized controlled trial aimed at promoting PA and reducing dementia risk in older Hispanic adults.

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Feasibility of Data Collection Via Consumer-Grade Wearable Devices in Adolescent Student Athletes: Prospective Longitudinal Cohort Study (2025)

JMIR Formative Research

Authors: Ransom, Danielle; Tudor, Brant; Irani, Sarah; Rehman, Mohamed; Suskauer, Stacy; Mularoni, P. Patrick; Ahumada, Luis

Abstract

Background Recent advancements in sports medicine have been fueled by innovative technologies, particularly consumer-grade wearable devices like Fitbit, Apple Watch, and Garmin. These devices offer physiological and biomechanical data and hold promise for personalized, real-time, and remote assessment of athlete recovery. However, few studies have been conducted with these devices in adolescent student athletes. Objective The primary objective of this study was to assess the feasibility of integrating consumer-grade wearable technology into injury recovery monitoring of adolescent student athletes. Methods The study included 34 high school student athletes aged 14‐18 diagnosed with either concussion or orthopedic injury, enrolled within 10 days of injury. Participants were equipped with a Fitbit Sense for continuous monitoring of physiological markers, including cardiovascular metrics, physical activity levels, and sleep patterns. Data collection extended 4‐6 weeks beyond injury clearance, during which adherence rates were assessed at both hourly and daily intervals. Hourly adherence was defined as the proportion of participants with at least 1 recorded heart rate data point per hour, while daily adherence was defined as the proportion of participants with at least 1 recorded heart rate data point per 24-hour period. Results The study demonstrated high participant adherence to wearing the device. The orthopedic injury cohort exhibited a median adherence rate of 95\%, with individual rates ranging from 82\% to 100\%. Similarly, the concussion cohort demonstrated a median adherence rate of 93\%, with adherence rates spanning from 37\% to 100\%. Notably, the study encountered minimal issues related to device functionality, with only 1 participant necessitating a device replacement. Conclusions These findings demonstrate successful integration of wearable technology in data collection for adolescent student athletes recovering from sports-related injuries. However, it is important to consider current limitations, including factors that may influence data accuracy and precision. In conclusion, this feasibility study demonstrates the practicality of using consumer-grade wearable technology for the collection of physiological and biomechanical parameters in adolescent student athletes recovering from sport-related injuries. The high level of adherence highlights the potential applicability of consumer-grade wearable devices in this population. Study findings lay the foundation for future investigations with larger and more diverse cohorts to identify the utility of device metrics in identifying unique patterns of injury-specific recovery (ie, sport-related concussion). Consumer-grade wearable devices offer promise for optimizing assessment and management of injured athletes through wearable technology integration into standard clinical protocols.

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Feasibility trial of STRONG: A digital intervention to improve nutritional management for individuals with esophageal and gastroesophageal junction cancer (2025)

Contemporary Clinical Trials Communications

Authors: Lin, Yu Chen; Pimiento, Jose M.; Milano, Jeanine; Riccardi, Diane; Mckinnie, Nakesha; Hume, Emma; Sprow, Olivia; Diaz-Carraway, Sophia; Budnetz, Mara; Hagen, Ryan; Al-Jumayli, Mohammed; Pereira, Allan Lima; Sinnamon, Andrew J.; Somasundaram, Ashwin; Permuth, Jennifer B.; Tabriz, Amir Alishahi; Turner, Kea

Abstract

INTRODUCTION: Individuals with esophageal and gastroesophageal junction (GEJ) cancers are at especially high risk of malnutrition. However, most patients with malnutrition do not receive adequate nutritional support. We conducted a single-arm trial to test the implementation of Support Through Remote Observation and Nutrition Guidance (STRONG), a multilevel digital intervention to improve nutritional outcomes for patients with locally advanced esophageal and gastroesophageal junction cancer. METHODS: Participants received five nutritional counseling sessions with a dietitian, logged daily food intake through the Fitbit app, and completed five study assessments related to patient malnutrition, nutrition-related symptoms, and quality-of-life outcomes. We assessed the feasibility, acceptability, and usability of STRONG against a priori benchmarks. RESULTS: Participants (N = 17) had a median age of 68 years, and 71 \% were male. Feasibility benchmarks were met for participants completing the baseline assessment (94 \%), completing four out of five assessments (82 \%), and participant retention (85 \%). Among participants who only received an oral diet during the study period, adherence to dietetic appointments (89 \%) and food intake tracking (78 \%) were high. Participant recruitment rate (47 \%) was slightly below the benchmark (50 \%). All participants found the intervention to be acceptable. Usability of the intervention was high, with 69 \% and 92 \% of participants reporting high satisfaction with tracking food intake through the Fitbit and the dietitian-led nutrition counseling sessions, respectively. CONCLUSION: Our study demonstrated that STRONG could be implemented with high feasibility, acceptability, and usability for esophageal and GEJ cancer patients. Findings from this study can guide a future efficacy study to assess the impact of STRONG on patient outcomes. CLINICAL TRIAL REGISTRATION: The Support Through Remote Observation and Nutrition Guidance Program for Gastroesophageal Cancer Patients (STRONG-GEC) study was registered on clinicaltrials.gov (NCT05438940) in June 2022 prior to participant enrollment.

GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women (2025)

The International Journal of Behavioral Nutrition and Physical Activity

Authors: Yi, Li; Hart, Jaime E.; Wilt, Grete; Hu, Cindy R.; Jimenez, Marcia Pescador; Lin, Pi-I. Debby; Suel, Esra; Hystad, Perry; Hankey, Steve; Zhang, Wenwen; Chavarro, Jorge E.; Laden, Francine; James, Peter

Abstract

Background: Increasing evidence positively links greenspace and physical activity (PA). However, most studies use measures of greenspace, such as satellite-based vegetation indices around the residence, which fail to capture ground-level views and day-to-day dynamic exposures, potentially misclassifying greenspace and limiting policy relevance. Methods: We analyzed data from the US-based Nurses' Health Study 3 Mobile Health Substudy (2018-2020). Participants wore Fitbits™ and provided smartphone global positioning system (GPS) for four 7-day periods throughout the year. Street-view greenspace (%trees, %grass, %other greenspace [flowers/plants/fields]) were derived from 2019 street-view imagery using deep-learning algorithms at a 100-meter resolution and linked to 10-minute GPS observations. Average steps-per-minute for were calculated for each 10-minute period following each GPS observation. Generalized Additive Mixed Models examined associations of street-view greenspace exposure with PA, adjusting for individual and area-level covariates. We considered effect modification by region, season, neighborhood walkability and socioeconomic status (SES), temperature, and precipitation. Results: Our sample included 335 participants (meanage= 39.4 years, n = 304,394 observations). Mean steps-per-minute per 10-minutes were 6.9 (SD = 14.6). An IQR increase (18.7%) in street-view trees was associated with a 0.36 steps-per-minute decrease (95%CI: -0.71, -0.01). In addition, an IQR increase (10.6%) in grass exposure was associated with a 0.59 steps-per-minute decrease (95% CI: -0.79, -0.40); however, the association was non-linear and flattened out after the 75th percentile of street-view grass. Conversely, an IQR increase (1.2%) in other greenspace was associated with a 1.99 steps-per-minute increase (95%CI: 0.01, 3.97). Associations were stronger in the spring and in higher SES neighborhoods, and among residents of the Northeast. Conclusions: In this prospective cohort, momentary street-view exposure to trees and grass was inversely associated with PA, while exposure to other greenspace was positively associated. Future research should confirm these results in other populations and explore the mechanisms through which specific greenspace components influence PA. Keywords: Deep learning; Global positioning system; Greenspace; Machine learning; Mobile health; Nature; Physical activity; Street view image; Wearables.

Heat-Treated Limosilactobacillus fermentum PS150 Improves Sleep Quality with Severity-Dependent Benefits: A Randomized, Placebo-Controlled Trial (2025)

Nutrients

Authors: Lee, Mon-Chien; Chen, Chao-Yuan; Chen, Ching-Yun; Huang, Chi-Chang

Abstract

Background: Insomnia is prevalent and difficult to treat safely over the long term. Given the role of the microbiota-gut-brain axis in melatonin and hypothalamic-pituitary-adrenal (HPA) regulation, and preclinical evidence for Limosilactobacillus fermentum PS150, we evaluated whether a heat-treated formulation (HT-PS150) could improve sleep and modulate endocrine/circadian markers in adults with poor sleep. Methods: In a randomized, double-blind, placebo-controlled trial, 84 adults aged 20-60 years with PSQI ≥ 5 and ISI {\textless} 22 were assigned to receive either placebo or HT-PS150 for eight weeks. Outcomes included patient-reported sleep (PSQI, ISI), anxiety/depression (GAD-7, PHQ-9), quality of life (QLESQ-SF), gastrointestinal symptoms (VAS-GI), wrist actigraphy (Fitbit Inspire 3), and sleep-relevant biomarkers measured from urine, saliva, and/or blood samples (melatonin, cortisol, orexin, serotonin, GABA, and/or norepinephrine). Repeated measures were analyzed using generalized estimating equations. An exploratory proportional regulation analysis classified individual biomarker changes as up- or down-regulated and compared proportions between study arms. Per-protocol analyses required ≥80\% compliance. Results: Improvements in the primary outcomes, PSQI and ISI, were observed over time in both groups, while no significant group × time interactions were detected. In exploratory proportional analyses, a higher proportion of participants in the HT-PS150 group exhibited up-regulated nocturnal melatonin secretion and improved daytime plasma orexin levels, as well as a tendency toward greater reductions in nocturnal salivary cortisol compared with placebo. In subgroup analyses with higher baseline insomnia severity (ISI ≥ 8), HT-PS150 was associated with greater improvements in PSQI (notably sleep duration and efficiency) and reduction in anxiety (GAD-7) upon post hoc testing. Conclusions: Although group mean scores on sleep symptom scales did not differ significantly in the full cohort, HT-PS150 appeared to modulate sleep-wake regulation by enhancing nocturnal melatonin secretion, attenuating HPA-axis activity, and stabilizing wakefulness. Clinical benefits were most evident among participants with greater baseline symptom burden, suggesting potential utility in more symptomatic populations.

Identifying Optimal Wearable Devices for Monitoring Mobility in Hospitalized Older Adults: Feasibility, Acceptability, and Validity Study (2025)

JMIR Aging

Authors: Nascimento, Paulo; Kirkwood, Renata; Griffith, Lauren E.; Duong, Mylinh; Cooper, Cody; Hao, Yujiao; Zheng, Rong; Raza, Samir; Beauchamp, Marla

Abstract

Background Hospitalized, frail older adults have an increased risk of developing hospital-acquired disability associated with hospital practices of restricted physical activity and immobilization. The use of activity tracking wearable devices may allow identification and prevention of mobility decline, reducing hospital-acquired disability. Objective This study aimed to identify the optimal wearable device and wear location for monitoring mobility in older hospitalized patients. Specific objectives included (1) comparison of the feasibility and acceptability of ActiGraph wGT3X-BT (ActiGraph LLC), MOX1 (Maastricht Instruments), MetaMotionC (mBientLab), and Fitbit Versa (Google) for continuous mobility monitoring and (2) determination of the concurrent validity of the selected device for detecting body posture and step count. Methods Participants were recruited for this observational study in the acute medical care unit of an academic hospital in Hamilton, Ontario, Canada. Eligible patients were aged 60 years and older, able to undertake the mobility protocol, and had an anticipated length of stay greater than 4 days. The study was divided into 2 experiments. Experiment 1 evaluated the feasibility of 4 wearable devices and validated the derived data for body posture and step count. Experiment 2 involved a mobility assessment session and a 24-hour monitoring and feasibility period with the selected device from experiment 1. Results The ActiGraph wGT3X-BT emerged as the most feasible device, demonstrating superior usability, data acquisition, and management. The thigh-worn ActiGraph accurately detected sedentary behavior, while the ankle-worn device provided detailed information on step counts and body postures. Bland-Altman plots and intraclass correlation coefficients indicated that the ankle-worn ActiGraph showed excellent reliability for step counting, with minimal bias and narrow limits of agreement. Patients expressed a high willingness to wear a continuous mobility tracking device at the hospital and at home. Conclusions Thigh- and ankle-worn ActiGraph are optimal for assessing and monitoring mobility in older hospitalized patients. Challenges such as discomfort and device removal observed during the 24-hour monitoring period highlight areas for future studies. Overall, our findings support the integration of wearable technology in hospital settings to enhance mobility monitoring and early intervention strategies. Further research is warranted to evaluate the long-term use of wearable data for predicting health outcomes post hospitalization and informing clinical decision-making to promote early mobility.

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Improving Outcomes for Care Partners of Individuals With Traumatic Brain Injury: Results for a mHealth Randomized Control Trial of the CareQOL App (2025)

Archives of Physical Medicine and Rehabilitation

Authors: Carlozzi, Noelle E.; Troost, Jonathan P.; Sen, Srijan; Choi, Sung Won; Wu, Zhenke; Miner, Jennifer A.; Lombard, Wendy L.; Graves, Christopher; Sander, Angelle M.

Abstract

Objective: To test the efficacy of a randomized control trial low-touch mobile health intervention designed to promote care partner self-awareness and self-care. Design: This randomized controlled trial included a baseline assessment of self-report surveys of health-related quality of life (HRQOL), care partner-specific outcomes, and the functional/mental status of the person with traumatic brain injury (TBI), as well as a 6-month home monitoring period that included 3 daily questions about HRQOL, monthly assessments of 12 HRQOL domains, and the use of a Fitbit to continuously monitor physical activity and sleep. HRQOL surveys were repeated at 3 and 6 months post-home monitoring. Setting: Two academic medical centers. Participants: A total of 254 TBI care partners. Interventions: The CareQOL app, a mobile health app designed to promote care partner self-awareness (through self-monitoring) and self-care (through personalized self-care push notifications). Results: Care partners were randomly assigned to self-monitoring alone (n=128) or self-monitoring plus self-care push notifications (n=126). Although we neither saw improvements in HRQOL outcomes, nor in physical activity or sleep, we found that across all the different measures, approximately 1/3 of the participants showed clinically meaningful improvements, 1/3 stayed the same, and 1/3 got worse; care partners who reported engagement in the intervention were more likely to show improvements than those who were not engaged. There was preliminary support for factors that being male, caring for a person with posttraumatic stress symptoms, living in the same household as the person with TBI, being a spousal care partner, working, and being diagnosed with COVID-19 during the study were associated with increased risk for negative outcomes. Conclusions: Findings suggest that engagement with the app, even when it is confined to self-monitoring alone, is associated with small improvements in HRQOL. Keywords: Brain injuries; Caregivers; Health care; Mobile applications; Outcome assessment; Quality of life; Rehabilitation; Self-monitoring; Traumatic.

Inconclusive Single-Lead ECGs From Smart-Devices: Impact of Baseline ECG Anomalies (2025)

JACC. Clinical electrophysiology

Authors: Isenegger, Corinne; Mannhart, Diego; Weidlich, Simon; Brügger, Jonas; Serban, Teodor; Jordan, Fabian; Krisai, Philipp; Knecht, Sven; Schaerli, Nicolas; Subin, Behnam; Mosher, Luke; du Fay de Lavallaz, Jeanne; Schaer, Beat; Mahfoud, Felix; Kühne, Michael; Sticherling, Christian; Badertscher, Patrick

Abstract

BACKGROUND: Multiple smart devices can record single-lead electrocardiograms (SL-ECGs) with automated rhythm classification. The impact of pre-existing baseline ECG anomalies on the accuracy of automated rhythm classification remains largely unknown. OBJECTIVES: This study sought to compare the presence of predefined ECG anomalies and their impact on rhythm classification ability of 5 commercially available FDA and CE-marked wearable smart-devices. METHODS: This prospective study included consecutive patients undergoing electrophysiological procedures at a tertiary referral center. Each participant obtained a 12-lead ECG followed by SL-ECGs with 5 different smart devices (AliveCor KardiaMobile, Apple Watch 6, Fitbit Sense, Samsung Galaxy Watch 3, and Withings ScanWatch). Two independent cardiologists performed manual rhythm classification and assessed the following ECG anomalies: ventricular pacing, conduction delay, low voltage, artifacts, and premature atrial or ventricular complexes. RESULTS: A total of 256 participants were included (29\% female, mean age 66 years) generating 1,280 recorded SL-ECGs. Of these, 242 SL-ECGs (19\%) were classified as inconclusive by at least 1 smart device. The presence of any ECG anomaly was significantly higher in inconclusive vs conclusive SL-ECGs, with 74\% vs 42\%; P {\textless} 0.001. ORs with 95\% CIs for inconclusive classification by ECG anomaly were ventricular pacing 6.35 [3.84-10.61], conduction delay 2.42 [1.82-3.22], low voltage 2.37 [1.75-3.21], minor artifact 1.72 [1.17-2.51], major artifact 10.62 [6.78-16.99], premature atrial complex 2.23 [1.29-3.74], and premature ventricular complex 1.94 [1.29-2.89]. Notable differences were found between the assessed smart devices. CONCLUSIONS: Automated rhythm classification is highly susceptible to baseline ECG anomalies. This study provides insights into the most appropriate patient population for smart device-based arrhythmia monitoring and offers guidance for selecting the optimal smart device tailored to individual patient characteristics.

Integration of Wearables Into a Cardiac Rehabilitation Program and Its Impact on Physical Activity and Exercise Capacity in Older Patients With Cardiovascular Disease (2025)

Advances in Rehabilitation Science and Practice

Authors: Yagi, Eijiro; Matsumura, Koichiro; Uchigashima, Yuki; Shiroyama, Jun; Hase, Mitsuki; Nanba, Tomoya; Yamada, Nobuhiro; Funauchi, Yohei; Ueno, Masafumi; Togi, Kiyonori; Shirotani, Manabu; Nakazawa, Gaku

Abstract

BACKGROUND: Cardiac rehabilitation using mobile health is increasingly being described as effective in improving exercise habits and physical function. However, the effectiveness of combined mobile health and hospital-based cardiac rehabilitation in older patients with cardiovascular disease is unknown. OBJECTIVE: To investigate the effect of a wearable watch device combined with hospital-based cardiac rehabilitation in older patients with cardiovascular disease compared with those with usual care. METHODS: A randomized, controlled trial was conducted in patients with cardiovascular disease aged ⩾60 years who underwent hospital-based cardiac rehabilitation. The patients were randomized 1:1 in those with a wearable watch (Fitbit Versa 3) or usual care. During out-of-hospital cardiac rehabilitation, patients with a wearable watch were advised to check their heart rate with a wearable watch and to target their physical activity at the heart rate determined by cardiopulmonary exercise testing. The primary endpoint was a change in physical activity obtained from the International Physical Activity Questionnaire (metabolic equivalents [METs]-minute/week) between the 2 groups during 12 weeks. RESULTS: Among 39 patients (median age = 73 years, 82\% men), the change in physical activity was significantly greater in patients with a wearable watch than in those with usual care (median: 2073 [1155-4400] vs 148 [-1261-899] METs-minute/week; analysis of covariance; P {\textless} .001). In patients with a wearable watch, 6-minute walk distance, the peak oxygen uptake, peak METs, and anaerobic threshold were significantly improved, whereas no significant increase was observed in patients with usual care from baseline to 12 weeks. CONCLUSIONS: In older patients with cardiovascular disease, a wearable watch device combined with hospital-based cardiac rehabilitation increases physical activity and improves exercise capacity outside of hospital.

Interpretable framework for predicting preoperative cardiorespiratory fitness using wearable data (2025)

Computer Methods and Programs in Biomedicine

Authors: Hussain, Iqram; Zeepvat, Julianna; Reid, M. Cary; Czaja, Sara; Pryor, Kane O.; Boyer, Richard

Abstract

Objectives: Predicting preoperative cardiorespiratory fitness (CRF) is crucial for assessing the risk of complications and adverse outcomes in patients undergoing surgery. CRF is formally evaluated through submaximal exercise testing with cardiopulmonary exercise testing (CPET) or the 6-minute walk test (6MWT). However, formal CRF testing is impractical as a preoperative screening tool. Wrist-worn devices with actigraphy and heart rate monitoring have become increasingly capable of predicting physiological measurements. Our aim was to develop a clinically interpretable machine learning (ML) model using wearable-derived physiological data to predict CRF for older adults, and to access whether this model can accurately estimate the 6MWT distances for preoperative risk evaluation. Methods: We examined heart rate and activity data collected from Fitbit devices worn by older adults (N = 65) who were scheduled to undergo major noncardiac surgery. Data collection took place over a 1-week period prior to surgery while participants engaged in their typical daily activities. Our primary aim was to leverage this wearable technology to forecast CRF among this group. We employed a machine-learning ensemble regression model to predict CRF, using 6MWT outcomes as an index. Further, we applied the shapley feature attribution approach to gain insights into how specific features derived from wearable data contribute to CRF prediction within the model, aiding in personalized fitness prediction. Results: Adults with higher CRF exhibited elevated levels of moderate-to-vigorous physical activity (MVPA), maximal activity energy expenditure (aEEmax), heart rate recovery (HRR), and non-linear heart rate variability (HRV). These measures increased concurrently with improvements in 6MWT outcomes. Our regression models, employing random forest and linear regression techniques, demonstrated strong predictive capabilities, with coefficient of determination values of 0.91 and 0.81, respectively, for estimating CRF. The shapley feature attribution approach elucidated those greater levels of MVPA, aEEmax, HRR, and nonlinear dynamics of HRV serve as reliable indicators of enhanced CRF test performance. Conclusion: The integration of wearable data-driven activity and heart rate metrics forms the basis for utilizing wearables to provide preoperative cardiorespiratory fitness assessments, supporting surgical risk stratification, personalized prehabilitation, and improved patient outcomes. Keywords: Cardiorespiratory fitness; Interpretability; Machine-learning; Personalized medicine; Preoperative assessment; Wearables.

Leveraging Accelerometry and Heartrate Data from Consumer Wearables to Predict Physical Activity in Children: A Device Agnostic Approach (2025)

Medicine and Science in Sports and Exercise

Authors: Ghosal, Rahul; White, James W.; Finnegan, Olivia; Nelakuditi, Srihari; Brown, Trey; Pate, Russ; Welk, Greg; de Zambotti, Massimiliano; Wang, Yuan; Burkart, Sarah; Adams, Elizabeth L.; Armstrong, Bridget; Beets, Michael W.; Weaver, R. Glenn

Abstract

INTRODUCTION: This study examined the potential of a device agnostic approach for predicting physical activity energy expenditure (PAEE) from research grade and consumer wearable accelerometry and heartrate (HR) raw data compared to indirect calorimetry in children. METHODS: Two-hundred and thirty-one 5-12-year-olds (52.4\% male) of diverse skin tone and body weights participated in a 60-minute protocol with multiple activities at varying intensities. Children wore two of three consumer wearables (Apple Watch Series 7, Garmin Vivoactive 4S, Fitbit Sense) and a research grade accelerometer (ActiGraph GT9X) on their non-dominant wrist, and a chest-placed, research grade HR monitor (Actiheart 5, ECG), concurrently. Children also wore a K5 criterion measure of PAEE (i.e., COSMED K5). Cross-sectional time series (CSTS), generalized additive mixed effects model (GAMM) and random forest (RF) were used to estimate minute-by-minute PAEE from features extracted from raw accelerometry and HR data. Variance explained (R2), in addition to other metrics, evaluated agreement between estimated and criterion measurements. RESULTS: For the research grade devices (i.e., ActiGraph accelerometry and Actiheart HR) R2 was 0.74, 0.74, and 0.76 for CSTS, GAMM, and RF, respectively. For Apple R2 was 0.77, 0.76, and 0.78, Garmin's was 0.73, 0.73, and 0.75, and Fitbit's was 0.63, 0.65, and 0.67 for CSTS, GAMM, and RF, respectively. Across all other evaluation metrics, a similar pattern was observed with Fitbit performing the worst but with little variability between the modeling approaches or the other devices. CONCLUSIONS: Except for Fitbit, accelerometry and HR data from consumer wearables predicted PAEE comparably to research grade devices and there was little variability across modeling approach. These outcomes support deploying a consumer wearable device-agnostic approach for PAEE estimation in children.

mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED): statistical analysis plan (2025)

Trials

Authors: Vetrovsky, Tomas; Kral, Norbert; Pfeiferova, Marketa; Seifert, Bohumil; Capek, Vaclav; Jurkova, Katerina; Steffl, Michal; Cimler, Richard; Kuhnova, Jitka; Harris, Tess; Ussher, Michael; Wahlich, Charlotte; Malisova, Katerina; Pelclova, Jana; Dygryn, Jan; Elavsky, Steriani; Maes, Iris; Van Dyck, Delfien; Rowlands, Alex; Yates, Tom

Abstract

Background Type 2 diabetes and prediabetes represent significant global health challenges, with physical activity (PA) being essential for disease management and prevention. Despite the well-documented benefits, many individuals with (pre)diabetes remain insufficiently active. General practitioners (GP) provide an accessible platform for delivering interventions; however, integrating PA interventions into routine care is hindered by resource constraints. Objectives The ENERGISED trial aims to address these barriers through an innovative GP-initiated mHealth intervention combining wearable technology and just-in-time adaptive interventions. Methods The ENERGISED trial is a pragmatic, 12-month, multicentre, randomised controlled trial, assessing a GP-initiated mHealth intervention to increase PA and reduce sedentary behaviour in patients with type 2 diabetes and prediabetes. The primary outcome is daily step count, assessed via wrist-worn accelerometry. The primary analysis follows the intention-to-treat principle, using mixed models for repeated measures. Missing data will be handled under the missing-at-random assumption, with sensitivity analyses exploring robustness through reference-based multiple imputation. The trial incorporates the estimand framework to provide transparent and structured treatment effect estimation. Discussion This statistical analysis plan outlines a robust approach to addressing participant non-adherence, protocol violations, and missing data. By adopting the estimand framework and pre-specified sensitivity analyses, the plan ensures methodological rigour while enhancing the interpretability and applicability of results. Conclusions The ENERGISED trial leverages innovative mHealth strategies within primary care to promote PA in individuals with (pre)diabetes. The pre-specified statistical framework provides a comprehensive guide for analysing trial data and contributes to advancing best practices in behavioural intervention trials for public health. Trial registration ClinicalTrials.gov NCT05351359. Registered on April 28, 2022. Supplementary Information The online version contains supplementary material available at 10.1186/s13063-025-08865-z.

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mHealth-Based Diabetes Prevention Program for Chinese Mothers With Abdominal Obesity: Randomized Controlled Trial (2025)

JMIR mHealth and uHealth

Authors: Huang, Qinyuan; Zhong, Qinyi; Zeng, Yanjing; Li, Yimeng; Wiley, James; Wang, Man Ping; Chen, Jyu-Lin; Guo, Jia

Abstract

BACKGROUND: Among people with abdominal obesity, women are more likely to develop diabetes than men. Mobile health (mHealth)-based technologies provide the flexibility and resource-saving opportunities to improve lifestyles in an individualized way. However, mHealth-based diabetes prevention programs tailored for busy mothers with abdominal obesity have not been reported yet. OBJECTIVE: The aim of this study is to evaluate the feasibility and acceptability of an mHealth-based diabetes prevention program and its preliminary efficacy in reducing weight-related variables, behavioral variables, psychological variables, and diabetes risk among Chinese mothers with abdominal obesity over 6 months. METHODS: A randomized controlled trial was conducted at health management centers in 2 tertiary hospitals in Changsha, China. The mHealth group (n=40) received 12 weekly web-based lifestyle modification modules for diabetes prevention, 6 biweekly individualized health education messages based on their goal settings, and a Fitbit tracker. The control group (n=40) received 12 weekly web-based general health education modules, 6 biweekly general health education messages, and a Fitbit tracker. Data were collected at baseline, 3 months, and 6 months on the feasibility and acceptability outcomes, weight-related variables (waist circumference and BMI), diabetes risk scores, glycemic levels, behavioral variables (daily step count, active minutes, fruit and vegetable intake, calorie consumption, and sleep duration), and psychological variables (self-efficacy and social support for physical activity and diet, perceived stress, and quality of life). Generalized estimating equations were used for data analysis. RESULTS: Approximately 85\% (68/80) of the participants completed 6 months of follow-up assessments. Regarding the feasibility and acceptance of the program in the mHealth group, the average number of modules reviewed was 7.9 out of 12, and the satisfaction score was 4.37 out of 5. Significant improvements at 6 months between the intervention and control groups were found in waist circumference (β=-2.24, 95\% CI -4.12 to -0.36; P=.02), modifiable diabetes risk scores (β=-2.5, 95\% CI -4.57 to -0.44; P=.02), daily steps (β=1.67, 95\% CI 0.06-3.29; P=.04), self-efficacy for physical activity (β=1.93, 95\% CI 0.44-3.43; P=.01), social support for physical activity (β=2.27, 95\% CI 0.80-3.74; P=.002), and physical health satisfaction (β=0.82, 95\% CI 0.08-1.55; P=.03). No differences were found in BMI, total diabetes risk score, daily active minutes, daily intake of fruits and vegetables, sleep duration, daily calorie consumption, self-efficacy, and social support for diet (P{\textgreater}.05). CONCLUSIONS: This study addresses the potential role of tailored lifestyle interventions based on mHealth technology by offering tailored web-based health modules and health information in managing diabetes risk among mothers with abdominal obesity. The mHealth diabetes prevention program provides a flexible, customized, and resource-saving model for busy mothers. Future research could further explore the efficacy improvement on dietary behaviors to better serve the health care needs of this population. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2400090554; https://www.chictr.org.cn/showproj.html?proj=226411.

Monitoring Adolescent Sport-Related Concussion Recovery Using Consumer-Grade Wearables: A Pilot Study (2025)

The Journal of Head Trauma Rehabilitation

Authors: Ransom, Danielle M.; Tudor, Brant H.; Irani, Sarah A.; Rehman, Mohamed A.; Suskauer, Stacy J.; Svingos, Adrian M.; Ahumada, Luis M.; Mularoni, P. Patrick

Abstract

OBJECTIVE: To evaluate whether consumer-grade wearable devices (CGWDs) can detect physiological differences between adolescent athletes recovering from sport-related concussion (SRC) versus musculoskeletal (MSK) injury, and to examine whether wearable-derived physiological markers are associated with symptom burden during the acute post-injury phase. SETTING: Outpatient sports medicine clinic at a pediatric academic medical center. PARTICIPANTS: High school student-athletes aged 14-18 years were eligible if they presented within 10 days of SRC or acute, nonsurgical MSK injury and had internet access and willingness to comply with study procedures. Thirty-eight participants were enrolled; four were excluded due to protocol deviations. The final analytic sample included 34 participants (SRC: n = 17; MSK: n = 17). DESIGN: Prospective observational cohort study conducted from September 2021 to April 2022. All participants were issued a Fitbit Sense to passively monitor sleep, activity, and heart rate for up to 6 weeks post-injury. No randomization or blinding occurred, as this was an observational study. MAIN MEASURES: The primary outcome was group differences in CGWD-derived physiological metrics (sleep patterns and architecture, physical activity, heart rate) across 3 post-enrollment time intervals (Days 1-14, 15-28, 29-42). Secondary outcomes included correlations between physiological data and symptom burden based on the Post-Concussion Symptom Inventory, Second Edition (PCSI-2). RESULTS: Compared to MSK peers, participants with SRC showed significantly more light sleep, more nocturnal wake time, and lower daily step counts during the first 4 weeks post-injury (P {\textless}.0038). No significant differences were observed in REM sleep, deep sleep, or heart rate. In SRC participants, greater nocturnal wake time and lower resting heart rate were modestly associated with higher cognitive symptom ratings; emotional symptoms were modestly associated with step counts. No adverse events occurred. CONCLUSIONS: CGWDs may capture recovery-specific physiological disruptions in adolescent SRC, particularly in sleep and physical activity. These findings support the potential for wearable technology to inform individualized, objective approaches to concussion monitoring in clinical practice.

Multidomain postoperative recovery trajectories after lumbar and thoracolumbar spine surgery (2025)

The Spine Journal: Official Journal of the North American Spine Society

Authors: Yakdan, Salim; Zhang, Jingwen; Benedict, Braeden; Xu, Ziqi; Javeed, Saad; Zhang, Justin K.; Steel, Benjamin A.; Gupta, Vivek P.; Botterbush, Kathleen; Piccirillo, Jay F.; Rodebaugh, Thomas L.; Goodin, Burel R.; Buchowski, Jacob M.; Neuman, Brian; Hafez, Daniel; Kelly, Michael; Ray, Wilson Z.; Lu, Chenyang; Frumkin, Madelyn; Greenberg, Jacob K.

Abstract

BACKGROUND CONTEXT: Understanding early postoperative recovery is crucial for improving perioperative care and long-term outcomes. Traditional recovery assessments relying primarily on cross-sectional patient-reported measures may not fully capture the complexity of the recovery process. PURPOSE: Our study evaluates early postoperative recovery using mobile health assessment and explores the relationship between early recovery patterns, multidomain recovery, and long-term outcomes. STUDY DESIGN/SETTING: A prospective observational study. PATIENT SAMPLE: A total of 129 patients were included in the analysis. OUTCOME MEASURES: Patient-reported outcome measures (PROMs) of pain, physical function, and disability at 1, 6 and 12 months postoperatively. METHODS: This study recruited patients aged 21 to 85 undergoing lumbar/thoracolumbar surgery for degenerative diseases. During the first month postoperatively, patients completed daily Ecological Momentary Assessment (EMA) surveys assessing pain, depression, and physical function and were passively monitored with Fitbit. EMA and Fitbit data (steps per minute, Maximum 30-minute cadence, and activity bout number) were clustered using functional principal component analysis. RESULTS: 129 patients were included (median age: 62; 56\% female). Two dominant recovery patterns were identified across all domains. At 12 months, patients with more favorable recovery across all domains except for activity bout number and depression, showed better outcomes. Favorable recovery in pain intensity and steps per minute was associated with greater improvements in all outcomes, while favorable recovery in maximum 30-minute cadence was associated with greater improvement in disability and physical function. Patients with less favorable pain recovery had a significantly higher complication rate (23\% vs. 7\%). A greater number of favorable recovery domains was associated with better 12-month outcomes improvement and demonstrated superior prognostic value compared to traditional patient assessment methods. CONCLUSION: Early postoperative recovery patterns and multidomain recovery, captured using mHealth tools, provide valuable insights into long-term outcomes. With further validation, these findings highlight the potential of integrating mHealth into clinical practice to personalize rehabilitation strategies, improve resource allocation, and enhance patient care.

Optimization and pre-use suitability selection for wrist photoplethysmography-based heart rate monitoring in patients with cardiac disease (2025)

European Heart Journal. Digital Health

Authors: Vermunicht, Paulien; Buyck, Christophe; Naessens, Sebastiaan; Hens, Wendy; Verberckt, Caro; Van Craenenbroeck, Emeline; Laukens, Kris; Desteghe, Lien; Heidbuchel, Hein

Abstract

Introduction: Sensor placement, activity type influencing wrist movements, and individual characteristics impact accuracy of wrist-worn photoplethysmography (PPG)-based heart rate (HR) monitors. This study investigated technical interventions to optimize PPG accuracy in patients with cardiac disease. Methods and results: The Fitbit Inspire 2 PPG monitor was evaluated across three cohorts, using a Polar H10 chest strap as reference: (ⅰ) 10 healthy volunteers performed wrist movements with the monitor placed one or three fingers above the wrist to identify optimal placement; (ⅱ) 10 volunteers engaged in sport activities (walking, running, cycling, rowing); (ⅲ) 30 cardiac rehabilitation patients were monitored during exercise to assess baseline accuracy. Patients with low accuracy [mean absolute percentage error (MAPE) < 10% for <70% of training time] underwent technical interventions (sensor cleaning, forearm shaving, position fixation, and/or relocation to the volar wrist). Placement three vs. one fingers above the wrist was significantly more accurate (mean difference in MAPE: -11.4%, P < 0.001). Walking showed the highest accuracy (MAPE = 3.8%), followed by cycling (MAPE = 6.9%) and running (MAPE = 8.5%), while rowing had the lowest accuracy (MAPE = 13.4%, P < 0.001). Among CR patients, 66.7% achieved high baseline accuracy. Technical interventions improved accuracy in 50.0% of those with low baseline accuracy, but no significant predictors of optimization success were identified. Conclusion: Accurate PPG-based monitoring requires a sensor placed higher on the wrist. Nevertheless, only two-thirds of patients are suitable for such monitoring, with improvement by technical adaptations possible (but impractical) in the others. Therefore, assessing baseline accuracy is a prerequisite before relying on these devices for activity guidance.

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Patient-Centered mHealth Intervention to Improve Self-Care in Patients With Chronic Heart Failure: Phase 1 Randomized Controlled Trial (2025)

Journal of Medical Internet Research

Authors: Kitsiou, Spyros; Gerber, Ben S.; Buchholz, Susan W.; Kansal, Mayank M.; Sun, Jiehuan; Pressler, Susan J.

Abstract

BACKGROUND: Heart failure (HF) is one of the most common causes of hospital readmission in the United States. These hospitalizations are often driven by insufficient self-care. Commercial mobile health (mHealth) technologies, such as consumer-grade apps and wearable devices, offer opportunities for improving HF self-care, but their efficacy remains largely underexplored. OBJECTIVE: The objective of this study was to examine the feasibility, acceptability, safety, and preliminary efficacy of a patient-centered mHealth intervention (iCardia4HF) that integrates 3 consumer mHealth apps and devices (Heart Failure Health Storylines, Fitbit, and Withings) with a program of individually tailored SMS text messages to improve HF self-care. METHODS: We conducted a phase 1 randomized controlled trial. Eligible patients had stage C HF, were aged ≥40 years, and had New York Heart Association (NYHA) class I, II, or III HF. Patients were randomly assigned to either iCardia4HF plus usual care or to usual care only and were observed for 8 weeks. Key feasibility measures were recruitment and retention rates. The primary efficacy outcome was change in HF self-care subscale scores (maintenance, symptom perception, and self-care management) at 8 weeks, assessed with the Self-Care Heart Failure Index (SCHFI; version 7.2). Key secondary outcomes were modifiable behaviors targeted by the intervention (health beliefs, self-efficacy, and HF knowledge), health status, and adherence to daily self-monitoring of 2 core vital signs (body weight and blood pressure). RESULTS: A total of 27 patients were enrolled in the study and randomly assigned to iCardia4HF (n=13, 48\%) or usual care (n=14, 52\%). Of these 27 patients, 11 (41\%) in the intervention group (iCardia4HF) and 14 (52\%) in the usual care group started their assigned care and were included in the full analysis. Patients' mean age was 56 (SD 8.3) years, 44\% (11/25) were female, 92\% (23/25) self-reported race as Black, 76\% (19/25) had NYHA class II or III HF, and 60\% (15/25) had HF with reduced left ventricular ejection fraction. Participant retention, completion of study visits, and adherence to using the mHealth apps and devices for daily self-monitoring were high ({\textgreater}80\%). At 8 weeks, the mean group differences in changes in the SCHFI subscale scores favored the intervention over the control group: maintenance (Cohen d=0.19, 95\% CI -0.65 to 1.02), symptom perception (Cohen d=0.33, 95\% CI -0.51 to 1.17), and self-care management (Cohen d=0.25, 95\% CI -0.55 to 1.04). The greatest improvements in terms of effect size were observed in self-efficacy (Cohen d=0.68) and health beliefs about medication adherence (Cohen d=0.63) and self-monitoring adherence (Cohen d=0.94). There were no adverse events due to the intervention. CONCLUSIONS: iCardia4HF was found to be feasible, acceptable, and safe. A larger trial with a longer follow-up duration is warranted to examine its efficacy among patients with HF. TRIAL REGISTRATION: ClinicalTrials.gov NCT03642275; https://clinicaltrials.gov/study/NCT03642275.

Personalized Physician-Assisted Sleep Advice for Shift Workers: Algorithm Development and Validation Study (2025)

JMIR formative research

Authors: Shen, Yufei; Choto Olivier, Alicia; Yu, Han; Ito-Masui, Asami; Sakamoto, Ryota; Shimaoka, Motomu; Sano, Akane

Abstract

BACKGROUND: In the modern economy, shift work is prevalent in numerous occupations. However, it often disrupts workers' circadian rhythms and can result in shift work sleep disorder. Proper management of shift work sleep disorder involves comprehensive and patient-specific strategies, some of which are similar to cognitive behavioral therapy for insomnia. OBJECTIVE: Our goal was to develop and evaluate machine learning algorithms that predict physicians' sleep advice using wearable and survey data. We developed a web- and app-based system to provide individualized sleep and behavior advice based on cognitive behavioral therapy for insomnia for shift workers. METHODS: Data were collected for 5 weeks from shift workers (N=61) in the intensive care unit at 2 hospitals in Japan. The data comprised 3 modalities: Fitbit data, survey data, and sleep advice. After the first week of enrollment, physicians reviewed Fitbit and survey data to provide sleep advice and selected 1 to 5 messages from a list of 23 options. We handcrafted physiological and behavioral features from the raw data and identified clusters of participants with similar characteristics using hierarchical clustering. We explored 3 models (random forest, light gradient-boosting machine, and CatBoost) and 3 data-balancing approaches (no balancing, random oversampling, and synthetic minority oversampling technique) to predict selections for the 7 most frequent advice messages related to bedroom brightness, smartphone use, and nap and sleep duration. We tested our predictions under participant-dependent and participant-independent settings and analyzed the most important features for prediction using permutation importance and Shapley additive explanations. RESULTS: We found that the clusters were distinguished by work shifts and behavioral patterns. For example, one cluster had days with low sleep duration and the lowest sleep quality when there was a day shift on the day before and a midnight shift on the current day. Our advice prediction models achieved a higher area under the precision-recall curve than the baseline in all settings. The performance differences were statistically significant (P{\textless}.001 for 13 tests and P=.003 for 1 test). Sensitivity ranged from 0.50 to 1.00, and specificity varied between 0.44 and 0.93 across all advice messages and dataset split settings. Feature importance analysis of our models found several important features that matched the corresponding advice messages sent. For instance, for message 7 (darken the bedroom when you go to bed), the models primarily examined the average brightness of the sleep environment to make predictions. CONCLUSIONS: Although our current system requires physician input, an accurate machine learning algorithm shows promise for automatic advice without compromising the trustworthiness of the selected recommendations. Despite its decent performance, the algorithm is currently limited to the 7 most popular messages. Further studies are needed to enable predictions for less frequent advice labels.

Pilot Study on the Effect of Cannabidiol-Coated Fabric for Pillow Covers Improves the Sleep Quality of Shift Nurses (2025)

Healthcare (Basel, Switzerland)

Authors: Afzal, Mashita; Huang, Chieh-Liang; Huang, Shih-Hao; Li, Chia-Ing; Liao, Wen-Chun; Yang, Juan-Cheng; Ma, Wen-Lung

Abstract

Background: Sleep difficulty is common in the current society. Poor sleep has a significant influence on health, social interactions and even mortality; therefore, maintaining good sleep is of prime importance. Cannabidiol (CBD), a cannabis-derived compound, is known for its medical significance with many positive effects in humans, including decreasing anxiety and improving sleep for those with sleep disorders. Objective: However, whether CBD skin absorption results in similar effects is unknown. Therefore, examining CBD-coated fabric as a pillow cover to improve sleep quality in duty shift nurses is the purpose of this paper. Methods: This study recruited 55 duty shift nurses as participants to evaluate sleep patterns and quality using the Pittsburgh Sleep Quality Index (PSQI) and a consumer-grade tracker (Fitbit Charge 3). Data were collected over three phases: a one-week baseline period, a two-week intervention period using a CBD-coated pillow cover and a one-week follow-up period, referred to as the post-intervention phase, during which the use of CBD-coated pillow cover was continued. Results: Of the 55 participants, 10 were men (18.2%) and 45 were women (81.8%). At baseline, all participants exhibited poor sleep quality (PSQI ≥ 5). However, after three weeks of using CBD-coated pillow covers, subjective sleep quality significantly improved, with 7.3% of participants achieving PSQI scores <5. Additionally, slight changes in sleep patterns were observed, with increases in both light sleep and deep sleep durations. Light sleep duration increased from a baseline of 196.21 ± 65.28 to 206.57 ± 59.15 min two weeks after intervention (p = 0.337). Similarly, deep sleep duration showed a modest increase from 61.97 ± 21.01 min to 64.35 ± 22.19 min (p = 0.288). Furthermore, a significant reduction in anxiety levels was reported (p < 0.005). Conclusions: Using a CBD-coated pillow cover was found to enhance sleep duration in healthy individuals experiencing poor sleep. Consequently, for adults struggling with sleep difficulties, incorporating a CBD-coated pillow cover may serve as an effective aid in improving sleep quality. Keywords: cannabidiol (CBD); non-rapid eye movement (NREM); nurses; pillowcase; sleep quality.

Predicting Incident Type 2 Diabetes Using Wearable Activity and Polygenic Risk: A Survival-Modeling Study in All of Us (2025)

The Journal of Clinical Endocrinology and Metabolism

Authors: Rahman, Md Hafizur; Arian, Ash; Konda, Sreenivas; McGuinn, Laura A.; Islam, Humayera; Chowdhury, Muhammad Ashique Haider; Shahriar, Mohammad Hasan; Rayna, Shahrin Emdad; Farzana, Shahla; Tasmin, Saira; Manna, Ridwana Maher; Haider, Mohammad Rifat; Ahsan, Habibul

Abstract

BACKGROUND: Evidence is limited on whether daily step counts are uniform across individuals or whether combining them with genetic risk improves prediction of type 2 diabetes (T2D), both essential for precision prevention. We aimed to assess whether objectively measured daily step count and Polygenic Risk Score (PRS) predict the incidence of T2D, and to evaluate the predictive performance of machine-learning models. METHODS: We conducted a prospective cohort study of 4,589 adults in the NIH All of Us Research Program with valid Fitbit step data and whole-genome-derived PRS, excluding individuals with T2D before or within a 180-day lead-in period. Incident T2D was defined by HbA1c ≥6.5\%, plasma glucose ≥126 mg/dL, or an All of Us T2D condition record. We evaluated Cox and machine-learning survival models. FINDINGS: Over a median of 2.92 years (15,340 person-years), 265 participants developed T2D (5.77\% cumulative incidence; 17.27 per 1,000 person-years). Risk-reducing thresholds were ∼7,000 steps/day (p{\textless}0.001) but differed by PRS group (∼7,800 high vs ∼5,800 low; p{\textless}0.001). Each additional 1,000 steps/day was associated with lower T2D risk (aHR 0.83, 95\% CI 0.79-0.88; p{\textless}0.005), whereas each 1-SD higher PRS was associated with higher T2D risk (aHR 2.62, 2.32-2.96; p{\textless}0.005). Adding steps to a clinical model increased the C-index from 0.748 to 0.774; adding PRS increased it to 0.867. Penalized Cox achieved the highest discrimination (C-index 0.859), followed by survival SVM (0.85) and classical Cox (0.846). Calibration was best with Random Survival Forests. INTERPRETATION: Step-count thresholds for reducing T2D risk varied across genetic risk groups, indicating that step counts do not confer uniform protection. Step counts and PRS provided independent, complementary predictive information, and their combination improved prediction of incident T2D.

Predicting Social Frailty in Older Adults Using Fitbit-Derived Circadian and Heart Rate Biomarkers: Cross-Sectional Study (2025)

JMIR formative research

Authors: Maekawa, Hiroki; Kume, Yu

Abstract

Background: Social frailty poses a potential risk even for relatively healthy older adults, necessitating development of early detection and prevention strategies. Recently, consumer-grade wearable devices have attracted attention due to their ability to continuously collect physiological and activity-related data. These data can potentially be used to calculate digital biomarkers for screening social frailty in older adults. Objective: The objective of this study was to explore digital biomarkers associated with social frailty using sensor data recorded via Fitbit devices and evaluate their relationship with health outcomes in older adults. Methods: This cross-sectional study was conducted in 102 community-dwelling older adults. Participants attending frailty prevention programs wore devices from the Fitbit Inspire series on their nondominant wrist for at least 7 consecutive days, during which step count and heart rate data were collected. Standardized questionnaires were used to assess physical functions, cognitive functions, and social frailty, and based on the scores, the participants were categorized into 3 groups: robust, social prefrailty, and social frailty. The sensor data were analyzed to calculate nonparametric and extended cosinor rhythm metrics, along with heart rate-related metrics. Results: The final sample included 86 participants who were categorized as robust (n=28, 33%), social prefrailty (n=39, 45%), and social frailty (n=19, 22%). The mean age of the participants was 77.14 (SD 5.70) years, and 91% (78/86) were women. Multinomial logistic regression analysis revealed that a step-based rhythm metric (intradaily coefficient of variation) was significantly associated with social frailty (odds ratio 1.05, 95% CI 1.01-1.11; P=.01). The heart rate metrics, including the delta resting heart rate and time of transition from rest to activity, showed significant associations with both social prefrailty (odds ratio 0.82, 95% CI 0.68-0.99; P=.04) and social frailty (odds ratio 0.69, 95% CI 0.50-0.95; P=.01). Specifically, delta resting heart rate, defined as the difference between the overall average heart rate and resting heart rate, exhibited significant negative associations with social prefrailty (odds ratio 0.82, 95% CI 0.68-0.97; P=.02) and social frailty (odds ratio 0.74, 95% CI 0.58-0.94; P=.02). Furthermore, analysis using a linear regression model revealed a significant association between the intradaily coefficient of variation and the word list memory score, a measure of cognitive decline (β=-0.04; P=.02). Conclusions: This study identified associations between novel rhythm and heart rate metrics calculated from the step count and heart rate recorded by Fitbit devices and social frailty. These findings suggest that consumer-grade wearable devices, which are low cost and accessible, hold promise as tools for evaluating social frailty and its risk factors through enabling the calculation of digital biomarkers. Future research should include larger sample sizes and focus on the clinical applications of these findings.

Real-Time and Long-Term Effects of Medical Marijuana on Older Adults: Protocol for the Study on Medical Marijuana and its Long-Term Effects (the SMILE study) Prospective Cohort (2025)

JMIR research protocols

Authors: Robinson, Kendall R.; Seeger, Stella D.; Nave, Lauren; Mejia, Marlin; Vander Meulen, Maria; Rashid, Ahmed; Mickle, Angela M.; Sibille, Kimberly; Li, Zhigang; Przkora, Rene; Schmidt, Siegfried; Lo, Margaret C.; Cook, Robert L.; Wang, Yan

Abstract

BACKGROUND: Older adults represent the fastest-growing group of medical marijuana (MM) users in the United States, with chronic pain being the most common reason for use. Despite this trend, scientific evidence remains limited regarding the short- and long-term effects of MM on critical health outcomes, including cognitive function, physical and mental health, and overall quality of life in this population. To better inform clinical practice and public policy, there is a clear need for more rigorous, longitudinal studies that examine the impact of real-world MM products over time. OBJECTIVE: The Study on Medical Marijuana and Its Long-Term Effects on Older Adults (SMILE) is a prospective cohort study that aims to 1) determine MM's short- and long-term effects on pain, physical, emotional, and cognitive functioning, and quality of life in older adults; and 2) identify MM product characteristics and patient subgroups associated with improved outcomes and side effects. METHODS: This study will recruit and follow 440 older adults (50 years or older, {\textasciitilde}50\% {\textgreater}65, {\textasciitilde}50\% male) with chronic pain for 12 months, as some initiate MM (MM group, n=330) and others do not (comparison group, n=110). Data collection included quarterly survey questionnaires (focusing longitudinal changes in cannabis use, pain, physical and emotional functioning, side effects, and quality of life); baseline and 12-month cognitive assessments, pain sensory tests, and blood/urine samples for cannabis use; and periodic smartphone- and Fitbit sensor-based measurements to capture detailed MM use patterns, real-time pain, mental health, and objective data on physical activity and sleep. Data will be analyzed using descriptive analyses, generalized linear mixed effects models, and generalized estimating equations models to assess differences in short- and long-term effects between the MM and comparison groups, and subgroups among those initiating MM treatment. RESULTS: Recruitment for the SMILE study began in July 2022 and all data collection is expected to be completed by 2026. As of October 2025, we enrolled 399 participants, with 277 in the MM group and 122 in the comparison group. Data analysis is currently underway, and results are expected to be published starting in 2027. CONCLUSIONS: With multisource data collected in real-time and over 12 months, our study will provide much-needed scientific evidence addressing: 1) whether MM can reduce pain and improve physical and emotional functioning in the short term among older adults; 2) whether effects of MM last for 12 months and demonstrate changes in quality of life or cognition; and 3) whether health benefits and consequences differ by MM product type and whether individual differences (e.g. sex, baseline pain phenotyping) moderate the relationship. Our findings will offer valuable insights for physicians and patients when considering MM as a treatment option, and will help guide more informed, individualized care decisions.

Relationship Between Activity Tracker Metrics and the Physical Activity Index and Their Association With Cardiometabolic Phenotypes, Subclinical Atherosclerosis, and Cardiac Remodeling: Cross-Sectional Study (2025)

JMIR mHealth and uHealth

Authors: Huang, Weiting; Wong, Mark Kei Fong; Loh, Enver De Wei; Koh, Tracy; Tan, Alex Weixian; Shen, Xiayan; Varli, Onur; Kong, Siew Ching; Chin, Calvin Woon Loong; Tan, Swee Yaw; Yap, Jonathan Jiunn Liang; Ng, Eddie Yin Kwee; Yeo, Khung Keong

Abstract

Background Consumer wearable technology quantifies physical activity; however, the association between these metrics and cardiometabolic health requires further elucidation. Objective This study identified latent factors derived from Fitbit heart rate metrics and their relationship with cross-sectional cardiovascular phenotypes. Methods This cross-sectional analysis included 457 participants from the SingHEART study, a multiethnic, population-based study of Asian individuals aged 21 to 69 years recruited in Singapore. Participants wore the Fitbit Charge HR for 7 days, and data on physical activity metrics, self-reported physical activity index (PAI), blood tests, coronary artery calcium scores, and cardiac magnetic resonance imaging were collected. Exploratory factor analysis identified latent factors from Fitbit metrics, and multivariate regression analysis assessed associations with blood and cardiovascular imaging phenotypes. Results Higher levels of self-reported PAI were significantly associated with a higher number of calories burned (P=.008), number of steps and floors climbed, distance, number of activity calories, and number of very active minutes (P{\textless}.001). However, there was no association between PAI and other Fitbit metrics. Using exploratory factor analysis, we identified three latent factors measured by Fitbit metrics: (1) elevated metabolic equivalents of task (METs; calories burned per day, minutes per day spent fairly active in 3-6 METs and very active in ≥6 METs, and activity calories), (2) total activity (steps per day, distance in kilometers per day, and number of floors per day), and (3) others, all with a Cronbach α of {\textgreater}0.7. Higher total activity was associated with increased high-density lipoprotein levels (β=0.06; P{\textless}.001), decreased triglyceride levels (β=−0.10; P=.006), and lower BMI (β=−0.63; P{\textless}.001) after adjustment for age, gender, systolic blood pressure, total cholesterol, and family history of heart disease. The interaction between total activity and elevated METs was associated with lower fasting glucose (β=−0.07; P=.004). Elevated METs were associated with higher log(coronary artery calcium+1) and higher BMI (P{\textless}.001). Total activity was significantly associated with higher indexed biventricular systolic (P=.01 for left and P=.006 for right) and diastolic volumes (P{\textless}.001) and higher indexed left ventricular mass (P=.005). Conclusions We identified 3 groups of wearable metrics with distinct characteristics. While total activity had a significant relationship with self-reported PAI, most metrics of elevated METs did not. Total activity had a consistent and favorable association with lipid and glucose profiles and a dose-dependent association with cardiac remodeling. Elevated METs alone did not appear to have a significant association with favorable cardiovascular profiles. This study suggests that the total activity metrics are robust and dependable when interpreting an individual’s activity levels, with construct validity according to self-reported PAI and a positive association with lipid and glucose profiles, and demonstrate dose-dependent associations with cardiac remodeling after adjustment for demographics and risk factors. Findings related to elevated METs may be due to the Hawthorne effect and require further studies.

URL

Relationship between social determinants of health, health-related quality of life, health perceptions, and physical activity during pregnancy (2025)

Women's Health (London, England)

Authors: Nowell, Kallie; Dlugonski, Deirdre; DeFranco, Emily; May, Linda; Hawk, Gregory S.; Hoch, Johanna M.

Abstract

BACKGROUND: Physical activity is essential to maintain the health of the mother and fetus during pregnancy; however, most pregnant women do not achieve the recommended amount. Studies have identified that social determinants of health (SDOH) may play a role in a woman's ability to participate in physical activity throughout pregnancy; however, there is little exploration of pregnant women from diverse backgrounds. Differences across SDOH influence health-related quality of life (HRQOL) and health perception, and each variable's relationship to physical activity during pregnancy requires further investigation. OBJECTIVES: Our first objective was to examine the relationship between SDOH and HRQOL variables in pregnant women. Our second objective was to compare participant physical activity levels by HRQOL, health perception, and SDOH categories in pregnant women. DESIGN: Secondary analysis. METHODS: Survey data from the National Institute of Health All of Us Research Program were utilized for this study. Demographics, SDOH, and HRQOL variables were extracted for analyses along with digital Fitbit data. HRQOL variables were analyzed for association with SDOH and demographic variables using separate one-way ANOVA. SDOH, demographic variables, and HRQOL variables were then analyzed for association with participant Fitbit data using separate one-way ANOVA. For significant associations, Tukey pairwise comparisons were performed. RESULTS: We found significant differences in health perception and quality of life across groups of SDOH and demographic variables including supportive relationships, income level, education level, and marital status. Women who reported higher HRQOL perceptions had significantly higher step counts and more very active minutes than those who reported lower HRQOL perceptions. CONCLUSIONS: SDOH are related to how pregnant women perceive their health and quality of life. Pregnant women with better health and quality-of-life perceptions are more likely to participate in more very active physical activity.

Reliability and Accuracy of the Fitbit Charge 4 Photoplethysmography Heart Rate Sensor in Ecological Conditions: Validation Study (2025)

JMIR mHealth and uHealth

Authors: Ceugniez, Maxime; Devanne, Hervé; Hermand, Eric

Abstract

Background: Wrist-worn photoplethysmography (PPG) sensors allow for continuous heart rate (HR) measurement without the inconveniences of wearing a chest belt. Although green light PPG technology reduces HR measurement motion artifacts, only a limited number of studies have investigated the reliability and accuracy of wearables in non-laboratory-controlled conditions with actual specific and various physical activity movements. Objective: The purpose of this study was to (1) assess the reliability and accuracy of the PPG-based HR sensor of the Fitbit Charge 4 (FC4) in ecological conditions and (2) quantify the potential variability caused by the nature of activities. Methods: We collected HR data from participants who performed badminton, tennis, orienteering running, running, cycling, and soccer while simultaneously wearing the FC4 and the Polar H10 chest belt (criterion sensor). Skin tone was assessed with the Fitzpatrick Skin Scale. Once data from the FC4 and criterion data were synchronized, accuracy and reliability analyses were performed, using intraclass correlation coefficients (ICCs), Lin concordance correlation coefficients (CCCs), mean absolute percentage errors (MAPEs), and Bland-Altman tests. A linear univariate model was also used to evaluate the effect of skin tone on bias. All analyses were stratified by activity and pooled activity types (racket sports and running sports). Results: A total of 77.5 hours of HR recordings from 26 participants (age: mean 21.1, SD 5.8 years) were analyzed. The highest reliability was found for running sports, with ICCs and CCCs of 0.90 and 0.99 for running and 0.80 and 0.93 for orienteering running, respectively, whereas the ICCs and CCCs were 0.37 and 0.78, 0.42 and 0.88, 0.65 and 0.97, and 0.49 and 0.81 for badminton, tennis, cycling, and soccer, respectively. We found the highest accuracy for running (bias: 0.1 beats per minute [bpm]; MAPE 1.2%, SD 4.6%) and the lowest for badminton (bias: -16.5 bpm; MAPE 16.2%, SD 14.4%) and soccer (bias: -16.5 bpm; MAPE 17.5%, SD 20.8%). Limit of agreement (LOA) width and artifact rate followed the same trend. No effect of skin tone was observed on bias. Conclusions: LOA width, bias, and MAPE results found for racket sports and soccer suggest a high sensitivity to motion artifacts for activities that involve "sharp" and random arm movements. In this study, we did not measure arm motion, which limits our results. However, whereas individuals might benefit from using the FC4 for casual training in aerobic sports, we cannot recommend the use of the FC4 for specific purposes requiring high reliability and accuracy, such as research purposes. Keywords: Fitbit; Fitbit Charge 4; accuracy; device; ecological; ecological conditions; exercise; heart rate; heart rate sensor; photoplethysmography; physical activity; reliability; sensitivity; sensor; usefulness; variability; wearables; wrist-worn device.

Rethinking measurement of movement-evoked pain with digital technology (2025)

The Journal of Pain

Authors: Frumkin, Madelyn R.; Zhang, Jingwen; Xu, Ziqi; Yakdan, Salim; Benedict, Braeden; Javeed, Saad; Zhang, Justin; Botterbush, Kathleen; Goodin, Burel R.; Lu, Chenyang; Ray, Wilson Z.; Greenberg, Jacob K.

Abstract

Movement-evoked pain (MEP) may be a useful metric for phenotyping musculoskeletal pain conditions. However, there is significant disagreement over operationalization, and no studies have assessed stability of MEP over time. Fitbit and Ecological Momentary Assessment (EMA) data were collected from adults with moderate-to-severe chronic pain schedule to receive lumbar/thoracolumbar fusion surgery (N=114). On average, participants provided 323 h of Fitbit data and 74 EMA surveys (84\% completion rate). To mimic task-based assessment of MEP using the 6-minute walk test, EMA pain ratings completed within 3 h of walking at a speed ≥70spm for at least 6 min were extracted. Of the full sample, 91 individuals (80\%) had any instances of pain ratings following 6-minute activity bouts (Median=6, SD=11). Post-activity pain scores exhibited good within-person consistency (ICC=.76). However, between-person differences in average pain accounted for {\textgreater}70\% of the variance in post-activity pain. MEP change scores defined as the difference between post-activity and pre-activity pain scores had poor reliability (ICC =.08). MEP change scores were not associated with average pain or factors related to the uncontrolled nature of digital assessment (e.g., activity amount, time from activity to pain report). However, MEP change scores tended to be lower when the preceding pain rating was elevated (β = -7.96, 95\% Credible Interval: -9.28, -6.66), suggesting ceiling effects. Small effects of time of day and prior activity were also observed, which could contaminate MEP assessed in the lab or clinic. Continued development of digital methodologies for assessing MEP is recommended. PERSPECTIVE: Existing movement-evoked pain assessments have limitations. Post-activity pain ratings capture overall disability and day-to-day fluctuations in pain, rather than the relationship between movement and pain. Pre-to-post activity change scores had poor reliability when assessed naturalistically and over time. Digital methodologies capture movement-evoked pain continuously across time, contexts, and real-world environments.

Self-Reported Acceptance of a Wearable Activity Monitor in Persons With Stroke: Usability Study (2025)

JMIR cardio

Authors: Nam, Jamie; Bellinger, Grace C.; Li, Junyao; French, Margaret A.; T Roemmich, Ryan

Abstract

BACKGROUND: Wearable activity monitors offer clinicians and researchers accessible, scalable, and cost-effective tools for continuous remote monitoring of functional status. These technologies can complement traditional clinical outcome measures by providing detailed, minute-by-minute, remotely collected data on a wide array of biometrics, including physical activity and heart rate. There is significant potential for the use of these devices in rehabilitation after stroke if individuals will wear and use the devices; however, the acceptance of these devices by persons with stroke is not well understood. OBJECTIVE: This study investigated the self-reported acceptance of a commercially available, wrist-worn wearable activity monitor (the Fitbit Inspire 2; Fitbit Inc) for remote monitoring of physical activity and heart rate in persons with stroke. We also assessed relationships between reported acceptance and adherence to wearing the device. METHODS: Sixty-five participants with stroke wore a Fitbit Inspire 2 for 3 months, at which point we assessed acceptance using the Technology Acceptance Questionnaire (TAQ), which includes 7 dimensions: perceived usefulness, perceived ease of use, equipment characteristics, privacy concerns, perceived risks, facilitating conditions, and subjective norm. We then performed Spearman correlations to assess relationships between acceptance and adherence to device wear, calculated as both the percentage of daily wear time and the percentage of valid days the device was worn during the 3 weeks preceding TAQ administration. RESULTS: Most participants reported generally agreeable responses, with high overall total TAQ scores across all 7 dimensions, indicating strong acceptance of the device; "Agree" was the median response to 29 of the 31 TAQ statements. Participants generally found the device beneficial for their health, efficient for monitoring, easy to use and to don and doff, and unintrusive to daily life. However, participant responses on the TAQ did not show significant positive correlations with measures of actual device wear time (all P{\textgreater}.05). CONCLUSIONS: This study demonstrates generally high self-reported acceptance of the Fitbit Inspire 2 among persons with stroke. Participants reported general agreement across all 7 TAQ dimensions, with minimal concerns interpreted as being directly relatable to poststroke motor impairment (eg, donning and doffing the device, using it independently). However, the high self-reported acceptance scores did not correlate positively with measures of real-world device wear. Accordingly, it should not be assumed that persons with stroke will adhere to wearing these devices simply because they report high acceptability.

Self-reported and tracker-estimated physical activity outcomes in women with chronic pelvic pain disorders: A longitudinal evaluation of construct validity (2025)

medRxiv: The Preprint Server for Health Sciences

Authors: Nagaldinne, Tanisee; Shahnawaz, Samia; Bakken, Suzanne R.; Elhadad, Noemie; Horan, Emma N.; Ewing-Garber, Carol; Rodrigues, Jovita; Danieletto, Matteo; Landell, Kyle; Ensari, Ipek

Abstract

Objective: This study aims to evaluate the short form International Physical Activity Questionnaire (IPAQ) for use in women with chronic pelvic pain disorders (CPPDs) by comparing its scores against objectively-estimated physical activity (PA) outcomes. We investigated IPAQ components that are most consistently predictive of habitual PA behavior. Method: The study sample included 966 weeks of data from 112 women with CPPDs who enrolled in a 14-week mHealth-based self-tracking study. Participants wore Fitbit devices and completed the IPAQ every week. We compared the IPAQ-reported minutes of walking, total activity, sitting, light-, moderate-, and vigorous intensity PA for concordance and divergence against their corresponding Fitbit estimates. We used linear mixed-effects regression models (MLMs) for all analyses and quantified the between-participant variance in the magnitude of agreement between the two methods via random slope terms. We further evaluated temporal consistency in scores using intraclass correlation coefficients (ICCs). Results: IPAQ-reported walking minutes were strongly associated with Fitbit step counts (B = 3952.36; p = 0.006), minutes of moderate PA (B = 15.498; p = 0.0113), and moderate-to-vigorous PA (MVPA; B = 28.973; p = 0.007). IPAQ total activity minutes were associated with Fitbit minutes of vigorous PA (B = 15.183; p = 0.007) and MVPA (B = 25.658; p = 0.010). IPAQ moderate activity minutes were predictive of Fitbit vigorous PA minutes (B = 9.060; SE = 3.719; p = 0.0151). There was substantial between-individual variance in these point estimates based on the significant random-effect terms, and average weekly PA level was a significant moderator of the association between IPAQ-reported and Fitbit-estimated scores for these variables. IPAQ-reported sitting minutes were inversely associated with Fitbit step counts (B = -3125.61; p = 0.004), and minutes of MVPA (B = -21.848; p = 0.007), vigorous AP (B = -10.854; p = 0.042), and moderate PA (B = -10.985; p = 0.004). Conclusion: These findings provide support for using IPAQ-reported walking and total activity minutes to monitor several PA domains in women with CPPDs, given their concordance with several tracker-estimated PA outcomes. However, the item on "sitting time" may not be a suitable for assessing sedentary time.

Sensor-triggered ecological momentary assessment in physical activity and sedentary behaviour research among Belgian community-dwelling elderly: lessons learnt from intensive longitudinal studies (2025)

BMJ open

Authors: Delobelle, Julie; Lebuf, Elien; Compernolle, Sofie; Vetrovsky, Tomas; Van Cauwenberg, Jelle; Cimler, Richard; Kuhnova, Jitka; Van Dyck, Delfien

Abstract

OBJECTIVES: Regular physical activity (PA) and reduced sedentary behaviour (SB) have been associated with positive health outcomes, but many older adults do not comply with the current recommendations. Sensor-triggered ecological momentary assessment (EMA) studies allow capturing real-time data during or immediately after PA or SB, which can yield important insights into these behaviours. Despite the promising potential of sensor-triggered EMA, this methodology is still in its infancy. Addressing methodological challenges in sensor-triggered EMA studies is essential for improving protocol adherence and enhancing validity. Therefore, this study aimed to examine (1) the patterns in sensor-triggered EMA protocol adherence (eg, compliance rates), (2) the impact of specific settings (eg, event duration) on the number of prompted surveys, and (3) participants' experiences with engaging in a sensor-triggered EMA study. DESIGN: Two longitudinal, sensor-triggered EMA studies-one focused on PA and the other on SB-were conducted using similar methodologies from February to October 2022. Participants' steps were monitored for seven days using a Fitbit activity tracker, which automatically prompted an EMA survey through the HealthReact smartphone application when specified (in)activity thresholds were reached. After the monitoring period, qualitative interviews were conducted. Data from both studies were merged. SETTING: The studies were conducted among community-dwelling Belgian older adults. PARTICIPANTS: The participants had a median age of 72 years, with 54.17\% being females. The PA study included 88 participants (four dropped out), while the SB study included 76 participants (seven dropped out). PRIMARY AND SECONDARY OUTCOME MEASURES: Descriptive methods and generalised logistic mixed models were employed to analyse EMA adherence patterns. Simulations were conducted to assess the impact of particular settings on the number of prompted EMA surveys. Additionally, qualitative interview data were transcribed verbatim and thematically analysed using NVivo. RESULTS: Participants responded to 81.22\% and 79.10\% of the EMA surveys in the PA and SB study, respectively. The confirmation rate, defined as the percentage of EMA surveys in which participants confirmed the detected behaviour, was 94.16\% for PA and 72.40\% for SB. Logistic mixed models revealed that with each additional day in the study, the odds of responding to the EMA survey increased significantly by 1.59 times (OR=1.59, 95\% CI: 1.36 to 1.86, p{\textless}0.01) in the SB study. This effect was not observed in the PA study. Furthermore, time in the study did not significantly impact the odds of participants confirming to be sedentary (OR=0.97, 95\% CI: 0.92 to 1.02, p=0.28). However, it significantly influenced the odds of confirming PA (OR: 0.81, 95\% CI: 0.68 to 0.97, p=0.02), with the likelihood of confirming decreasing by 19\% with each additional day in the study. Furthermore, a one-minute increase in latency (ie, time between last syncing and starting the EMA survey) in the PA study decreased the odds of the participant confirming to be physically active by 20\% (OR: 0.80, 95\% CI: 0.72 to 0.89, p{\textless}0.01). Simulations of the specific EMA settings revealed that reducing the event duration and shorter minimum time intervals between prompts increased the number of EMA surveys. Overall, most participants found smartphone usage to be feasible and rated the HealthReact app as user-friendly. However, some reported issues, such as not hearing the notification, receiving prompts at an inappropriate time and encountering technical issues. While the majority reported that their behaviour remained unchanged due to study participation, some noted an increased awareness of their habits and felt more motivated to engage in PA. CONCLUSIONS: This study demonstrates the potential of sensor-triggered EMA to capture real-time data on PA and SB among older adults, showing strong adherence potential with compliance rates of approximately 80\%. The SB study had lower confirmation rates than the PA study, due to technical issues and discrepancies between self-perception and device-based measurements. Practical recommendations were provided for future studies, including improvements in survey timing, technical reliability and strategies to reduce latency.

Sleep duration and efficiency moderate the effects of prenatal and childhood ambient pollutant exposure on global white matter microstructural integrity in adolescence (2025)

bioRxiv: The Preprint Server for Biology

Authors: Cotter, Devyn L.; Kiss, Orsolya; Ahmadi, Hedyeh; de Jesus, Alethea; Schwartz, Joel; Baker, Fiona C.; Hackman, Daniel A.; Herting, Megan M.

Abstract

Background: Air pollution is a ubiquitous neurotoxicant associated with alterations in structural connectivity. Good habitual sleep may be an important protective lifestyle factor due to its involvement in the brain waste clearance and its bidirectional relationship with immune function. Wearable multisensory devices may provide more objective measures of sleep quantity and quality. We investigated whether sleep duration and efficiency moderated the relationship between prenatal and childhood pollutant exposure and whole-brain white matter microstructural integrity at ages 10-13 years. Methods: We used multi-shell diffusion-weighted imaging data collected on 3T MRI scanners and objective sleep data collected with Fitbit Charge 2 from the 2-year follow-up visit for 2178 subjects in the Adolescent Brain Cognitive Development Study®. White matter tracts were identified using a probabilistic atlas. Restriction spectrum imaging was performed to extract restricted normalized isotropic (RNI) and directional (RND) signal fraction parameters for all white matter tracts, then averaged to calculate global measures. Sleep duration was calculated by summing the time spent in each sleep stage; sleep efficiency was calculated by dividing sleep duration by time spent in bed. Using an ensemble-based modeling approach, air pollution concentrations of PM2.5, NO2, and O3 were assigned to each child's residential addresses during the prenatal period (9-month average before birthdate) as well as at ages 9-10 years. Multi-pollutant linear mixed effects models assessed the associations between global RNI and RND and sleep-by-pollutant interactions, adjusting for appropriate covariates. Results: Sleep duration interacted with childhood NO2 exposure and sleep efficiency interacted with prenatal O3 exposure to affect RND at ages 10-13 years. Longer sleep duration and higher sleep efficiency in the context of higher pollutant exposure was associated with lower RND compared to those with similar pollutant exposure but shorter sleep duration and lower sleep efficiency. Conclusions: Low-level air pollution poses a risk to brain health in youth, and healthy sleep duration and efficiency may increase resilience to its harmful effects on white matter microstructural integrity. Future studies should evaluate the generalizability of these results in more diverse cohorts as well as utilize longitudinal data to understand how sleep may impact brain health trajectories in the context of pollution over time. Keywords: adolescence; air pollution; ground-level ozone; objective sleep measures; prenatal exposure; white matter microstructural integrity.

Snacktivity™ to Promote Physical Activity in Primary Care, Community Health and Public Health Settings: A Feasibility Randomised Controlled Trial (2025)

International Journal of Behavioral Medicine

Authors: Daley, Amanda J.; Griffin, Ryan A.; Sanders, James P.; Gokal, Kajal; Ives, Natalie; Skrybant, Magdalena; Parretti, Helen M.; Edwardson, Charlotte L.; Biddle, Stuart J. H.; Jolly, Kate; Greaves, Colin J.; Greenfield, Sheila M.; Maddison, Ralph; Esliger, Dale W.; Sherar, Lauren B.; Frew, Emma; Mutrie, Nanette; Maylor, Ben; Yates, Tom; Tearne, Sarah; Moakes, Catherine A.

Abstract

Background: A novel 'whole day' approach that could motivate the public to be more physically active is Snacktivity™. The Snacktivity™ approach encourages individuals to accumulate 150 min of physical activity in short 2-5-min 'snacks' of moderate-vigorous intensity physical activity (MVPA) throughout the day/week. Method: A randomised controlled trial to assess the feasibility/acceptability of a Snacktivity™ intervention and trial processes was conducted. The trial aimed to recruit 80 physically inactive adults from healthcare services and via social media. Participants were randomised to the Snacktivity™ intervention or usual care and followed up at 12 weeks. The intervention was predominately delivered by health professionals within consultations. Assessment of whether the Snacktivity™ intervention and trial methods were acceptable to participants, adherence to Snacktivity™ (assessed by Fitbit) and physical activity (assessed by accelerometer), and retention were considered according to traffic light stop-go progression criteria (green-amber-red). Results: Seventy-two participants (n = 37 Snacktivity™ intervention; n = 35 usual care) were recruited across 14 months (72/80, 90%, (green) 95% CI: 83% to 97%). Snacktivity™ adherence was achieved in 12/37 participants (32%, (red) 95% CI: 17% to 48%). Physical activity adherence was achieved in 17/37 participants (46%, (amber) 95% CI: 30% to 62%). Seven participants (10%, (green) 95% CI: 3% to 17%) withdrew from follow-up and 25/72 (35%, (amber) 95% CI: 24% to 46%) had no accelerometer data at follow-up (retention). Conclusion: The Snacktivity™ intervention may be feasible and acceptable to implement. Findings can inform subsequent research that seeks to investigate whether Snacktivity™ based approaches are effective in promoting physical activity in the population.

Somatomotor Disconnection Links Sleep Duration With Socioeconomic Context, Screen Time, Cognition, and Psychopathology (2025)

Biological Psychiatry Global Open Science

Authors: Michael, Cleanthis; Taxali, Aman; Angstadt, Mike; McCurry, Katherine L.; Weigard, Alexander; Kardan, Omid; Molloy, M. Fiona; Toda-Thorne, Katherine; Burchell, Lily; Dziubinski, Maria; Choi, Jason; Vandersluis, Melanie; Hyde, Luke W.; Heitzeg, Mary M.; Sripada, Chandra

Abstract

BACKGROUND: Sleep is critical for healthy brain development and emotional well-being, especially during adolescence, when sleep, behavior, and neurobiology are rapidly evolving. Theoretical reviews and empirical research have historically focused on how sleep influences mental health through its impact on higher-order brain systems. No studies have leveraged data-driven network neuroscience methods to uncover interpretable, brainwide signatures of sleep duration in adolescence, their socioenvironmental origins, and their consequences for cognition and psychopathology. METHODS: We implemented graph theory and component-based predictive modeling to examine how a multimodal index of sleep duration (parent-report, youth-report, Fitbit) is associated with intrinsic brain architecture in 3037 youths (ages 11-12 years) from the ABCD (Adolescent Brain Cognitive Development) Study. RESULTS: We demonstrated that network integration/segregation exhibited a strong, generalizable multivariate association with sleep duration (r = 0.23, p {\textless} .001). The multivariate signature of shorter sleep predominantly involved increasing disconnection of a lower-order system, the somatomotor network, from other systems. Next, we identified a single component of brain architecture as the dominant contributor of this relationship (r = 0.15), which again exhibited this somatomotor disconnection motif. Finally, greater somatomotor disconnection was associated with lower socioeconomic resources, longer screen times, reduced cognitive/academic performance, and elevated externalizing problems (βs {\textgreater} 0.03, ps ≤ .007). CONCLUSIONS: These findings reveal a novel neural signature of shorter sleep in adolescence that is intertwined with environmental risk, cognition, and psychopathology. By robustly elucidating the key involvement of an understudied brain system in sleep, this study can inform theoretical and translational research directions on sleep to promote neurobehavioral development and mental health during the adolescent transition.

Temporal relationships between depression, self-efficacy, and physical activity in individuals with stroke (2025)

medRxiv

Authors: Bellinger, Grace C.; Roemmich, Ryan T.; Psoter, Kevin J.; Wegener, Stephen T.; Keatley, Eva; French, Margaret A.

Abstract

Objective To investigate the temporal relationships between depressive symptoms, physical activity, and self-efficacy in individuals with stroke Design Six-month prospective observational cohort study Setting General community Participants Seventy-three individuals with stroke (42 male; 61.9±12.3 years old) Interventions Not applicable Main Outcome Measures Three functional domains were the primary outcomes: physical activity was defined by average steps per day as measured by a Fitbit device; depressive symptoms and self-efficacy were measured by Patient-Reported Outcomes Measurement Information System (PROMIS) short forms. These outcome measures were collected at study enrollment and monthly thereafter for six months, resulting in a maximum of seven timepoints. Results Three separate lagged linear mixed effects models were constructed (one with each functional domain as the dependent variable). Each model included the measure of the targeted functional domain as the dependent variable, measurements from the previous month of the two other functional domains and their interaction as fixed effects, participant as a random effect, and demographics and stroke characteristics as covariates. The depressive symptoms by self-efficacy interaction was associated with future physical activity, suggesting that higher self-efficacy positively impacts the following month’s physical activity only when depressive symptoms are low. Depressive symptoms were not associated with self-efficacy, steps per day, or their interaction in the prior month, indicating that the relationship between depressive symptoms and physical activity is unidirectional. Finally, depressive symptoms were associated with self-efficacy in the subsequent month. Conclusions The longitudinal study provides evidence that 1) mitigating depressive symptoms and promoting self-efficacy may improve future physical activity; 2) addressing depressive symptoms first may lead to more effective treatment of depression, low self-efficacy, and low physical activity; and 3) treating depression may improve future self-efficacy. Together the results provide additional knowledge about the complex relationships between mobility, mood, and self-efficacy that must be carefully managed during post-stroke rehabilitation.

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Tension and Trauma Releasing Exercises for People with Multiple Sclerosis: A Randomized Controlled Trial (2025)

Advances in Mind-Body Medicine

Authors: Skovgaard, Lasse; Trénel, Philipp; Hanehøj, Kirsten; Lynning, Marie

Abstract

CONTEXT: Some studies suggests that mind-body therapies may be helpful for people with multiple sclerosis (PwMS) for symptom management. PwMS have reported benefits from Tension and Trauma Releasing Exercises (TRE); however, only limited research exists on the potential benefits of TRE. OBJECTIVE: The study intended to determine whether an eight-week intervention of Tension and Trauma Releasing Exercises (TRE), a mind-body therapy, could primarily reduce fatigue and secondarily decrease other MS-related symptoms and to explore new, experimental outcome measures-sleep, hand motor function, gait function, cognitive function, or mood-for use in future research on TRE for PwMS. DESIGN: The research team performed a randomized controlled trial (RCT). SETTING: The study took place at the Danish MS Society in Valby, Denmark. PARTICIPANTS: Participants were 28 members of the society who had an MS diagnosis and lived in the Copenhagen area. INTERVENTION: The research team performed simple randomization to allocate participants to the intervention and control groups. The intervention group received eight sessions of TRE and performed TRE daily at home, while the control group continued their usual care only. OUTCOME MEASURES: The primary outcome measure was self-reported fatigue measured via the Modified Fatigue Impact Scale (MFIS) at baseline and postintervention. Daily self-reported levels of nine MS-related symptoms as well as stress levels were obtained as secondary endpoints, using a digital tool, the MS PRO. For explorative purposes, daily measures of sleep duration and quality were obtained, via the Fitbit Charge 3 activity tracker. Finally, smartphone-based measurements of hand motor function, gait, cognition, and mood were obtained via the Floodlight Open (FLO) app. RESULTS: On primary outcomes, no significant differences between the TRE intervention group and the control group were detected at follow-up in the unadjusted analyses. However, when adjusted for imbalance in covariates, significant group differences were obtained in the MFIS total score (P = .03) as well as marginal significance in the MFISphys score (P = .06). The TRE intervention significantly reduced reported levels of spasticity and pain across the whole intervention period, and it showed a significant effect of gradual improvement in the 5 U-turn test over the study period. CONCLUSIONS: Positive effects on both primary and secondary outcomes from the TRE intervention were seen when adjusting for covariate imbalance. Therefore, it cannot be ruled out that TRE significantly improves fatigue in people with MS. Furthermore, the current study underlines the potential effect of bias-adjustment, when covariate imbalance is present. However, further research is needed to confirm the positive effects.

The effect of sleep quality on glucose variability among adolescents with type 1 diabetes in China: A multi-central temporal longitudinal association analysis (2025)

Sleep Medicine

Authors: Li, Qingting; Lv, Wencong; Yuwen, Weichao; Jia, Zhumin; Li, Xia; Guo, Jia

Abstract

Study objectives High glucose variability is common among adolescents with type 1 diabetes mellitus (T1DM). On person level, poor sleep quality has been reported to be an important factor associated with high glucose variability among adolescents with T1DM. However, on day level, the effect of sleep quality on glucose variability remains unclear, limiting temporal adjustment of treatment regimens. This study aimed to concurrently explore associations between sleep quality and glucose variability at both day and person levels among Chinese adolescents with T1DM based on the 24-h Recursive Cycle model. Methods A multi-center, seven-day, temporal longitudinal study was conducted among Chinese adolescents with T1DM. Glucose variability measures were calculated by fingertip blood glucose level at least seven times a day. Subjective sleep quality was measured by total sleep time, wake after sleep onset, number of awakenings, a score of sleep quality, sleep time, and wake time using a sleep diary. Objective sleep quality was assessed by Fitbit Inspire HR and included total sleep time, wake after sleep onset, and number of awakenings, rapid eye movement, light sleep time, deep sleep time, sleep time, wake time, sleep midpoint, and sleep efficiency. A multilevel linear regression model was performed to examine the associations between objective and subjective sleep quality and glucose variability at day and person levels. Gender, age, diabetes duration, complications documented within the preceding 6 months, HbA1c, and insulin pump therapy were controlled at person-level model. Results A total of 51 adolescents with T1DM participated in this study, which included 357 records of data. Only 21.57 \% (N = 12) of adolescents met the recommended sleep time of 480 min per night measured by Fitbit. About a quarter (N = 11) of adolescents had a coefficient of variation of blood glucose {\textgreater}36 \%. At person level, there was no significant association between sleep quality and glucose variability (p {\textgreater} 0.05). Multilevel models found significant associations between sleep quality and glucose variability at day level. Lower score of subjective sleep quality was significantly associated with higher standard deviation of blood glucose (p {\textless} 0.05) in the next day. Less Fitbit-measured light sleep time was significantly associated with higher standard deviation of blood glucose, and postprandial of glycemic excursions in the next day (p {\textless} 0.05). More Fitbit-measured awakenings and less rapid eye movement were associated with higher postprandial glycemic excursions in the next day (p {\textless} 0.05). Conclusion Nearly 80 \% of Chinese adolescents with T1DM did not meet the recommended amount of sleep for their age group. They experienced more wakes after sleep onset at night and poorer sleep quality than their subjective experience. According to the findings on temporal relationships, intervention components targeting reducing wakes after sleep onset and improving subjective sleep quality would reduce glucose variability over time among Chinese adolescents with T1DM.

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The effectiveness and cost effectiveness of Snacktivity™ as an intervention to promote physical activity and health outcomes: a study protocol for a multi-centre randomised controlled trial (2025)

Trials

Authors: Daley, Amanda J.; Griffin, Ryan A.; Sanders, James P.; Edwardson, Charlotte L.; Neal, Liam; Lee, Sam; Skrybant, Magdalena; Moakes, Catherine A.; Gkini, Eleni; Frew, Emma; Greaves, Colin J.; Dobell, Alexandra; Gokal, Kajal; Tearne, Sarah; Parretti, Helen M.; Biddle, Stuart J. H.; Jolly, Kate; Greenfield, Sheila M.; Maddison, Ralph; Esliger, Dale W.; Sherar, Lauren B.; Mutrie, Nanette; Yates, Tom; Ives, Natalie

Abstract

BACKGROUND: A novel 'whole day' approach that could motivate the public to be more physically active is termed Snacktivity™. Consistent with guidance, the Snacktivity™ approach encourages the public to accumulate ≥ 150 min of physical activity in short 2-5-min 'activity snacks' of moderate-vigorous intensity physical activity throughout the day/week. Snacktivity™ also promotes muscle-strengthening activity twice per week. Following completion of research to co-design and develop the Snacktivity™ approach, the aim of this trial is to assess the effectiveness and cost-effectiveness of a Snacktivity™ intervention to increase physical activity and reduce future risk of disease in the population, compared with usual care. METHODS: A multi-centre, two-arm, individually randomised, parallel group, superiority trial, with an economic evaluation, will be conducted in 966 physically inactive adults. Participants will be recruited from National Health Service Trusts and organisations and non-National Health Service settings (e.g. community groups and social media). Participants will be individually randomized (1:1) to the Snacktivity™ intervention group or a usual care comparator group. The Snacktivity intervention involves two main components; a brief 5-min consultation about the principles and purpose of Snacktivity™; and access to technology support (mobile phone app called the SnackApp, linked to a Fitbit activity device (Versa 4)) that through behavioural change techniques promote self-monitoring of physical activity, habit formation, action planning and feedback on the number of activity snacks completed each day. The primary outcome is the difference in average minutes of moderate-vigorous physical activity between the groups at 12-months follow up, measured using a wrist worn accelerometer. Secondary outcomes include accelerometer-assessed average minutes per day of light, moderate, and vigorous intensity physical activity, time sedentary, weight and psychological health outcomes, at 12 month follow-up. DISCUSSION: Innovative interventions such as Snacktivity™, that aim to support the public to increase their physical activity each day are required. Findings could inform future public health guidance and public health messaging that seeks to raise awareness in the population of the potential benefits of Snacktivity™ for health. TRIAL REGISTRATION: ISRCTN: 12390945 . Registered on 22 March, 2024.

The feasibility and acceptability of delivering and evaluating a physical activity intervention (ACCEPTANCE) for cervical cancer survivors (2025)

Pilot and Feasibility Studies

Authors: Millet, Nessa; McDermott, Hilary J.; Munir, Fehmidah; Edwardson, Charlotte L.; Plekhanova, Tatiana; Moss, Esther L.

Abstract

BACKGROUND: Cervical cancer treatment can be associated with long-term physical, psychological and emotional issues leading to compromised quality of life (QOL). Physical activity (PA) may improve QOL in cervical cancer survivors. METHODS: A one-arm pre/post-feasibility study with parallel process evaluation was conducted to test the feasibility and acceptability of a 12-week PA intervention (ACCEPTANCE). Feasibility was determined by using pre-established criteria relating to inclusion criteria, recruitment and retention, compliance with intervention components and compliance with evaluation measures. The 12-week intervention consisted of (1) an online education session on the benefits of PA and a barrier identification and problem-solving session; (2) a Fitbit monitor; (3) daily and weekly diary entries; (4) brief fortnightly online health coaching sessions; and (5) organising and participating in group walks; (6) online social interaction via a messaging group. Measures included accelerometer assessed PA and sleep, quality-of-life and PA behaviour change questionnaires distributed at 4-time points (baseline, week 6, week 12, and week 24). Process evaluation measures were questionnaires on the acceptance of intervention components and semi-structured interviews with participants after completion. RESULTS: Thirty participants were recruited with a retention rate of 77\% at week 24. The education session, health coaching and Fitbit PA monitor were deemed to be feasible based on compliance rates whilst the online messaging group, diary and group walking compliance suggested that modifications would be needed for these components. Accelerometer and questionnaires were deemed to be feasible evaluation measures based on compliance rates. Process evaluation results suggest that the Fitbit and health coaching sessions were perceived to be the most beneficial aspects of the programme as they enabled self-monitoring of behaviour and goal setting. Unexpected mechanisms of behaviour change were the integration of a small change approach and formation of habits to facilitate PA, whilst barriers to behaviour change included the online, virtual nature of the programme, poor mental health, and environmental challenges. PA levels were higher after the intervention, whilst global QOL was seen to worsen throughout the study, and depression and anxiety symptoms improved. CONCLUSIONS: The ACCEPTANCE study is deemed to be feasible based on criteria established a priori, and only minor modifications would needed to implement in a definitive randomised control trial. The intervention showed potential to increase PA, through hypothesised mechanisms of self-monitoring behaviour and problem solving and unexpected mechanisms such as habit formation. TRIAL REGISTRATION: ISRCTN16349793, Registered 30 September 2020.

The Physical Activity at Work (PAW) Program in Thai Office Workers: Mixed Methods Process Evaluation Study (2025)

JMIR formative research

Authors: Akksilp, Katika; Rouyard, Thomas; Isaranuwatchai, Wanrudee; Nakamura, Ryota; Müller-Riemenschneider, Falk; Teerawattananon, Yot; Chen, Cynthia

Abstract

Background: An increasing number of multicomponent workplace interventions are being developed to reduce sedentary time and promote physical activity among office workers. The Physical Activity at Work (PAW) trial was one of these interventions, but it yielded an inconclusive effect on sedentary time after 6 months, with a low uptake of movement breaks, the main intervention component. Objective: This study investigates the factors contributing to the outcomes of the PAW cluster randomized trial. Methods: Following the Medical Research Council's guidance for process evaluation of complex interventions, we used a mixed methods study design to evaluate the PAW study's recruitment and context (how job nature and cluster recruitment affected movement break participation), implementation (dose and fidelity), and mechanisms of impact (assessing how intervention components affected movement break participation and identifying the facilitators and barriers to participation in the movement breaks). Data from accelerometers, pedometers, questionnaires, on-site monitoring, and focus group discussions were used for the evaluation. Linear mixed effects models were used to analyze the effects of different intervention components on the movement breaks. Subsequently, qualitative analysis of the focus group discussions provided additional insights into the relationship between the intervention components. Results: The participation in movement breaks declined after the third week, averaging 12.7 sessions (SD 4.94) per participant per week for the first 3 weeks, and continuing to decrease throughout the intervention. On-site monitoring confirmed high implementation fidelity. Analysis of Fitbit data revealed that each additional movement break was associated with a reduction of 6.20 (95% CI 6.99-5.41) minutes in sedentary time and an increase of 245 (95% CI 222-267) steps. Regarding the mechanisms of impact, clusters with higher baseline sedentary time demonstrated greater participation in movement breaks, while those with frequent out-of-office duties showed minimal engagement. Moreover, clusters with enthusiastic and encouraging movement break leaders were associated with a 24.1% (95% CI 8.88%-39.4%) increase in participation. Environmental and organizational support components using posters and leaders' messages were ineffective, showing no significant change in percentage participation in movement breaks (4.49%, 95% CI -0.49% to 9.47% and 1.82%, 95% CI -2.25% to 5.9%, respectively). Barriers such as high workloads and meetings further hindered participation, while the facilitators included participants' motivation to feel active and the perceived health benefits from movement breaks. Conclusions: Despite high fidelity, the PAW trial did not significantly reduce sedentary time, with limited uptake of movement breaks due to context-related challenges, ineffective environmental support, and high workloads during the COVID-19 pandemic. Keywords: movement breaks; physical activity; process evaluation; sedentary behavior; workplace.

Transcutaneous auricular vagus nerve stimulation (taVNS) improves sleep quality in chronic insomnia disorder: A double-blind, randomized, sham-controlled trial (2025)

Sleep Medicine

Authors: Yeom, Ji Won; Kim, Hyojin; Park, Soohyun; Yoon, Yeaseul; Seo, Ju Yeon; Cho, Chul-Hyun; Lee, Heon-Jeong

Abstract

Background Insomnia is a common sleep disorder that significantly impacts quality of life and health. Conventional treatments such as cognitive-behavioral therapy and pharmacological interventions have limitations, underscoring the need for non-invasive alternatives. Transcutaneous auricular vagus nerve stimulation (taVNS) has emerged as a promising therapy to enhance sleep quality by modulating the autonomic nervous system. Objective This study aimed to evaluate the efficacy and safety of taVNS compared to sham in managing chronic insomnia disorder. Methods A randomized, double-blind, sham-controlled trial was conducted with 40 participants diagnosed with chronic insomnia disorder. Participants were randomly assigned to receive taVNS or sham for 30 min daily over six weeks. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) as the primary outcome. Secondary outcomes included the Insomnia Severity Index (ISI), World Health Organization Quality of Life Brief Version (WHOQOL-BREF), and total sleep time. Adverse events were recorded, and objective sleep measures were obtained using Fitbit wearable devices. Results In the modified intention-to-treat analysis at 6 weeks, the taVNS group exhibited significantly greater reductions in PSQI scores compared to the sham group (mean change: 4.5 ± 3.55 vs. −1.9 ± 2.15; Cohen's d = −1.21; p = .009). ISI scores also improved more in the taVNS group (−7.6 ± 5.23 vs. −4.25 ± 3.48; Cohen's d = −.75; p = .023). Total sleep time increased significantly in the taVNS group (584 ± 1015 min, vs. −10.8 ± 579 min; Cohen's d = .69; p = .019) and improved quality of life (WHOQOL-BREF: 32.2 ± 40.9 vs. 7.95 ± 33.5; Cohen's d = .65, p = .047). No significant adverse events were reported. Conclusions taVNS significantly improved sleep quality, insomnia severity, and overall quality of life compared to sham. These findings establish taVNS as a safe and effective non-invasive therapy for managing insomnia, with potential for broader clinical applications.

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Unlocking the Potential of Wear Time of a Wearable Device to Enhance Postpartum Depression Screening and Detection: Cross-Sectional Study (2025)

JMIR Formative Research

Authors: Hurwitz, Eric; Meltzer-Brody, Samantha; Butzin-Dozier, Zachary; Patel, Rena C.; Elhadad, Noémie; Haendel, Melissa A.

Abstract

Background Postpartum depression (PPD) is a mood disorder affecting 1 in 7 women after childbirth that is often underscreened and underdetected. If not diagnosed and treated, PPD is associated with long-term developmental challenges in the child and maternal morbidity. Wearable technologies, such as smartwatches and fitness trackers (eg, Fitbit), offer continuous and longitudinal digital phenotyping for mood disorder diagnosis and monitoring, with device wear time being an important yet understudied aspect. Objective We aimed to suggest that wear time of a wearable device may provide additional information about perinatal mental health to facilitate screening and early detection of PPD. We proposed that wear time of a wearable device may also be valuable for managing other mental health disorders. Methods Using the All of Us Research Program dataset, we identified females who experienced childbirth with and without PPD using computational phenotyping. We compared the percentage of days and number of hours per day females with and without PPD wore Fitbit devices during prepregnancy, pregnancy, postpartum, and PPD periods, determined by electronic health records. Comparisons between females with and without PPD were conducted using linear regression models. We also assessed the correlation between Fitbit wear time consistency (measured as the maximum number of consecutive days the Fitbit was worn) during prepregnancy and PPD periods in females with and without PPD using the Pearson correlation. All analyses were run with Bonferroni correction. Results Our findings showed a strong trend, although nonsignificant after multiple testing correction, that females in the PPD cohort wore their Fitbits more than those in non-PPD cohort during the postpartum (PPD cohort: mean 69.9\%, 95\% CI 42.7\%-97\%; non-PPD cohort: mean 50\%, 95\% CI 25.5\%-74.4\%; P=.02) and PPD periods (PPD cohort: mean 66.6\%, 95\% CI 37.9\%-95.3\%; non-PPD cohort: mean 46.4\%, 95\% CI 20.5\%-72.2\%; P=.02). We found no difference in the number of hours per day females in the PPD and non-PPD cohorts wore their Fitbit during any period of pregnancy. Finally, there was no relationship between the consistency of Fitbit wear time during prepregnancy and PPD periods (r=–0.05, 95\% CI –0.46 to 0.38; P=.84); however, there was a trend, though nonsignificant, in Fitbit wear time consistency among females without PPD (r=0.25, 95\% CI –0.02 to 0.49; P=.07). Conclusions We hypothesize that increased Fitbit wear time among females with PPD may be attributed to hypervigilance, given the common co-occurrence of anxiety symptoms. Future studies should assess the link between PPD, hypervigilance, and wear time patterns. We envision that wear time patterns of a wearable device combined with digital biomarkers such as sleep and physical activity could enhance early PPD detection using machine learning by alerting clinicians to potential concerns and facilitating timely screenings, which may have implications for other mental health disorders.

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Usability and Implementation Considerations of Fitbit and App Intervention for Diverse Cancer Survivors: Mixed Methods Study (2025)

JMIR cancer

Authors: Dabbagh, Zakery; Najjar, Reem; Kamberi, Ariana; Gerber, Ben S.; Singh, Aditi; Soni, Apurv; Cutrona, Sarah L.; McManus, David D.; Faro, Jamie M.

Abstract

Background: Despite the known benefits of physical activity, cancer survivors remain insufficiently active. Prior trials have adopted digital health methods, although several have been pedometer-based and enrolled mainly female, non-Hispanic White, and more highly educated survivors of breast cancer. Objective: The objective of this study was to test a previously developed mobile health system consisting of a Fitbit activity tracker and the MyDataHelps smartphone app for feasibility in a diverse group of cancer survivors, with the goal of refining the program and setting the stage for a larger future trial. Methods: Participants were identified from one academic medical center's electronic health records, referred by a clinician, or self-referred to participate in the study. Participants were screened for eligibility, enrolled, provided a Fitbit activity tracker, and instructed to download the Fitbit: Health & Wellness and MyDataHelps apps. They completed usability surveys at 1 and 3 months. Interviews were conducted at the end of the 3-month intervention with participants and cancer care clinicians to assess the acceptability of the intervention and the implementation of the intervention into clinical practice, respectively. Descriptive statistics were calculated for demographics, usability surveys, and Fitbit adherence and step counts. Rapid qualitative analysis was used to identify key findings from interview transcriptions. Results: Of the 100 patients screened for eligibility, 31 were enrolled in the trial (mean age 64.8, SD 11.1 years; female patients=17/31, 55%; Hispanic or Latino=7/31, 23%; non-White=11/31, 35%; less than a bachelor's degree=14/31, 45%; and household income <US $75,000=11/31, 35%). The mean (SD) years since diagnosis was 7.1 (8.2), and the two most frequent cancer diagnoses were prostate (9/31, 29%) and breast (4/31, 13%) cancer. Participants provided positive feedback on the MyDataHelps app usability; the overall app quality received a mean score of 3.79 (SD 0.82) on a 5-point Likert scale (1=worst, 5=best). Interviews with 10 patients yielded four themes: (1) Fitbit and app setup was easy but the research team provided assistance, when needed, which was helpful, (2) motivational messages within the app were not memorable, (3) step counts and Fitbit notifications were motivating, and (4) medical professionals viewing their data were acceptable. Interviews with 5 cancer care clinicians yielded four themes: (1) some patients used wearables but rarely discussed data with clinicians; (2) activity trackers can be helpful to motivate patients and keep them accountable; (3) objective activity measures-similar to BMI, weight, and blood pressure- that they can track over time and refer to afterward were preferred; and (4) training and systematic processes to view these data as part of active workflow were desired. Conclusions: Implementing a remotely delivered, light-intensity physical activity program was feasible and acceptable in a sample of diverse cancer survivors. Future studies should consider registry-based methods and work with clinicians to engage hard-to-reach survivor populations who have low physical activity levels and disproportionately high adverse health outcomes. Keywords: Fitbit; Hispanic; activity tracker; breast cancer; cancer survivor; digital health; digital health method; diverse; feasibility; mHealth; mobile health; physical activity; smartphone app; usability; wearable; wearable device; women.

Use of mHealth Technology for Improving Exercise Adherence in Patients With Heart Failure: Systematic Review (2025)

Journal of Medical Internet Research

Authors: Deka, Pallav; Salahshurian, Erin; Ng, Teresa; Buchholz, Susan W.; Klompstra, Leonie; Alonso, Windy

Abstract

Background: The known and established benefits of exercise in patients with heart failure (HF) are often hampered by low exercise adherence. Mobile health (mHealth) technology provides opportunities to overcome barriers to exercise adherence in this population. Objective: This systematic review builds on prior research to (1) describe study characteristics of mHealth interventions for exercise adherence in HF including details of sample demographics, sample sizes, exercise programs, and theoretical frameworks; (2) summarize types of mHealth technology used to improve exercise adherence in patients with HF; (3) highlight how the term "adherence" was defined and how it was measured across mHealth studies and adherence achieved; and (4) highlight the effect of age, sex, race, New York Heart Association (NYHA) functional classification, and HF etiology (systolic vs diastolic) on exercise adherence. Methods: We searched for papers in PubMed, MEDLINE, and CINAHL databases and included studies published between January 1, 2015, and June 30, 2022. The risk of bias was analyzed. Results: In total, 8 studies (4 randomized controlled trials and 4 quasi-experimental trials) met our inclusion and exclusion criteria. A moderate to high risk of bias was noted in the studies. All studies included patients with HF in NYHA classification I-III, with sample sizes ranging from 12 to 81 and study durations lasting 4 to 26 weeks. Six studies had an equal distribution of male and female participants whose ages ranged between 53 and 73 years. Videoconferencing was used in 4 studies, while 4 studies used smartphone apps. Three studies using videoconferencing included an intervention that engaged participants in a group setting. A total of 1 study used a yoga program, 1 study used a walking program, 1 study combined jogging with walking, 1 study used a cycle ergometer, 2 studies combined walking with cycle ergometry, and 1 study used a stepper. Two studies incorporated resistance exercises in their program. Exercise programs varied, ranging between 3 and 5 days of exercise per week, with exercise sessions ranging from 30 to 60 minutes. The Borg rating of perceived exertion scale was mostly used to regulate exercise intensity, with 3 studies using heart rate monitoring using a Fitbit. Only 1 study implicitly mentions developing their intervention using a theoretical framework. Adherence was reported to the investigator-developed exercise programs. All studies were mostly feasibility or pilot studies, and the effect of age, sex, race, and NYHA classification on exercise adherence with the use of mHealth was not reported. Conclusions: The results show some preliminary evidence of the feasibility of using mHealth technology for building exercise adherence in patients with HF; however, theoretically sound and fully powered studies, including studies on minoritized communities, are lacking. In addition, the sustainability of adherence beyond the intervention period is unknown. Keywords: activity monitors; adherence; age; exercise; exercise programs; feasibility; heart; heart failure; mHealth; mHealth technology; mobile health; mobile phone; race; sex; smartphone; software apps; telehealth technology; videoconferencing.

Using Continuous Glucose Monitoring as a Biological Feedback Strategy to Motivate Physical Activity in Cancer Survivors: A Mixed-Methods Pilot Study (2025)

Cancer Control: Journal of the Moffitt Cancer Center

Authors: Liao, Yue; Brannon, Grace E.; Rethorst, Chad D.; Baum, Miranda; Bevers, Therese B.; Schembre, Susan M.; Basen-Engquist, Karen M.

Abstract

IntroductionIdentifying novel strategies to motivate regular physical activity in cancer survivors continues to be a critical mission, as the majority of cancer survivors are not sufficiently active to achieve the many health benefits of being regularly physically active. Providing biological feedback is one of the behavioral change techniques that shows promising effects in physical activity interventions. This study used a mixed-methods approach to test the acceptability and changes in physical activity motivation of a pilot intervention that provided personalized feedback via text messaging based on data from an activity tracker (Fitbit) and continuous glucose monitor (CGM) over a 4-week period.MethodsTwelve breast and colorectal cancer survivors completed this pilot intervention, which involved a one-on-one educational session followed by a 4-week intervention period with a Fitbit wristband and CGM. They received 2-3 weekly text messages based on their Fitbit and CGM data that aimed to increase their motivation to engage in physical activity. Participants completed surveys assessing motivational readiness before and after the intervention, and a post-intervention survey that assessed acceptability of the intervention. Exit interview was also conducted to collect their feedback and opinions toward the intervention.ResultsBoth quantitative and qualitative results suggest a high acceptability of the study devices (ie, Fitbit and CGM) as well as the intervention components (e.g., the glucose-based biological feedback). Participants reported a significant decrease in the preparation stage and an increase in the action and maintenance stages (ps < 0.05). Results from qualitative analysis further indicate participants' positive changes in physical activity motivations.ConclusionThe use of CGM along with an activity tracker is a viable method to provide personally relevant and motivating biological feedback messages to motivate physical activity in cancer survivors. Future studies can incorporate this behavior change technique into their intervention and further evaluate its impact on behavior change and related health outcomes.Clinical trial number: NCT05124405.

Using Step Trackers Among Older People Receiving Aged Care Services Is Feasible and Acceptable: A Mixed-Methods Study (2025)

Healthcare

Authors: Dawson, Rik; Kay, Judy; Cameron, Lauren; Bucalon, Bernard; Sherrington, Catherine; Haynes, Abby

Abstract

Background: Maintaining physical activity (PA) is vital for older people, particularly those with frailty and mobility limitations. Wearable activity trackers and digital feedback tools show promise for encouraging PA, but their feasibility and acceptability in aged care remain underexplored. This study evaluated the feasibility and acceptability of using wearable and mobile devices for step tracking and examined the usability of three interfaces (Fitbit, mobile app, and website) for reviewing PA progress in aged care. Methods: This is a user experience and feasibility study that does not involve objective physical activity quantification or device performance analysis. It is a mixed-methods feasibility study conducted with 14 participants aged ≥65 years from residential and community aged care services in metropolitan and regional New South Wales, Australia. Participants used a Fitbit Inspire 3 linked to a study website and a mobile phone step-counting app to monitor their steps across the three interfaces for four weeks. Feasibility was evaluated through enrolment and retention, and acceptability through a facilitator-led survey. Quantitative items on usability, comfort, motivation and device preference were summarised descriptively; open-ended responses were analysed thematically to identify user experiences, benefits, and barriers. Results: Step tracking was feasible, with 82\% enrolment and 93\% retention. Participants preferred the Fitbit over the mobile phone or website due to its ease of use, visibility and more enjoyable experience. Step tracking increased awareness of PA and supported confidence to move more. Participants valued reminders, rewards and opportunities for social sharing. Reported barriers included illness, usability challenges and occasional technical issues. Conclusions: Wearable step trackers show promise for supporting PA among older people receiving aged care. Despite the small sample and short follow-up, strong acceptability signals suggest that simple digital tools could enhance the reach and sustainability of mobility-promoting interventions into aged care systems. Future studies should examine long-term adherence, usability across diverse mobility and cognitive needs, and conditions for successful scale-up.

Using Wear Time for the Analysis of Consumer-Grade Wearables' Data: Case Study Using Fitbit Data (2025)

JMIR mHealth and uHealth

Authors: Baroudi, Loubna; Zernicke, Ronald Fredrick; Tewari, Muneesh; Carlozzi, Noelle E.; Choi, Sung Won; Cain, Stephen M.

Abstract

Background: Consumer-grade wearables allow researchers to capture a representative picture of human behavior in the real world over extended periods. However, maintaining users' engagement remains a challenge and can lead to a decrease in compliance (eg, wear time in the context of wearable sensors) over time (eg, "wearables' abandonment"). Objective: In this work, we analyzed datasets from diverse populations (eg, caregivers for various health issues, college students, and pediatric oncology patients) to quantify the impact that wear time requirements can have on study results. We found evidence that emphasizes the need to account for participants' wear time in the analysis of consumer-grade wearables data. In Aim 1, we demonstrate the sensitivity of parameter estimates to different data processing methods with respect to wear time. In Aim 2, we demonstrate that not all research questions necessitate the same wear time requirements; some parameter estimates are not sensitive to wear time. Methods: We analyzed 3 Fitbit datasets comprising 6 different clinical and healthy population samples. For Aim 1, we analyzed the sensitivity of average daily step count and average daily heart rate at the population sample and individual levels to different methods of defining "valid" days using wear time. For Aim 2, we evaluated whether some research questions can be answered with data from lower compliance population samples. We explored (1) the estimation of the average daily step count and (2) the estimation of the average heart rate while walking. Results: For Aim 1, we found that the changes in the population sample average daily step count could reach 2000 steps for different methods of analysis and were dependent on the wear time compliance of the sample. As expected, population samples with a low daily wear time (less than 15 hours of wear time per day) showed the most sensitivity to changes in methods of analysis. On the individual level, we observed that around 15% of individuals had a difference in step count higher than 1000 steps for 4 of the 6 population samples analyzed when using different data processing methods. Those individual differences were higher than 3000 steps for close to 5% of individuals across all population samples. Average daily heart rate appeared to be robust to changes in wear time. For Aim 2, we found that, for 5 population samples out of 6, around 11% of individuals had enough data for the estimation of average heart rate while walking but not for the estimation of their average daily step count. Conclusions: We leveraged datasets from diverse populations to demonstrate the direct relationship between parameter estimates from consumer-grade wearable devices and participants' wear time. Our findings highlighted the importance of a thorough analysis of wear time when processing data from consumer-grade wearables to ensure the relevance and reliability of the associated findings. Keywords: Fitbit; behavior; caregiver; dataset; engagement; mobile health; physical activity; reliability; smartwatch; students; users; walking; wear time; wearable devices; wearables.

Validation of the Caen Chronotype Questionnaire: Exploring the added value of amplitude and correlations with actigraphy (2025)

Chronobiology International

Authors: Hickman, Robert; Lai Jie, Daniel; Shergill, Sukhi; Laborde, Sylvain; D'Oliveira, Teresa C.

Abstract

Chronotype self-report instruments are time and cost-efficient measures to profile diurnal or time-of-day preferences. The Caen Chronotype Questionnaire (CCQ) captures morningness and eveningness (CCQ-ME) and a circadian amplitude dimension for diurnal variation (distinctiveness; CCQ-DI). This study extends prior multilanguage validations for the English version of the CCQ. In total, 628 participants enrolled from a UK working population (mean age 30.34 ± 8.36 years, 61.3\% female) including a subset of shift workers (n = 179; mean age 27.62 ± 5.95 years, 49.2\% female). A subsample of participants also wore a consumer-grade actigraph device (Fitbit Charge 4) for seven days to compare chronotype estimates with objective sleep-wake parameters (n = 22; mean age 27.05 ± 3.99 years, 81.8\% female, 90.9\% worked standard daytime schedules, and 9.1\% worked rotating shifts). All participants completed online chronotype measures, including the CCQ and Morningness-Eveningness Questionnaire (MEQ), depressive symptoms (Patient Health Questionnaire; PHQ-9), sleep quality (Pittsburgh Sleep Quality Index; PSQI), and other outcome measures. Results from the Confirmatory Factor Analysis (CFA) offer support for a two-factor structure of the CCQ in an English-speaking sample, highlighting how individual preferences for the timing of activities is associated with chronotype (morningness-eveningness; ME) and a second subjective amplitude dimension (DI). However, in contrast with the original CCQ structure, a more parsimonious solution and best overall fit involved the reduction of the original 16-item questionnaire (8 items per factor) to 4 ME items and 5 DI items. Convergent validity with the reduced CCQ scale (rME) and the MEQ was also established. The CCQ was sensitive in discriminating differences in actigraphic sleep-wake timings between morning-and evening-oriented individuals. Regression models demonstrated that amplitude (CCQ-DI) was a significant predictor explaining most of the variance in depressive symptoms (PHQ-9) compared to other variables. Overall, the English version of the CCQ was shown to be a robust tool in estimating chronotype in a sample of adults based in the UK.

Wearable Devices in Remote Cardiac Rehabilitation With and Without Weekly Online Coaching for Patients With Coronary Artery Disease: Randomized Controlled Trial (2025)

JMIR mHealth and uHealth

Authors: Nishio, Ryota; Dohi, Tomotaka; Yokoyama, Miho; Nakade, Taisuke; Takahashi, Norihito; Chikata, Yuichi; Endo, Hirohisa; Nishiyama, Hiroki; Okai, Iwao; Iwata, Hiroshi; Okazaki, Shinya; Miyauchi, Katsumi; Daida, Hiroyuki; Minamino, Tohru

Abstract

Background Cardiac rehabilitation (CR) is effective in preventing cardiovascular diseases; however, participation in CR programs remains limited due to the associated challenges. The integration of wearable devices and real-time monitoring offers a potential solution to enhance adherence to remote CR programs and their outcomes. Objective This study aimed to evaluate the efficacy of a remote CR program using wearable devices and real-time monitoring with or without online coaching (OLC) in improving exercise capacity in patients with coronary artery disease (CAD). Methods We enrolled 50 patients with CAD in a remote CR program in this randomized, open-label, single-center pilot trial (phase III). After baseline cardiopulmonary exercise tests (CPETs), all patients were assigned a CPET-based home exercise program and were provided with a wearable device (Fitbit Sense; Fitbit, Inc) with a real-time monitoring system (Recoval; SapplyM, Inc). The patients were randomly assigned to an intervention group with OLC (n=25) or a control wearable device (CON; n=25) group. The primary outcomes were changes in peak oxygen consumption (peak VO2) and anaerobic threshold VO2 (oxygen consumption) at 12 weeks. The secondary outcomes were changes in CPET parameters, daily activity, anxiety levels, and health-related quality of life. Results Peak VO2 and anaerobic threshold VO2 increased significantly from baseline to 12 weeks in the OLC (+1.6 mL/kg/min, P{\textless}.001; +1.0 mL/kg/min, P=.001) and CON (+0.6 mL/kg/min, P=.008; +1.3 mL/kg/min, P=.002) groups with no significant between-group differences (P=.65 and P=.90). In the latter half of the intervention, the daily distance and highly active time in the OLC group were significantly increased compared with those in the CON group (all P{\textless}.05). Mental status and health-related quality of life scores showed no significant differences between the groups. No major adverse cardiac events were reported. One patient in the OLC group dropped out due to lower limb muscle strain. Conclusions Remote CR using wearable devices and a real-time monitoring system significantly improved exercise capacity in patients with CAD over a 12-week intervention program. The addition of regular OLC to the intervention program further enhanced the physical activity levels, particularly in high-intensity activities. Future studies are warranted to validate these findings in more diverse populations and over longer intervention periods to optimize the benefits and safety of remote CR programs.

URL

Wearable technology for mobility measurement in orthopedics and traumatology: a comparison of commercially available systems (2025)

Archives of Orthopaedic and Trauma Surgery

Authors: Keppler, A. M.; Zaccaria, R.; Weigert, M.; Keppler, L.; Böcker, W.; Neuerburg, C.; Schniepp, R.; Fürmetz, J.

Abstract

BACKGROUND: Wearable activity sensors offer valuable insights into physical activity and are increasingly used in clinical and rehabilitation settings. However, most are designed for healthy individuals, necessitating a thorough evaluation of their applicability for pathological gait patterns. This study aims to assess the accuracy of commercially available wearables in measuring gait patterns among patients with lower limb injuries compared to healthy individuals. METHODS: A prospective cohort study enrolled 40 participants divided into four groups: Group A (younger patients with lower limb injuries with age {\textless} 75y), Group B (younger healthy individuals with age 75y), Group C (elderly patients with lower limb injuries and age 75y), and Group D (elderly healthy individuals with age {\textgreater} 75y). Mobility was assessed in real-world scenarios using four wearable devices (Apple Watch Series 4, Fitbit Charge 3, ActivPal 4, and StappOne Insoles V1.0) across three gait speeds in a gait laboratory, with GAITrite mats and video as gold standards. RESULTS: Accuracy varied significantly between devices. The accelerometer-based wearables (Apple Watch Series 4, Fitbit Charge 3 and ActivPal 4™) underestimated cumulative step count compared to pressure-based Stappone v1. 0, especially for slow and restricted gait patterns (Groups C and D). Relative Difference of Wearables Measurements to the true numbers of steps (Group C: AW -21.83\%, FB -28.99\%, AP -20.00\% versus SO 0.00\% - Group D: AW -8.51\%, FB -14.29\%, AP -20.00\% versus SO 4.55\%). Zero measurements occurred frequently with wrist-worn devices, highlighting their limitations in detecting slow or restricted movements. In contrast, pressure-based StappOne Insoles demonstrated superior accuracy, with minimal deviations across all groups and gait speeds. The inaccuracy was exacerbated by factors such as the use of mobility aids, partial weight-bearing, and postoperative restrictions, which altered arm and leg movements. CONCLUSIONS: Accelerometer-based wearables require algorithmic improvements to address the challenges of slow and pathological gait patterns. The frequent occurrence of zero measurements with wrist-worn devices underscores their limited utility in clinical populations. Practical challenges, such as altered movement patterns due to mobility aids and partial weight-bearing, further limit their accuracy. Pressure-based systems, while accurate, face practicality issues for daily use. These findings emphasize the need for tailored wearable technologies for orthopedic and trauma patients. LEVEL OF EVIDENCE: Prospective cohort study, Level of Evidence 2.

A comparison of the rates of clock-based nocturnal hypoglycemia and hypoglycemia whilst asleep among people living with diabetes: findings from the Hypo-METRICS study (2024)

Diabetes Technology \& Therapeutics

Authors: Martine-Edith, Gilberte; Divilly, Patrick; Zaremba, Natalie; Søholm, Uffe; Broadley, Melanie; Baumann, Petra Martina; Mahmoudi, Zeinab; Gomes, Mikel; Ali, Namam; Abbink, Evertine J.; de Galan, Bastiaan E.; Brøsen, Julie Maria Bøggild; Pedersen-Bjergaard, Ulrik; Vaag, Allan A.; McCrimmon, Rory; Renard, Eric; Heller, Simon; Evans, Mark; Cigler, Monika; Mader, Julia K.; Speight, Jane; Pouwer, Frans; Amiel, Stephanie; Choudhary, Pratik

Abstract

Introduction Nocturnal hypoglycemia is generally calculated between 00:00 and 06:00. However, those hours may not accurately reflect sleeping patterns and it is unknown whether this leads to bias. We therefore compared hypoglycemia rates whilst asleep to those of clock-based nocturnal hypoglycemia in adults with type 1 (T1D) or insulin-treated type 2 diabetes (T2D). Methods Participants from the Hypo-METRICS study wore a blinded continuous glucose monitor and a Fitbit Charge 4 activity monitor for 10 weeks. They recorded details of episodes of hypoglycemia using a smartphone app. Sensor-detected hypoglycemia (SDH) and person-reported hypoglycemia (PRH) were categorized as nocturnal (00:00-06:00hrs) vs diurnal and whilst asleep vs awake defined by Fitbit sleeping intervals. Paired sample Wilcoxon tests were used to examine the differences in hypoglycemia rates. Results 574 participants (47\% T1D, 45\% women, 89\% White, median (IQR) age 56 (45-66) years and HbA1c 7.3\% (6.8-8.0)) were included. Median sleep duration was 6.1h (5.2-6.8), bedtime and waking time approximately 23:30 and 07:30 respectively. There were higher median weekly rates of SDH and PRH whilst asleep than clock-based nocturnal SDH and PRH among people with T1D, especially for SDH{\textless}70 mg/dL (1.7 vs 1.4, p{\textless}0.001). Higher weekly rates of SDH whilst asleep than nocturnal SDH were found among people with T2D, especially for SDH{\textless}70 mg/dL (0.8 vs 0.7, p{\textless}0.001). Conclusion Using 00:00 to 06:00 as a proxy for sleeping hours may underestimate hypoglycemia whilst asleep. Future hypoglycemia research should consider the use of sleep trackers to record sleep and reflect hypoglycemia whilst asleep more accurately.

A pilot randomised controlled trial exploring the feasibility and efficacy of a human-AI sleep coaching model for improving sleep among university students (2024)

Digital Health

Authors: Liu, Jintana; Ito, Sakura; Ngo, Tra My; Lawate, Ashwini; Ong, Qi Chwen; Fox, Tatiana Erlikh; Chang, Si Yuan; Phung, Duy; Nair, Elizabeth; Palaiyan, Malar; Joty, Shafiq; Abisheganaden, John; Lee, Chuen Peng; Lwin, May Oo; Theng, Yin Leng; Ho, Moon-Ho Ringo; Chia, Michael; Bojic, Iva; Car, Josip

Abstract

OBJECTIVE: Sleep quality is a crucial concern, particularly among youth. The integration of health coaching with question-answering (QA) systems presents the potential to foster behavioural changes and enhance health outcomes. This study proposes a novel human-AI sleep coaching model, combining health coaching by peers and a QA system, and assesses its feasibility and efficacy in improving university students' sleep quality. METHODS: In a four-week unblinded pilot randomised controlled trial, 59 university students (mean age: 21.9; 64\% males) were randomly assigned to the intervention (health coaching and QA system; n = 30) or the control conditions (QA system; n = 29). Outcomes included efficacy of the intervention on sleep quality (Pittsburgh Sleep Quality Index; PSQI), objective and self-reported sleep measures (obtained from Fitbit and sleep diaries) and feasibility of the study procedures and the intervention. RESULTS: Analysis revealed no significant differences in sleep quality (PSQI) between intervention and control groups (adjusted mean difference = -0.51, 95\% CI: [-1.55-0.77], p = 0.40). The intervention group demonstrated significant improvements in Fitbit measures of total sleep time (adjusted mean difference = 32.5, 95\% CI: [5.9-59.1], p = 0.02) and time in bed (adjusted mean difference = 32.3, 95\% CI: [2.7-61.9], p = 0.03) compared to the control group, although other sleep measures were insignificant. Adherence was high, with the majority of the intervention group attending all health coaching sessions. Most participants completed baseline and post-intervention self-report measures, all diary entries, and consistently wore Fitbits during sleep. CONCLUSIONS: The proposed model showed improvements in specific sleep measures for university students and the feasibility of the study procedures and intervention. Future research may extend the intervention period to see substantive sleep quality improvements.

A pilot randomized controlled trial of a virtual peer-support exercise intervention for female older adults with cancer (2024)

BMC geriatrics

Authors: Smith-Turchyn, Jenna; Sinclair, Susanne; O'Loughlin, Erin K.; Innes, Anthea; Vani, Madison F.; Beauchamp, Marla; Phillips, Stuart M.; Richardson, Julie; Thabane, Lehana; Sabiston, Catherine M.

Abstract

BACKGROUND: Regular exercise can mitigate side effects of cancer treatment. However, only a small proportion of adults with cancer meet exercise guidelines, and older adults ({\textgreater} 65 years) are underrepresented in cancer rehabilitation research. Peer support facilitates health-promoting behaviours in general populations, but interventions merging exercise and peer support for older adults with cancer are not examined. The purpose of this study was to determine the feasibility and preliminary effectiveness of a virtual partner-based peer support exercise intervention for older adult female cancer survivors. METHODS: Older adult female cancer survivors with internet access and currently participating in {\textless} 150 min of moderate-vigorous physical activity per week were included in this study. Participants were matched with a partner and given a peer support guide, exercise guidelines, and a Fitbit Inspire©. In addition, intervention group dyads (AgeMatchPLUS) had weekly 1-h virtual sessions with a qualified exercise professional for 10 weeks. Dyads randomized to the control group (AgeMatch) independently supported their partner around exercise for 10 weeks. The primary outcome was feasibility, measured using retention and adherence rates. Secondary outcomes included exercise volume, social support, quality of life, physical function, and physical activity enjoyment. Descriptive statistics were used to report feasibility and an ANCOVA was used to explore between group differences on secondary outcomes at post-intervention (10 weeks post baseline) and post-tapering timepoints (14 weeks post baseline). RESULTS: Eighteen participants (9 dyads; mean age 72 years (SD: 5.7 years)) were included in the pilot trial. Retention and adherence rates to the AgeMatchPLUS intervention were 100\% and 95\% respectively. All but one participant was satisfied with the quality of their peer match. Preliminary effects were seen between group, favouring AgeMatchPLUS for exercise-related social support post-intervention (effect size (d) = 0.27, 95\% CI = 0,0.54) and physical activity enjoyment at post-tapering (d = 0.25, 95\% CI = 0,0.52) and favouring the AgeMatch group for 30 s sit-to-stand repetitions at post-tapering (d = 0.31, 95\% CI = 0.004, 0.57). No other effects were found. CONCLUSIONS: A virtual partner-based exercise intervention for older adults with cancer is feasible and shows preliminary effect benefits. Findings inform future trials aimed at increasing exercise in older adults with cancer. TRIAL REGISTRATION: Clinicaltrials.gov (ID: NCT05549479, date: 22/09/22).

A Pregnancy and Postnatal RCT Among Women With Gestational Diabetes Mellitus and Overweight/Obesity: The PAIGE2 Study (2024)

Journal of the Endocrine Society

Authors: Kemp, Bridie J.; Kelly, Bronagh; Cupples, Georgina; Fleck, Olwen; McAuley, Emma; Creighton, Rachel M.; Wallace, Helen; Graham, Una; Mulligan, Ciara; Kennedy, Adele; Patterson, Chris C.; McCance, David R.

Abstract

PURPOSE: Resting heart rate (RHR) is a sensitive indicator of an individual's physiologic condition. However, its use in clinical practice has been limited due to the wide variation in baseline RHR based on multiple factors, including age, sex, cardiovascular fitness, and comorbidities. The study aims to develop a novel, clinically meaningful metric that is applicable across these conditions, based on day-by-day changes in RHR-the difference in autocorrelation of daily RHR (ACΔ-RHR). We present ACΔ-RHR in the context of monitoring post-discharge recovery for pediatric appendectomy patients. METHODS: Children 3-17 years old who underwent laparoscopic appendectomy for complicated appendicitis from 2019 to 2022 at a tertiary children's hospital wore a Fitbit for twenty-one postoperative days (POD). Patients without complications were included to describe normative recovery. Using RHR on POD 1-3 as the baseline, autocorrelation of daily RHR was calculated (fixed lag = 1) for POD 3-21. Then, daily ACΔ-RHR was determined by subtracting autocorrelation values between the current and previous day. Means and standard deviations were calculated for daily RHR to estimate on which POD ACΔ-RHR stabilized at 0, representing general RHR stability and recovery from surgery for all patients. Subgroup analyses were performed by age (3-10 years old vs 11-17 years old) and sex. RESULTS: Thirty-one patients were included (58.1 \% 3-10 years old, 41.9 \% female, 67.7 \% Hispanic). Whereas the mean daily RHR did not demonstrate clear trends, the mean ACΔ-RHR for the cohort first reached 0 on POD 12 and stabilized on POD 14 (95 \% confidence interval: POD [11,17]). Subgroup analysis showed that ACΔ-RHR stabilized on POD 9 for age of 3-10 years, POD 12 for age of 11-17 years, POD 12 for females and POD 10 for males. CONCLUSIONS: The ACΔ-RHR is a promising clinical metric that could enhance post-surgical patient monitoring, such as for children following laparoscopic appendectomy for complicated appendicitis.

A Remotely Delivered Light-Intensity Physical Activity Intervention for Older Cancer Survivors: Protocol for a Feasibility Randomized Controlled Trial (2024)

JMIR research protocols

Authors: Blair, Cindy K.; Brown-Glaberman, Ursa; Walters, Scott T.; Pestak, Claire; Boyce, Tawny; Barriga, Laura; Burgess, Ellen; Tawfik, Bernard; Killough, Cynthia; Kinney, Anita Y.; Demark-Wahnefried, Wendy; Meisner, Angela L.; Wiggins, Charles L.; Pankratz, V. Shane; Davis, Sally

Abstract

Background: Older cancer survivors face age- and treatment-related comorbidities, including physical functional impairment, which are exacerbated by physical inactivity and sedentary behavior. Regular physical activity can reduce this risk, yet less than 30% of older cancer survivors meet the recommended guidelines for physical activity. Objective: This study aims to describe the design, methods, and rationale for a remotely delivered intervention that uses a whole-of-day approach to physical activity in older cancer survivors. This approach focuses on the accumulation of intermittent bouts of light-intensity activity throughout the entire day by disrupting and reducing sedentary activity. The intervention was guided by social cognitive and self-determination theories and incorporated motivational interviewing. Methods: The 12-week Move for Your Health trial randomly assigned 64 older cancer survivors to a theory-based physical activity intervention or a waitlist control. A Fitbit (Google) activity tracker and smartphone app were used to promote awareness of activity levels and enable self-monitoring of both activity and inactivity in tandem with health coaching phone calls. Motivational interviewing was used to engage participants and tailor strategies to achieve goals during the 12-week intervention. Data were collected at baseline, immediately after the intervention, and at longer-term follow-up (3 months thereafter). Feasibility outcomes included recruitment, retention, adherence, adverse events, and acceptability. Other outcomes included obtaining the parameter estimates for changes in physical function, physical performance, physical activity, sedentary behavior, and quality of life. Results: Recruitment for the Move for Your Health randomized controlled trial was completed in June 2023. Data collection was completed in March 2024. Data analyses are ongoing. Conclusions: The results of this trial will provide information on the feasibility of implementing this intervention in the target patient population, as well as data that will provide information about the potential impact of the intervention on the outcomes. Both of these outcomes will inform the design of a larger randomized controlled trial to more fully test a physical activity intervention in an older cancer survivor population. Trial registration: ClinicalTrials.gov NCT05582889; https://clinicaltrials.gov/study/NCT05582889. International registered report identifier (irrid): DERR1-10.2196/59504. Keywords: activity tracker; cancer survivor; mobile phone; older adults; physical activity; physical function; physical performance.

A single-armed proof-of-concept study of Lymfit: A personalized, virtual exercise intervention to improve health outcomes in lymphoma survivors in the pandemic (2024)

PloS One

Authors: Angelillo, Christopher; Tock, Wing Lam; Salaciak, Matthew; Reid, Ryan E. R.; Andersen, Ross E.; Maheu, Christine; Johnson, Nathalie A.

Abstract

Background and objective: Treatments of lymphoma can lead to reduced physical functioning, cancer-related fatigue, depression, anxiety, and insomnia. These side effects can negatively impact the cancer survivor's quality of life. Mounting evidence indicates that physical activities are highly therapeutic in mitigating the short- and long-term side effects of cancer treatments. Yet, lymphoma survivors' participation in physical activities remains suboptimal, which has been further exacerbated by the deleterious effects of isolation during the COVID-19 pandemic. The Lymfit intervention aims to offer motivational support, expert guidance, and a personalized exercise prescription to optimize physical activities among lymphoma survivors. This proof-of-concept study explores implementation feasibility (retention, technical and safety), and the preliminary effects of Lymfit on various health outcomes. Method: This was a single-armed trial with a pre-and post-test design. Twenty lymphoma survivors were recruited to participate in the 12-week Lymfit intervention. Wearable activity trackers (Fitbit) were given to participants as a motivational tool and for data collection purposes. Participants received a personalized exercise prescription designed by a kinesiologist. Physiologic metrics were collected by the Fitbit monitors and were stored in the Lymfit database. Self-reported questionnaires measuring health outcomes were collected at baseline and post-intervention. Results: The retention rate of this trial was 70%. Minimal technical issues and no adverse effects were reported. Lymfit led to significant improvements in sleep disturbances and the ability to participate in social activities and decreased fear of cancer recurrence. It also increased daily steps and decreased sedentary time in participants who did not meet the recommended physical activity guidelines. Significance: With access to resources and fitness centers being limited during the pandemic, the Lymfit intervention filled an immediate need to provide physical activity guidance to lymphoma survivors. Findings provide preliminary support that implementing the Lymfit intervention is feasible and demonstrated promising results.

Accuracy of Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP Versus Polysomnography: Systematic Review (2024)

JMIR mHealth and uHealth

Authors: Schyvens, An-Marie; Van Oost, Nina Catharina; Aerts, Jean-Marie; Masci, Federica; Peters, Brent; Neven, An; Dirix, Hélène; Wets, Geert; Ross, Veerle; Verbraecken, Johan

Abstract

BACKGROUND: Despite being the gold-standard method for objectively assessing sleep, polysomnography (PSG) faces several limitations as it is expensive, time-consuming, and labor-intensive; requires various equipment and technical expertise; and is impractical for long-term or in-home use. Consumer wrist-worn wearables are able to monitor sleep parameters and thus could be used as an alternative for PSG. Consequently, wearables gained immense popularity over the past few years, but their accuracy has been a major concern. OBJECTIVE: A systematic review of the literature was conducted to appraise the performance of 3 recent-generation wearable devices (Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP) in determining sleep parameters and sleep stages. METHODS: Per the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement, a comprehensive search was conducted using the PubMed, Web of Science, Google Scholar, Scopus, and Embase databases. Eligible publications were those that (1) involved the validity of sleep data of any marketed model of the candidate wearables and (2) used PSG or an ambulatory electroencephalogram monitor as a reference sleep monitoring device. Exclusion criteria were as follows: (1) incorporated a sleep diary or survey method as a reference, (2) review paper, (3) children as participants, and (4) duplicate publication of the same data and findings. RESULTS: The search yielded 504 candidate articles. After eliminating duplicates and applying the eligibility criteria, 8 articles were included. WHOOP showed the least disagreement relative to PSG and Sleep Profiler for total sleep time (-1.4 min), light sleep (-9.6 min), and deep sleep (-9.3 min) but showed the largest disagreement for rapid eye movement (REM) sleep (21.0 min). Fitbit Charge 4 and Garmin Vivosmart 4 both showed moderate accuracy in assessing sleep stages and total sleep time compared to PSG. Fitbit Charge 4 showed the least disagreement for REM sleep (4.0 min) relative to PSG. Additionally, Fitbit Charge 4 showed higher sensitivities to deep sleep (75\%) and REM sleep (86.5\%) compared to Garmin Vivosmart 4 and WHOOP. CONCLUSIONS: The findings of this systematic literature review indicate that the devices with higher relative agreement and sensitivities to multistate sleep (ie, Fitbit Charge 4 and WHOOP) seem appropriate for deriving suitable estimates of sleep parameters. However, analyses regarding the multistate categorization of sleep indicate that all devices can benefit from further improvement in the assessment of specific sleep stages. Although providers are continuously developing new versions and variants of wearables, the scientific research on these wearables remains considerably limited. This scarcity in literature not only reduces our ability to draw definitive conclusions but also highlights the need for more targeted research in this domain. Additionally, future research endeavors should strive for standardized protocols including larger sample sizes to enhance the comparability and power of the results across studies.

Accuracy of smartwatches for the remote assessment of exercise capacity (2024)

Scientific Reports

Authors: Jamieson, Alexandra; Jones, Siana; Chaturvedi, Nishi; Hughes, Alun D.; Orini, Michele

Abstract

Exercise capacity is a strong independent predictor of cardiovascular and all-cause mortality. The utilization of well-established submaximal tests of exercise capacity such as the 6-min walk test (6MWT), 3-min step test (3MST) and 10-chair rise test (10CRT) in the community would improve patient care but requires remote monitoring technology. Consumer grade smartwatches provide such an opportunity, however, their accuracy in measuring physiological responses to these tests is unclear. The aim of this study was to determine the accuracy of consumer grade smartwatches in assessing exercise capacity to develop a framework for remote, unsupervised testing. 16 healthy adults (7 male (44\%), age median 27 [interquartile range (IQR) 26,29] years) performed 6MWTs using two protocols: (1) standard-straight 30 m laps (6MWT-standard) and 2) continuous lap-circular 240 m laps around a park (6MWT-continuous lap), 3MSTs and 10CRTs. Each one of these four tests was performed three times across two clinic visits. Each participant was fitted with a Garmin Vivoactive4 and Fitbit Sense smartwatch to measure three parameters: distance, step counts and heart rate (HR) response. Reference measures were a meter-wheel, hand tally counter and ECG, respectively. Mean HR was measured at rest, peak exercise and recovery. Agreement was measured using Bland-Altman analysis for repeated measures and summarized as median absolute percentage errors (MAPE). Distance during 6MWT-continuous lap had better agreement than during 6MWT-standard for both Garmin (MAPE: 6.4\% [3.0, 10.4\%] versus 20.1\% [13.9, 28.4\%], p {\textless} 0.001) and Fitbit (8.0\% [2.9, 10.1\% versus 18.8\% [15.2, 28.1\%], p {\textless} 0.001). Garmin measured step count more accurately than Fitbit (MAPE: 1.8\% [0.9, 2.9\%] versus 8.0\% [2.6, 12.3\%], p {\textless} 0.001). Irrespective of test, both devices showed excellent accuracy in measuring HR at rest and recovery (≤ 3\%), while accuracy decreased during peak exercise (Fitbit: {\textasciitilde} 12\% and Garmin: {\textasciitilde} 7\%). In young adults without mobility difficulties, exercise capacity can be measured remotely using standardized tests and consumer grade smartwatches.

Actívatexto: Feasibility and Acceptability of a Mobile Intervention That Promotes Smoking Cessation and Physical Activity among Latinos (2024)

Cancer Research Communications

Authors: Lara, Daimarelys; Alaniz-Cantú, Edgar I.; Siddalingaiaha, Simran; Oliveira, Igor; Chávez-Iñiguez, Arlette; DeJesus, Elisa; Fuller, Daniel; Marquez, David X.; Vásquez, Elizabeth; Li, Dongmei; McIntosh, Scott; Ossip, Deborah J.; Cupertino, Ana Paula; Cartujano-Barrera, Francisco

Abstract

The purpose of this study was to assess the feasibility and acceptability of a mobile intervention that promotes smoking cessation and physical activity among Latinos living in the United States. Twenty Latino adults who smoked and did not meet recommended levels of physical activity were recruited using community-based recruitment strategies. Participants received Actívatexto, a theory-based, culturally accommodated, 12-week text messaging intervention (available in English and Spanish) that promotes smoking cessation and physical activity. Actívatexto integrates four components: (i) a text messaging program, (ii) a wearable device, (iii) an online dashboard where the research team manages participants' incoming and outgoing data from both the text messaging program and wearable device, and (iv) nicotine replacement therapies (NRT). We assessed self-reported 7-day point prevalence smoking abstinence at month 3, weekly minutes of moderate to vigorous physical activity (MVPA), pharmacotherapy adherence, and satisfaction. At baseline, participants' mean age was 47.3 years old (SD 16.0), 55\% of participants were female, and 60\% indicated that Spanish was their language of preference. Seventy-five percent of participants smoked 1-10 cigarettes daily and 35\% smoked their first cigarette within 5 minutes after waking up. At month 3, 14 participants (70\%) self-reported 7-day point prevalence smoking abstinence (90\% follow-up rate). Fitbit-assessed mean minutes of MVPA per week increased from 113 (SD 127; range: 0-399) at week 1 to 177 (SD 163; range: 0-513) at month 3 (P = 0.15). Sixteen participants (88.9\%, 16/18) reported NRT use in the past 90 days. Most participants reported being extremely satisfied or satisfied with the intervention (88.9\%, 16/18). SIGNIFICANCE: Actívatexto resulted in a noteworthy cessation rate at month 3 (70\%), increased mean weekly minutes of MVPA, produced high use of NRT, and was well received by participants. Additional testing in a randomized clinical trial is warranted to assess the efficacy of the intervention.

Adolescents' Daily Lives (ADL) project: an intensive longitudinal design study protocol examining the associations between physical literacy, movement behaviours, emotion regulation and mental health (2024)

BMJ open

Authors: Ames, Megan; Srinivasa Gopalan, Sharan; Sihoe, C. Emmett; Craig, Stephanie G.; Garcia-Barrera, Mauricio; Liu, Sam; Rhodes, Ryan; Rush, Jonathan; Buckler, E. Jean

Abstract

Introduction: Adolescence represents a critical developmental period, with changes in emotional regulation capacities influencing physical and mental health. With less than 6% of Canadian youth currently meeting the 24-hour movement guidelines for physical activity, sleep and sedentary behaviour, there is an urgent need to understand the potential association between movement behaviours, physical literacy, emotional regulation and mental health during adolescence. Additionally, there is a need to better understand these associations among equity-deserving groups. We developed the Adolescents' Daily Lives (ADL) project to identify how, when, under what contexts and to whom to promote healthy engagement in movement behaviours to optimise youth mental health. Methods and analysis: For the ADL project, we will employ a 14-day intensive longitudinal design to investigate the associations between physical literacy, movement behaviours, emotion regulation and mental health among a diverse sample of 120 adolescents (ages 13-17 years) living in the Greater Victoria Area, British Columbia, Canada. A comprehensive baseline survey and movement competence test, assessing physical and mental well-being, 24-hour movement behaviours (ie, physical activity, sleep and sedentary behaviours) and physical literacy, will be accompanied by daily diary surveys and accelerometer-based movement tracking (ie, Fitbit Inspire 3) to assess daily fluctuations in movement behaviour, emotional regulation and mood. Multivariate analyses, including multilevel modelling, multilevel structural equation modelling and Bayesian hierarchical continuous-time SEM, will be used to model the repeated measures data and understand the simultaneous variations in daily movement behaviours, emotion regulation and mental health. Ethics and dissemination: The ADL project received ethical approval from the University of Victoria Behavioural Research Ethics Board (protocol #22-0262). Study participation is voluntary, and data collection will be anonymised to protect participant privacy and confidentiality. Research findings will be shared through academic publications and conference proceedings. Through knowledge mobilisation resources, cocreated with the youth community advisory board, relevant findings will be shared directly with the wider community of adolescents. Keywords: Adolescents; Child; Exercise; MENTAL HEALTH.

An Outdoor Walking Program for Immigrant Muslim Older Adults: A Community-Based Participatory Intervention (2024)

Nursing Open

Authors: Salma, Jordana; Yamamoto, Shelby; Salbach, Nancy M.; Barclay, Ruth; Jones, Allyson

Abstract

AIM: To explore Muslim immigrant older adults' experiences of a modified community-based outdoor walking program and identify factors that facilitate or hinder program acceptance and participation. DESIGN: An exploratory qualitative description single-group pilot study was designed and implemented in three phases: (1) pre-intervention focus group interviews; (2) intervention implementation with tracking of physical activity levels using personal activity monitors; and (3) postintervention individual interviews. METHODS: Participants were recruited using a convenience sampling strategy in a mosque in Edmonton, Canada, in June 2019. After focus group discussions with participants, walking sessions were conducted for 10 weeks in a local accessible park with required amenities such as benches and restrooms. A fitness instructor delivered the weekly program that was followed by individual semistructured interviews to explore participants' satisfaction and program acceptance. Content analysis was used for qualitative data and sociodemographic, health and physical activity level (via step counts) data was documented for all participants. RESULTS: Thirteen participants with a mean age of 66.9 years completed the program. The majority of participants led a sedentary lifestyle. Participants identified three motivators that increased program satisfaction, which were socialising with peers, having a fitness instructor, and using Fitbit activity trackers. Difficulties with transportation and lack of appropriate educational components were areas for improvement that could enhance acceptability of the program. CONCLUSIONS: This study suggests that early incorporation of older immigrants' preferences increases acceptance of physical activity programs. IMPLICATIONS: Nurses' engaging in healthy lifestyle support for older immigrants can identify the influences on positive uptake of physical activity programs in this population. IMPACT: Immigrant Muslim older adults lack access to evidence-based physical activity programming that meets their cultural and religious preferences. This study provides some insights into ways to engage this population in similar programs. PATIENT OR PUBLIC CONTRIBUTION: Community-dwelling older adults who participated in this study completed focus groups and interviews and engaged in the 10-week pilot intervention. Their input informed the modifications to the intervention.

Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study (2024)

Journal of Medical Internet Research

Authors: Singh, Rujul; Tetrick, Macy K.; Fisher, James L.; Washington, Peter; Yu, Jane; Paskett, Electra D.; Penedo, Frank J.; Clinton, Steven K.; Benzo, Roberto M.

Abstract

BACKGROUND: To date, no studies have examined adherence to the 2018 Physical Activity Guidelines for Americans (PAGA) in real-world longitudinal settings using objectively measured activity monitoring data. This study addresses this gap by using commercial activity monitoring (Fitbit) data from the All of Us dataset. OBJECTIVE: The primary objectives were to describe the prevalence of adherence to the 2018 PAGA and identify associated sociodemographic determinants. Additionally, we compared 3 distinct methods of processing physical activity (PA) data to estimate adherence to the 2008 PAGA. METHODS: We used the National Institutes of Health's All of Us dataset, which contains minute-level Fitbit data for 13,947 US adults over a 7-year time span (2015-2022), to estimate adherence to PAGA. A published step-based method was used to estimate metabolic equivalents and assess adherence to the 2018 PAGA (ie, ≥150 minutes of moderate- to vigorous-intensity PA per week). We compared the step-based method, the heart rate-based method, and the proprietary Fitbit-developed algorithm to estimate adherence to the 2008 PAGA. RESULTS: The average overall adherence to the 2018 PAGA was 21.6\% (3006/13,947; SE 0.4\%). Factors associated with lower adherence in multivariate logistic regression analysis included female sex (relative to male sex; adjusted odds ratio [AOR] 0.66, 95\% CI 0.60-0.72; P{\textless}.001); BMI of 25.0-29.9 kg/m2 (AOR 0.53, 95\% CI 0.46-0.60; P{\textless}.001), 30-34.9 kg/m2 (AOR 0.30, 95\% CI 0.25-0.36; P{\textless}.001), or ≥35 kg/m2 (AOR 0.13, 95\% CI 0.10-0.16; P{\textless}.001; relative to a BMI of 18.5-24.9 kg/m2); being aged 30-39 years (AOR 0.66, 95\% CI 0.56-0.77; P{\textless}.001), 40-49 years (AOR 0.79, 95\% CI 0.68-0.93; P=.005), or ≥70 years (AOR 0.74, 95\% CI 0.62-0.87; P{\textless}.001; relative to being 18-29 years); and non-Hispanic Black race or ethnicity (AOR 0.63, 95\% CI 0.50-0.79; P{\textless}.001; relative to non-Hispanic White race or ethnicity). The Fitbit algorithm estimated that a larger percentage of the sample (10,307/13,947, 73.9\%; 95\% CI 71.2-76.6) adhered to the 2008 PAGA compared to the heart rate method estimate (4740/13,947, 34\%; 95\% CI 32.8-35.2) and the step-based method (1401/13,947, 10\%; 95\% CI 9.4-10.6). CONCLUSIONS: Our results show significant sociodemographic differences in PAGA adherence and notably different estimates of adherence depending on the algorithm used. These findings warrant the need to account for these disparities when implementing PA interventions and the need to establish an accurate and reliable method of using commercial accelerometers to examine PA, particularly as health care systems begin integrating wearable device data into patient health records.

Assessing the current utilization status of wearable devices in clinical research (2024)

Clinical Trials (London, England)

Authors: Miyakoshi, Takashi; Ito, Yoichi M.

Abstract

Background/aims: Information regarding the use of wearable devices in clinical research, including disease areas, intervention techniques, trends in device types, and sample size targets, remains elusive. Therefore, we conducted a comprehensive review of clinical research trends related to wristband wearable devices in research planning and examined their applications in clinical investigations. Methods: As this study identified trends in the adoption of wearable devices during the planning phase of clinical research, including specific disease areas and targeted number of intervention cases, we searched ClinicalTrials.gov-a prominent platform for registering and disseminating clinical research. Since wrist-worn devices represent a large share of the market, we focused on wrist-worn devices and selected the most representative models among them. The main analysis focused on major wearable devices to facilitate data analysis and interpretation, but other wearables were also surveyed for reference. We searched ClinicalTrials.gov with the keywords "ActiGraph,""Apple Watch,""Empatica,""Fitbit,""Garmin," and "wearable devices" to obtain studies published up to 21 August 2022. This initial search yielded 3214 studies. After excluding duplicate National Clinical Trial studies (the overlap was permissible among different device types except for wearable devices), our analysis focused on 2930 studies, including simple, time-series, and type-specific assessments of various variables. Results: Overall, an increasing number of clinical studies have incorporated wearable devices since 2012. While ActiGraph and Fitbit initially dominated this landscape, the use of other devices has steadily increased, constituting approximately 10% of the total after 2015. Observational studies outnumbered intervention studies, with behavioral and device-based interventions being particularly prevalent. Regarding disease types, cancer and cardiovascular diseases accounted for approximately 20% of the total. Notably, 114 studies adopted multiple devices simultaneously within the context of their clinical investigations. Conclusions: Our findings revealed that the utilization of wearable devices for data collection and behavioral interventions in various disease areas has been increasing over time since 2012. The increase in the number of studies over the past 3 years has been particularly significant, suggesting that this trend will continue to accelerate in the future. Devices and their evaluation methods that have undergone thorough validation, confirmed their accuracy, and adhered to established legal regulations will likely assume a pivotal role in evaluations, allowing for remote clinical trials. Moreover, behavioral intervention therapy utilizing apps is becoming more extensive, and we expect to see more examples that will lead to their approval as programmed medical devices in the future. Keywords: ActiGraph; Apple Watch; Empatica; Fitbit; Garmin; clinical trial; disease area; intervention; observational study; wearable device.

Association of physical activity and screen time with cardiovascular disease risk in the Adolescent Brain Cognitive Development Study (2024)

BMC public health

Authors: Nagata, Jason M.; Weinstein, Shayna; Alsamman, Sana; Lee, Christopher M.; Dooley, Erin E.; Ganson, Kyle T.; Testa, Alexander; Gooding, Holly C.; Kiss, Orsolya; Baker, Fiona C.; Pettee Gabriel, Kelley

Abstract

Background: According to the Physical Activity Guidelines Advisory Committee Scientific Report, limited evidence is available on sedentary behaviors (screen time) and their joint associations with physical activity (steps) for cardiovascular health in adolescence. The objective of this study was to identify joint associations of screen time and physical activity categories with cardiovascular disease (CVD) risk factors (blood pressure, hemoglobin A1c, cholesterol) in adolescence. Methods: This study analyzed data from the Adolescent Brain Cognitive Development (ABCD) Study, comprising a diverse sample of 4,718 U.S. adolescents aged 10-15 years between 2018 and 2021. Steps were measured by a Fitbit wearable device and levels were categorized as low (1,000-6,000), medium (> 6,000-12,000), and high (> 12,000) averaged daily step counts. Self-reported recreational screen time hours per day were classified as low (0-4), medium (> 4-8), and high (> 8) hours per day. CVD risk factors including blood pressure, hemoglobin A1c, and cholesterol (total and HDL) were measured. Results: The analytical sample averaged 6.6 h of screen time per day and 9,722 steps per day. In models including both screen time and steps, the high screen time category was associated with a 4.27 higher diastolic blood pressure percentile (95% CI 1.83-6.73) and lower HDL cholesterol (B= -2.85, 95% CI -4.77 to -0.94 mg/dL) compared to the low screen time category. Medium (B = 3.68, 95% CI 1.24-6.11) and low (B = 7.64, 95% CI 4.07-11.20) step categories were associated with higher diastolic blood pressure percentile compared to the high step category. The medium step category was associated with lower HDL cholesterol (B= -1.99, 95% CI -3.80 to -0.19 mg/dL) compared to the high step category. Findings were similar when screen time and step counts were analyzed as continuous variables; higher continuous step count was additionally associated with lower total cholesterol (mg/dL). Conclusions: Combinations of low screen time and high steps were generally associated with favorable cardiovascular health markers including lower diastolic blood pressure and higher HDL cholesterol, which can inform future adolescent health guidelines. Keywords: Adolescent; Blood pressure; Cardiovascular disease; Cholesterol; Diabetes; Digital media; Dyslipidemia; Hemoglobin A1c; Hypertension; Physical activity; Screen use.

Association of Remote Patient-Reported Outcomes and Step Counts With Hospitalization or Death Among Patients With Advanced Cancer Undergoing Chemotherapy: Secondary Analysis of the PROStep Randomized Trial (2024)

Journal of Medical Internet Research

Authors: Manz, Christopher R.; Schriver, Emily; Ferrell, William J.; Williamson, Joelle; Wakim, Jonathan; Khan, Neda; Kopinsky, Michael; Balachandran, Mohan; Chen, Jinbo; Patel, Mitesh S.; Takvorian, Samuel U.; Shulman, Lawrence N.; Bekelman, Justin E.; Barnett, Ian J.; Parikh, Ravi B.

Abstract

Background: Patients with advanced cancer undergoing chemotherapy experience significant symptoms and declines in functional status, which are associated with poor outcomes. Remote monitoring of patient-reported outcomes (PROs; symptoms) and step counts (functional status) may proactively identify patients at risk of hospitalization or death. Objective: The aim of this study is to evaluate the association of (1) longitudinal PROs with step counts and (2) PROs and step counts with hospitalization or death. Methods: The PROStep randomized trial enrolled 108 patients with advanced gastrointestinal or lung cancers undergoing cytotoxic chemotherapy at a large academic cancer center. Patients were randomized to weekly text-based monitoring of 8 PROs plus continuous step count monitoring via Fitbit (Google) versus usual care. This preplanned secondary analysis included 57 of 75 patients randomized to the intervention who had PRO and step count data. We analyzed the associations between PROs and mean daily step counts and the associations of PROs and step counts with the composite outcome of hospitalization or death using bootstrapped generalized linear models to account for longitudinal data. Results: Among 57 patients, the mean age was 57 (SD 10.9) years, 24 (42%) were female, 43 (75%) had advanced gastrointestinal cancer, 14 (25%) had advanced lung cancer, and 25 (44%) were hospitalized or died during follow-up. A 1-point weekly increase (on a 32-point scale) in aggregate PRO score was associated with 247 fewer mean daily steps (95% CI -277 to -213; P<.001). PROs most strongly associated with step count decline were patient-reported activity (daily step change -892), nausea score (-677), and constipation score (524). A 1-point weekly increase in aggregate PRO score was associated with 20% greater odds of hospitalization or death (adjusted odds ratio [aOR] 1.2, 95% CI 1.1-1.4; P=.01). PROs most strongly associated with hospitalization or death were pain (aOR 3.2, 95% CI 1.6-6.5; P<.001), decreased activity (aOR 3.2, 95% CI 1.4-7.1; P=.01), dyspnea (aOR 2.6, 95% CI 1.2-5.5; P=.02), and sadness (aOR 2.1, 95% CI 1.1-4.3; P=.03). A decrease in 1000 steps was associated with 16% greater odds of hospitalization or death (aOR 1.2, 95% CI 1.0-1.3; P=.03). Compared with baseline, mean daily step count decreased 7% (n=274 steps), 9% (n=351 steps), and 16% (n=667 steps) in the 3, 2, and 1 weeks before hospitalization or death, respectively. Conclusions: In this secondary analysis of a randomized trial among patients with advanced cancer, higher symptom burden and decreased step count were independently associated with and predictably worsened close to hospitalization or death. Future interventions should leverage longitudinal PRO and step count data to target interventions toward patients at risk for poor outcomes. Trial registration: ClinicalTrials.gov NCT04616768; https://clinicaltrials.gov/study/NCT04616768. International registered report identifier (irrid): RR2-10.1136/bmjopen-2021-054675. Keywords: accelerometer; accelerometers; cancer; chemotherapy; death; gastrointestinal cancer; hospitalization; lung cancer; mobile phone; monitoring; oncology; patient-generated health data; patient-reported outcomes; risk; step counts; symptom burden; symptoms; wearables.

Associations between sleep health, negative reinforcement learning, and alcohol use among South Florida college students with elevated internalizing symptoms (2024)

Alcohol (Fayetteville, N.Y.)

Authors: Sollenberger, Nathan A.; Cummings, Logan R.; Freitag, Josefina; Trucco, Elisa M.; Gomez, Sthefany; Giraldo, Melanie; Muse, Gabriela; Mattfeld, Aaron T.; McMakin, Dana L.

Abstract

Negative reinforcement is proposed to mediate associations between sleep and alcohol use, especially among people with depression and/or anxiety symptoms. Worse sleep (e.g., shorter duration, less efficiency, more irregular timing) exacerbates negative emotions, which alcohol may temporarily relieve. Not yet examined, we propose sleep indirectly impacts early stages of alcohol use via differences in negative reinforcement learning (NRL), since sleep impacts emotion, reward response, and learning. The current study aimed to replicate associations between sleep and alcohol use, test associations with NRL, and examine indirect associations between sleep health and alcohol use via NRL among 60 underage college students (ages 18-20 years, 77\% female) varying in depression and anxiety symptoms. Participants wore Fitbit smartwatches and completed daily diaries measuring sleep and substance use for ∼14 days before completing two computer tasks assessing social (SNRL) and monetary (MNRL) negative reinforcement learning. Robust generalized linear models tested direct associations within the proposed model. SNRL performance was positively associated with alcohol use, but no other associations were observed. Statistical mediation models failed to indicate indirect effects of sleep on alcohol use via SNRL or MNRL performance. Post-hoc exploratory models examining depression and anxiety symptoms as moderators of direct associations indicated several interactions. Positive associations between sleep timing variability and alcohol use were weakened at higher anxiety symptom severity and stronger at higher depression symptom severity. The positive association between SNRL performance and alcohol use was also stronger at higher depression symptom severity. Among students with elevated depression symptoms, variable sleep timing and stronger SNRL performance were independently associated with more alcohol use, but indirect effects were not supported. Future research should replicate findings, confirm causality of interactions, and examine sleep timing and behavioral responses to negative social stimuli as targets for improving alcohol-related outcomes among underage college students with elevated depressive symptoms.

Autocorrelation of daily resting heart rate: A novel metric of postoperative recovery (2024)

International Journal of Medical Informatics

Authors: Carter, Michela; Hua, Rui; O'Brien, Megan K.; Benjamin Pitt, J.; Kwon, Soyang; Jayaraman, Arun; Mk Ghomrawi, Hassan; Abdullah, Fizan

Abstract

Purpose: Resting heart rate (RHR) is a sensitive indicator of an individual's physiologic condition. However, its use in clinical practice has been limited due to the wide variation in baseline RHR based on multiple factors, including age, sex, cardiovascular fitness, and comorbidities. The study aims to develop a novel, clinically meaningful metric that is applicable across these conditions, based on day-by-day changes in RHR-the difference in autocorrelation of daily RHR (ACΔ-RHR). We present ACΔ-RHR in the context of monitoring post-discharge recovery for pediatric appendectomy patients. Methods: Children 3-17 years old who underwent laparoscopic appendectomy for complicated appendicitis from 2019 to 2022 at a tertiary children's hospital wore a Fitbit for twenty-one postoperative days (POD). Patients without complications were included to describe normative recovery. Using RHR on POD 1-3 as the baseline, autocorrelation of daily RHR was calculated (fixed lag = 1) for POD 3-21. Then, daily ACΔ-RHR was determined by subtracting autocorrelation values between the current and previous day. Means and standard deviations were calculated for daily RHR to estimate on which POD ACΔ-RHR stabilized at 0, representing general RHR stability and recovery from surgery for all patients. Subgroup analyses were performed by age (3-10 years old vs 11-17 years old) and sex. Results: Thirty-one patients were included (58.1 % 3-10 years old, 41.9 % female, 67.7 % Hispanic). Whereas the mean daily RHR did not demonstrate clear trends, the mean ACΔ-RHR for the cohort first reached 0 on POD 12 and stabilized on POD 14 (95 % confidence interval: POD [11,17]). Subgroup analysis showed that ACΔ-RHR stabilized on POD 9 for age of 3-10 years, POD 12 for age of 11-17 years, POD 12 for females and POD 10 for males. Conclusions: The ACΔ-RHR is a promising clinical metric that could enhance post-surgical patient monitoring, such as for children following laparoscopic appendectomy for complicated appendicitis. Keywords: Appendectomy; Autocorrelation; Consumer wearable devices; Fitbit; Pediatrics; Postoperative care; Remote sensing technology; Resting heart rate.

Comparison of raw accelerometry data from ActiGraph, Apple Watch, Garmin, and Fitbit using a mechanical shaker table (2024)

PloS One

Authors: White, James W.; Finnegan, Olivia L.; Tindall, Nick; Nelakuditi, Srihari; Brown, David E.; Pate, Russell R.; Welk, Gregory J.; de Zambotti, Massimiliano; Ghosal, Rahul; Wang, Yuan; Burkart, Sarah; Adams, Elizabeth L.; Chandrashekhar, Mvs; Armstrong, Bridget; Beets, Michael W.; Weaver, R. Glenn

Abstract

The purpose of this study was to evaluate the reliability and validity of the raw accelerometry output from research-grade and consumer wearable devices compared to accelerations produced by a mechanical shaker table. Raw accelerometry data from a total of 40 devices (i.e., n = 10 ActiGraph wGT3X-BT, n = 10 Apple Watch Series 7, n = 10 Garmin Vivoactive 4S, and n = 10 Fitbit Sense) were compared to reference accelerations produced by an orbital shaker table at speeds ranging from 0.6 Hz (4.4 milligravity-mg) to 3.2 Hz (124.7mg). Two-way random effects absolute intraclass correlation coefficients (ICC) tested inter-device reliability. Pearson product moment, Lin's concordance correlation coefficient (CCC), absolute error, mean bias, and equivalence testing were calculated to assess the validity between the raw estimates from the devices and the reference metric. Estimates from Apple, ActiGraph, Garmin, and Fitbit were reliable, with ICCs = 0.99, 0.97, 0.88, and 0.88, respectively. Estimates from ActiGraph, Apple, and Fitbit devices exhibited excellent concordance with the reference CCCs = 0.88, 0.83, and 0.85, respectively, while estimates from Garmin exhibited moderate concordance CCC = 0.59 based on the mean aggregation method. ActiGraph, Apple, and Fitbit produced similar absolute errors = 16.9mg, 21.6mg, and 22.0mg, respectively, while Garmin produced higher absolute error = 32.5mg compared to the reference. ActiGraph produced the lowest mean bias 0.0mg (95\%CI = -40.0, 41.0). Equivalence testing revealed raw accelerometry data from all devices were not statistically significantly within the equivalence bounds of the shaker speed. Findings from this study provide evidence that raw accelerometry data from Apple, Garmin, and Fitbit devices can be used to reliably estimate movement; however, no estimates were statistically significantly equivalent to the reference. Future studies could explore device-agnostic and harmonization methods for estimating physical activity using the raw accelerometry signals from the consumer wearables studied herein.

Criterion-Related Validity of Consumer-Wearable Activity Trackers for Estimating Steps in Primary Schoolchildren under Controlled Conditions: Fit-Person Study (2024)

Journal of Sports Science \& Medicine

Authors: Mayorga-Vega, Daniel; Casado-Robles, Carolina; Guijarro-Romero, Santiago; Viciana, Jesús

Abstract

The purposes were to examine the criterion-related validity of the steps estimated by consumer-wearable activity trackers (wrist-worn activity trackers: Fitbit Ace 2, Garmin Vivofit Jr, and Xiomi Mi Band 5; smartphone applications: Pedometer, Pedometer Pacer Health, and Google Fit/Apple Health) and their comparability in primary schoolchildren under controlled conditions. An initial sample of 66 primary schoolchildren (final sample = 56; 46.4% females), aged 9-12 years old (mean = 10.4 ± 1.0 years), wore three wrist-worn activity trackers (Fitbit Ace 2, Garmin Vivofit Jr 2, and Xiaomi Mi Band 5) on their non-dominant wrist and had three applications in two smartphones (Pedometer, Pedometer Pacer Health, and Google Fit/Apple Health for Android/iOS installed in Samsung Galaxy S20+/iPhone 11 Pro Max) in simulated front trouser pockets. Primary schoolchildren's steps estimated by the consumer-wearable activity trackers and the video-based counting independently by two researchers (gold standard) were recorded while they performed a 200-meter course in slow, normal and brisk pace walking, and running conditions. Results showed that the criterion-related validity of the step scores estimated by the three Samsung applications and the Garmin Vivofit Jr 2 were good-excellent in the four walking/running conditions (e.g., MAPE = 0.6-2.3%; lower 95% CI of the ICC = 0.81-0.99), as well as being comparable. However, the Apple applications, Fitbit Ace 2, and Xiaomi Mi Band 5 showed poor criterion-related validity and comparability on some walking/running conditions (e.g., lower 95% CI of the ICC < 0.70). Although, as in real life primary schoolchildren also place their smartphones in other parts (e.g., schoolbags, hands or even somewhere away from the body), the criterion-related validity of the Garmin Vivofit Jr 2 potentially would be considerably higher than that of the Samsung applications. The findings of the present study highlight the potential of the Garmin Vivofit Jr 2 for monitoring primary schoolchildren's steps under controlled conditions.

Deconstructing Fitbit to Specify the Effective Features in Promoting Physical Activity Among Inactive Adults: Pilot Randomized Controlled Trial (2024)

JMIR mHealth and uHealth

Authors: Takano, Keisuke; Oba, Takeyuki; Katahira, Kentaro; Kimura, Kenta

Abstract

BACKGROUND: Wearable activity trackers have become key players in mobile health practice as they offer various behavior change techniques (BCTs) to help improve physical activity (PA). Typically, multiple BCTs are implemented simultaneously in a device, making it difficult to identify which BCTs specifically improve PA. OBJECTIVE: We investigated the effects of BCTs implemented on a smartwatch, the Fitbit, to determine how each technique promoted PA. METHODS: This study was a single-blind, pilot randomized controlled trial, in which 70 adults (n=44, 63\% women; mean age 40.5, SD 12.56 years; closed user group) were allocated to 1 of 3 BCT conditions: self-monitoring (feedback on participants' own steps), goal setting (providing daily step goals), and social comparison (displaying daily steps achieved by peers). Each intervention lasted for 4 weeks (fully automated), during which participants wore a Fitbit and responded to day-to-day questionnaires regarding motivation. At pre- and postintervention time points (in-person sessions), levels and readiness for PA as well as different aspects of motivation were assessed. RESULTS: Participants showed excellent adherence (mean valid-wear time of Fitbit=26.43/28 days, 94\%), and no dropout was recorded. No significant changes were found in self-reported total PA (dz{\textless}0.28, P=.40 for the self-monitoring group, P=.58 for the goal setting group, and P=.19 for the social comparison group). Fitbit-assessed step count during the intervention period was slightly higher in the goal setting and social comparison groups than in the self-monitoring group, although the effects did not reach statistical significance (P=.052 and P=.06). However, more than half (27/46, 59\%) of the participants in the precontemplation stage reported progress to a higher stage across the 3 conditions. Additionally, significant increases were detected for several aspects of motivation (ie, integrated and external regulation), and significant group differences were identified for the day-to-day changes in external regulation; that is, the self-monitoring group showed a significantly larger increase in the sense of pressure and tension (as part of external regulation) than the goal setting group (P=.04). CONCLUSIONS: Fitbit-implemented BCTs promote readiness and motivation for PA, although their effects on PA levels are marginal. The BCT-specific effects were unclear, but preliminary evidence showed that self-monitoring alone may be perceived demanding. Combining self-monitoring with another BCT (or goal setting, at least) may be important for enhancing continuous engagement in PA. TRIAL REGISTRATION: Open Science Framework; https://osf.io/87qnb/?view\_only=f7b72d48bb5044eca4b8ce729f6b403b.

Detection of Common Respiratory Infections, Including COVID-19, Using Consumer Wearable Devices in Health Care Workers: Prospective Model Validation Study (2024)

JMIR formative research

Authors: Esmaeilpour, Zeinab; Natarajan, Aravind; Su, Hao-Wei; Faranesh, Anthony; Friel, Ciaran; Zanos, Theodoros P.; D'Angelo, Stefani; Heneghan, Conor

Abstract

BACKGROUND: The early detection of respiratory infections could improve responses against outbreaks. Wearable devices can provide insights into health and well-being using longitudinal physiological signals. OBJECTIVE: The purpose of this study was to prospectively evaluate the performance of a consumer wearable physiology-based respiratory infection detection algorithm in health care workers. METHODS: In this study, we evaluated the performance of a previously developed system to predict the presence of COVID-19 or other upper respiratory infections. The system generates real-time alerts using physiological signals recorded from a smartwatch. Resting heart rate, respiratory rate, and heart rate variability measured during the sleeping period were used for prediction. After baseline recordings, when participants received a notification from the system, they were required to undergo testing at a Northwell Health System site. Participants were asked to self-report any positive tests during the study. The accuracy of model prediction was evaluated using respiratory infection results (laboratory results or self-reports), and postnotification surveys were used to evaluate potential confounding factors. RESULTS: A total of 577 participants from Northwell Health in New York were enrolled in the study between January 6, 2022, and July 20, 2022. Of these, 470 successfully completed the study, 89 did not provide sufficient physiological data to receive any prediction from the model, and 18 dropped out. Out of the 470 participants who completed the study and wore the smartwatch as required for the 16-week study duration, the algorithm generated 665 positive alerts, of which 153 (23.0\%) were not acted upon to undergo testing for respiratory viruses. Across the 512 instances of positive alerts that involved a respiratory viral panel test, 63 had confirmed respiratory infection results (ie, COVID-19 or other respiratory infections detected using a polymerase chain reaction or home test) and the remaining 449 had negative upper respiratory infection test results. Across all cases, the estimated false-positive rate based on predictions per day was 2\%, and the positive-predictive value ranged from 4\% to 10\% in this specific population, with an observed incidence rate of 198 cases per week per 100,000. Detailed examination of questionnaires filled out after receiving a positive alert revealed that physical or emotional stress events, such as intense exercise, poor sleep, stress, and excessive alcohol consumption, could cause a false-positive result. CONCLUSIONS: The real-time alerting system provides advance warning on respiratory viral infections as well as other physical or emotional stress events that could lead to physiological signal changes. This study showed the potential of wearables with embedded alerting systems to provide information on wellness measures.

Detection of sedentary time and bouts using consumer-grade wrist-worn devices: a hidden semi-Markov model (2024)

BMC medical research methodology

Authors: Salim, Agus; Brakenridge, Christian J.; Lekamlage, Dulari Hakamuwa; Howden, Erin; Grigg, Ruth; Dillon, Hayley T.; Bondell, Howard D.; Simpson, Julie A.; Healy, Genevieve N.; Owen, Neville; Dunstan, David W.; Winkler, Elisabeth A. H.

Abstract

Background: Wrist-worn data from commercially available devices has potential to characterize sedentary time for research and for clinical and public health applications. We propose a model that utilizes heart rate in addition to step count data to estimate the proportion of time spent being sedentary and the usual length of sedentary bouts. Methods: We developed and trained two Hidden semi-Markov models, STEPHEN (STEP and Heart ENcoder) and STEPCODE (STEP enCODEr; a steps-only based model) using consumer-grade Fitbit device data from participants under free living conditions, and validated model performance using two external datasets. We used the median absolute percentage error (MDAPE) to measure the accuracy of the proposed models against research-grade activPAL device data as the referent. Bland-Altman plots summarized the individual-level agreement with activPAL. Results: In OPTIMISE cohort, STEPHEN's estimates of the proportion of time spent sedentary had significantly (p < 0.001) better accuracy (MDAPE [IQR] = 0.15 [0.06-0.25] vs. 0.23 [0.13-0.53)]) and agreement (Bias Mean [SD]=-0.03[0.11] vs. 0.14 [0.11]) than the proprietary software, estimated the usual sedentary bout duration more accurately (MDAPE[IQR] = 0.11[0.06-0.26] vs. 0.42[0.32-0.48]), and had better agreement (Bias Mean [SD] = 3.91[5.67] minutes vs. -11.93[5.07] minutes). With the ALLO-Active dataset, STEPHEN and STEPCODE did not improve the estimation of proportion of time spent sedentary, but STEPHEN estimated usual sedentary bout duration more accurately than the proprietary software (MDAPE[IQR] = 0.19[0.03-0.25] vs. 0.36[0.15-0.48]) and had smaller bias (Bias Mean[SD] = 0.70[8.89] minutes vs. -11.35[9.17] minutes). Conclusions: STEPHEN can characterize the proportion of time spent being sedentary and usual sedentary bout length. The methodology is available as an open access R package available from https://github.com/limfuxing/stephen/ . The package includes trained models, but users have the flexibility to train their own models.

Digital phenotyping in bipolar disorder: Using longitudinal Fitbit data and personalized machine learning to predict mood symptomatology (2024)

Acta Psychiatrica Scandinavica

Authors: Lipschitz, Jessica M.; Lin, Sidian; Saghafian, Soroush; Pike, Chelsea K.; Burdick, Katherine E.

Abstract

BACKGROUND: Effective treatment of bipolar disorder (BD) requires prompt response to mood episodes. Preliminary studies suggest that predictions based on passive sensor data from personal digital devices can accurately detect mood episodes (e.g., between routine care appointments), but studies to date do not use methods designed for broad application. This study evaluated whether a novel, personalized machine learning approach, trained entirely on passive Fitbit data, with limited data filtering could accurately detect mood symptomatology in BD patients. METHODS: We analyzed data from 54 adults with BD, who wore Fitbits and completed bi-weekly self-report measures for 9 months. We applied machine learning (ML) models to Fitbit data aggregated over two-week observation windows to detect occurrences of depressive and (hypo)manic symptomatology, which were defined as two-week windows with scores above established clinical cutoffs for the Patient Health Questionnaire-8 (PHQ-8) and Altman Self-Rating Mania Scale (ASRM) respectively. RESULTS: As hypothesized, among several ML algorithms, Binary Mixed Model (BiMM) forest achieved the highest area under the receiver operating curve (ROC-AUC) in the validation process. In the testing set, the ROC-AUC was 86.0\% for depression and 85.2\% for (hypo)mania. Using optimized thresholds calculated with Youden's J statistic, predictive accuracy was 80.1\% for depression (sensitivity of 71.2\% and specificity of 85.6\%) and 89.1\% for (hypo)mania (sensitivity of 80.0\% and specificity of 90.1\%). CONCLUSION: We achieved sound performance in detecting mood symptomatology in BD patients using methods designed for broad application. Findings expand upon evidence that Fitbit data can produce accurate mood symptomatology predictions. Additionally, to the best of our knowledge, this represents the first application of BiMM forest for mood symptomatology prediction. Overall, results move the field a step toward personalized algorithms suitable for the full population of patients, rather than only those with high compliance, access to specialized devices, or willingness to share invasive data.

Digital Phenotyping of Geriatric Depression Using a Community-Based Digital Mental Health Monitoring Platform for Socially Vulnerable Older Adults and Their Community Caregivers: 6-Week Living Lab Single-Arm Pilot Study (2024)

JMIR mHealth and uHealth

Authors: Song, Sunmi; Seo, YoungBin; Hwang, SeoYeon; Kim, Hae-Young; Kim, Junesun

Abstract

BACKGROUND: Despite the increasing need for digital services to support geriatric mental health, the development and implementation of digital mental health care systems for older adults have been hindered by a lack of studies involving socially vulnerable older adult users and their caregivers in natural living environments. OBJECTIVE: This study aims to determine whether digital sensing data on heart rate variability, sleep quality, and physical activity can predict same-day or next-day depressive symptoms among socially vulnerable older adults in their everyday living environments. In addition, this study tested the feasibility of a digital mental health monitoring platform designed to inform older adult users and their community caregivers about day-to-day changes in the health status of older adults. METHODS: A single-arm, nonrandomized living lab pilot study was conducted with socially vulnerable older adults (n=25), their community caregivers (n=16), and a managerial social worker over a 6-week period during and after the COVID-19 pandemic. Depressive symptoms were assessed daily using the 9-item Patient Health Questionnaire via scripted verbal conversations with a mobile chatbot. Digital biomarkers for depression, including heart rate variability, sleep, and physical activity, were measured using a wearable sensor (Fitbit Sense) that was worn continuously, except during charging times. Daily individualized feedback, using traffic signal signs, on the health status of older adult users regarding stress, sleep, physical activity, and health emergency status was displayed on a mobile app for the users and on a web application for their community caregivers. Multilevel modeling was used to examine whether the digital biomarkers predicted same-day or next-day depressive symptoms. Study staff conducted pre- and postsurveys in person at the homes of older adult users to monitor changes in depressive symptoms, sleep quality, and system usability. RESULTS: Among the 31 older adult participants, 25 provided data for the living lab and 24 provided data for the pre-post test analysis. The multilevel modeling results showed that increases in daily sleep fragmentation (P=.003) and sleep efficiency (P=.001) compared with one's average were associated with an increased risk of daily depressive symptoms in older adults. The pre-post test results indicated improvements in depressive symptoms (P=.048) and sleep quality (P=.02), but not in the system usability (P=.18). CONCLUSIONS: The findings suggest that wearable sensors assessing sleep quality may be utilized to predict daily fluctuations in depressive symptoms among socially vulnerable older adults. The results also imply that receiving individualized health feedback and sharing it with community caregivers may help improve the mental health of older adults. However, additional in-person training may be necessary to enhance usability. TRIAL REGISTRATION: ClinicalTrials.gov NCT06270121; https://clinicaltrials.gov/study/NCT06270121.

Digital Rehabilitation Program for Breast Cancer Survivors on Adjuvant Hormonal Therapy: A Feasibility Study (2024)

Cancers

Authors: Chan, Wing-Lok; Wong, Yat-Lam; Tai, Yin-Ling; Liu, Michelle; Yun, Bryan; Zhang, Yuning; Hou, Holly Li-Yu; Kwong, Dora; Lee, Victor Ho-Fun; Lam, Wendy Wing-Tak

Abstract

Background: Breast cancer survivors often face physical and psychological challenges, including weight gain, metabolic syndrome, and reduced quality of life. To address these concerns, a mobile app-based rehabilitation program called "THRIVE" was developed to improve physical activity, medication adherence, and health-related quality of life (HRQoL) in this population. Methods: This prospective, single-arm study assessed the feasibility and effectiveness of the "THRIVE" app among breast cancer survivors undergoing hormonal therapy. Participants were recruited from Queen Mary Hospital in Hong Kong between December 2022 and June 2023. Eligible survivors had completed treatment within the last five years or had stable advanced disease on hormonal therapy. Participants monitored their exercise, medication adherence, and self-care via the app and a Fitbit activity tracker for 16 weeks. Primary outcomes included recruitment, dropout, adherence rates, and safety. Secondary outcomes, measured at baseline and week 16, included physical activity intensity, HRQoL, psychological stress, body composition, and app satisfaction. Results: A total of 50 participants, with a median age of 53 years, completed the study. The recruitment rate was 70.4% with no dropouts. The adherence rate, measured by completing exercises recommended in the mobile app at least three times per week, was 74%. No severe adverse events were reported. While physical activity intensity showed no significant changes from baseline to week 16 (p = 0.24), cognitive function (p = 0.021), future perspective (p = 0.044), arm symptoms (p = 0.042), depression (p = 0.01), and anxiety (p = 0.004) improved. All participants reported perfect medication compliance (100%). Satisfaction with the app was high. Conclusions: This mobile app-based rehabilitation program demonstrated good feasibility, with satisfactory recruitment, adherence, and safety, providing valuable insights into future definitive studies. Keywords: breast cancer; cognition; depression; digital rehabilitation; hormonal therapy; mobile app-based intervention; survivor.

Digitizing Survivorship Care Plans Through the POST-Treatment Health Outcomes of Cancer Survivors (POSTHOC) Mobile App: Protocol for a Phase II Randomized Controlled Trial (2024)

JMIR research protocols

Authors: Chung, Kaitlin H.; Youngblood, Shari M.; Clingan, Carin L.; Deighton, Dana C.; Jump, Virginia A.; Manuweera, Thushini; McGeorge, Nicolette M.; Renn, Cynthia L.; Rosenblatt, Paula Y.; Winder, Aaron T.; Zhu, Shijun; Kleckner, Ian R.; Kleckner, Amber S.

Abstract

BACKGROUND: Survivorship care plans (SCPs) are provided at the completion of cancer treatment to aid in the transition from active treatment to long-term survivorship. They describe the details of a patient's diagnosis and treatment and offer recommendations for follow-up appointments, referrals, and healthy behaviors. The plans are currently paper-based and become outdated as soon as a patient's health status changes. There is a need to digitize these plans to improve their accessibility, modifiability, and longevity. With current technology, SCPs can be linked to mobile devices and activity trackers so that patients can track health behaviors and compare them to their clinical goals, taking charge of their own health. OBJECTIVE: A mobile app, POSTHOC (POST-Treatment Health Outcomes of Cancer Survivors), that digitizes the SCP was developed, with goals of integrating it with wearable technologies and electronic medical records. Herein, we are conducting a randomized controlled trial that evaluates the POSTHOC app versus the traditional SCP on total symptom burden in the early posttreatment period. METHODS: We will recruit 54 patients who have recently completed curative therapy for cancer (any type) in person and remotely. They will be randomized 2:1, POSTHOC:usual care (unblinded). Those randomized to the POSTHOC group will receive their SCP via the app and will choose to focus on nutrition or exercise for the duration of the study based on their individual plan and personal preferences. Those randomized to the control group will get a paper-based plan. At baseline, 6 weeks, and 12 weeks, we will evaluate patient-reported outcomes, including total symptom burden (web-based questionnaire), diet (24-hour Automated Self-Administered [ASA24]), and physical activity (Fitbit Charge 6 [Google LLC]). We will also collect quantitative and qualitative feedback on the usability of the app from those in the POSTHOC arm to improve the app for future implementation studies, with a specific focus on patient-provider communication. For feasibility, we will calculate the percentage of patients who used the POSTHOC app at least 3 times per week. We will use linear mixed models to evaluate the effects of the POSTHOC app versus those of usual care on other outcomes at weeks 6 and 12. RESULTS: This trial is open to accrual in the University of Maryland Medical System as of March 2024, and as of July 3, 2024, a total of 20 participants have consented. CONCLUSIONS: This study is among the first to digitize the SCP in a mobile app and test the effects of a mobile health-delivered behavioral health intervention on symptom burden in cancer survivors. Our results will provide evidence about the effects of health self-management on symptoms. This knowledge will be integral to larger randomized controlled studies, integration with the electronic medical record, and nationwide implementation. TRIAL REGISTRATION: ClinicalTrials.gov NCT05499663; https://clinicaltrials.gov/ct2/show/NCT05499663. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59222.

Ecological Momentary Intervention to Replace Sedentary Time With Physical Activity to Improve Executive Function in Midlife and Older Latino Adults: Pilot Randomized Controlled Trial (2024)

Journal of Medical Internet Research

Authors: Bronas, Ulf G.; Marquez, David X.; Fritschi, Cynthia; Petrarca, Katherine; Kitsiou, Spyros; Ajilore, Olu; Tintle, Nathan

Abstract

BACKGROUND: Exercise interventions often improve moderate to vigorous physical activity, but simultaneously increase sedentary time due to a compensatory resting response. A higher level of sedentary time is associated with a lower level of executive function, while increased moderate to vigorous physical activity is associated with improved global cognition and working memory among Latino adults. Latino adults are the fastest-growing minority group in the United States and are at high risk for cognitive decline, spend more time sedentary compared to non-Hispanic populations, and engage in low levels of physical activity. Interventions that are culturally appropriate for Latino adults to replace sedentary time with physical activity are critically needed. OBJECTIVE: This study aims to develop and test the feasibility and acceptability of an ecological momentary intervention (EMI; delivered in real time) that is individually designed to replace sedentary time with physical activity in Latino adults. METHODS: This pilot study randomized 39 (n=26, 67\% female; mean age 61, SD 5.8 years) community-dwelling, Spanish-speaking Latino adults (1:1 allocation) to either a 6-week EMI program designed to replace sitting time with physical activity (20/39, 51\%) or physical activity guidelines education (19/39, 49\%). The program was conducted on the web and in Spanish. The intervention was individualized based on individual interview responses. The intervention included the use of a Fitbit activity monitor, weekly didactic phone meetings, interactive tools (SMS text messages), and coach-delivered feedback. Feasibility and acceptability were assessed via study satisfaction (Likert scales), motivation (ecological momentary assessment), retention, and compliance. Sedentary time and physical activity were assessed via 7-day actigraphy. Cognitive performance was assessed via the trail making test part A and B (part B=executive function) and via the National Institutes of Health Toolbox remote cognitive assessment. Statistical analysis included a linear model on change score from baseline, adjusting for age, sex, and education, emphasizing effect size. RESULTS: Participant satisfaction with EMI was high (9.4/10), with a high degree of motivation to replace sitting time with physical activity (9.8/10). The intervention compliance rate was 79\% with low difficulty using the Fitbit (1.7/10). Weekly step count increased in the intervention group by 5543 steps (group difference: d=0.54; P=.05) and sedentary time decreased by a mean 348 (SD 485) minutes (group difference: d=0.47; P=.24) compared to controls, with moderately strong effect sizes. The trail making test part B improved in the intervention group (mean -35.26, SD 60.35 seconds), compared to the control group (mean 7.19, SD 46 seconds; group difference: d=0.74; P=.01). No group differences were observed in other cognitive measures. CONCLUSIONS: An individualized EMI designed for midlife and older Latino adults has the potential to replace sitting time with physical activity and improve executive functioning. The intervention was feasible and well received with a high degree of satisfaction. TRIAL REGISTRATION: ClinicalTrials.gov NCT04507464; https://tinyurl.com/44c4thk5.

Effect of communicating genetic risk of type 2 diabetes and wearable technologies on wearable device-measured behavioural outcomes in East Asians: protocol of a randomised controlled trial (2024)

BMJ open

Authors: Kim, Youngwon; Godino, Job G.; Cheung, Flora Lai Tung; Multhaup, Michael; Chan, Derwin King Chung K. C.; Chen, Ziyuan; Ho, Harrison Hin Sheung; Tse, Tsz Him Timothy; Au Yeung, Shiu Lun Ryan; Lou, Shan; Zhang, Joni H.; Wang, Mengyao; Chung, Brian; Griffin, Simon

Abstract

INTRODUCTION: The communication of information about the risk of type 2 diabetes (T2D) alone has not been associated with changes in habitual behaviours among individuals of European ancestry. In contrast, the use of wearable devices that monitor physical activity (PA) has been associated with behavioural changes in some studies. It is uncertain whether risk communication might enhance the effects of wearable devices. We aim to assess the effects of communicating genetic risk for T2D alone or in combination with wearable device functions on wearable device-measured PA among overweight or obese East Asians. METHODS AND ANALYSIS: In a parallel group, randomised controlled trial, 355 overweight or obese East Asian individuals aged 40-60 years are allocated into one of three groups: one control and two intervention groups. Blood samples will be used for estimation of T2D genetic risk and analysis of metabolic risk markers. Genetic risk of T2D will be estimated based on 113 single-nucleotide polymorphisms associated with T2D among East Asians. All three groups receive a Fitbit device. Both intervention groups will receive T2D genetic risk estimates along with lifestyle advice, but one of the intervention groups additionally uses Fitbit's step goal setting and prompt functions. Questionnaires and physical measurements are administered at baseline, immediately after intervention delivery, and 6 and 12 months post intervention. The primary outcome is time spent in moderate-to-vigorous PA from the Fitbit, which will be assessed at baseline, immediately post intervention, 12 months post intervention and at 6-month follow-up. Secondary outcomes include other wearable device-measured parameters, sedentary time, and sleep, blood pressure, metabolic risk markers, hand grip strength, self-reported PA, fruit and vegetable consumption, smoking, and psychological variables. Between-group differences in the continuous and categorical variables collected at baseline will be examined using Analysis of Variance (ANOVA) and χ2 tests, respectively. A series of linear mixed effects models with fixed effects of time, group and interaction between time and group will be performed, with adjustment for potential confounders. ETHICS AND DISSEMINATION: The study protocol has undergone review and received approval from the ethics committee of the University of Hong Kong. Findings from our trial will be disseminated through publication in peer-reviewed research journals and presented at international academic conferences. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov, NCT05524909. https://register. CLINICALTRIALS: gov/ (11 November 2024).

Effectiveness of a digital health and financial incentive intervention to promote physical activity in patients with type 2 diabetes: study protocol for a randomised controlled trial with a nested qualitative study-ACTIVATE trial (2024)

Trials

Authors: Sanders, James P.; Daley, Amanda J.; Esliger, Dale W.; Roalfe, Andrea K.; Colda, Antoanela; Turner, Joanne; Hajdu, Soma; Potter, Andrew; Humayun, Asif M.; Spiliotis, Ioannis; Reckless, Ian; Mytton, Oliver

Abstract

BACKGROUND: The prevention of type 2 diabetes (T2DM) is recognised as a health care priority in the UK. In people living with T2DM, lifestyle changes (e.g. increasing physical activity) have been shown to slow disease progression and protect from the development of associated comorbidities. The use of digital health technologies provides a strategy to increase physical activity in patients with chronic disease. Furthermore, behaviour economics suggests that financial incentives may be a useful strategy for increasing the maintenance and effectiveness of behaviour change intervention, including physical activity intervention using digital health technologies. The Milton Keynes Activity Rewards Programme (MKARP) is a 24-month intervention which combines the use of a mobile health app, smartwatch (Fitbit or Apple watch) and financial incentives to encourage people living with T2DM to increase physical activity to improve health. Therefore, this randomised controlled trial aims to examine the long-term acceptability, health effects and cost-effectiveness of the MKARP on HbA1c in patients living with T2DM versus a waitlist usual care comparator. METHODS: A two-arm, single-centre, randomised controlled trial aiming to recruit 1018 participants with follow-up at 12 and 24 months. The primary outcome is the change in HbA1c at 12 months. Secondary outcomes included changes in markers of metabolic, cardiovascular, anthropometric, and psychological health along with cost-effectiveness. Recruitment will be via annual diabetes review in general practices, retinal screening services and social media. Participants aged 18 or over, with a diagnosis of type 2 diabetes and a valid HbA1c measurement in the last 2 months are invited to take part in the trial. Participants will be individually randomised (1:1 ratio) to receive either the Milton Keynes Activity Rewards Programme or usual care. The intervention will last for 24 months with assessment for outcomes at baseline, 12 and 24 months. DISCUSSION: This study will provide new evidence of the long-term effectiveness of an activity rewards scheme focused on increasing physical activity conducted within routine care in patients living with type 2 diabetes in Milton Keynes, UK. It will also investigate the cost-effectiveness of the intervention. TRIAL REGISTRATION: ISRCTN 14925701. Registered on 30 October 2023.

Effectiveness of a Lifestyle Improvement Support App in Combination with a Wearable Device in Japanese People with Type 2 Diabetes Mellitus: STEP-DM Study (2024)

Diabetes Therapy: Research, Treatment and Education of Diabetes and Related Disorders

Authors: Takahashi, Akiko; Ishii, Manabu; Kino, Yurika; Sasaki, Kazuyo; Matsui, Takahiro; Arakawa, Kenji; Kunisaki, Makoto

Abstract

INTRODUCTION: Although the use of application (app)s and wearable devices supporting diabetes treatment has spread rapidly in recent years, evidence of their impact, especially in combination of them, is limited. TOMOCO™ is a lifestyle improvement support app that features interactive virtual conversations according to the programmed algorithm guiding users toward their goals of lifestyle improvement. We hypothesized that TOMOCO™ in combination with Fitbit, which accurately tracks users' activity level, would encourage people with type 2 diabetes mellitus (T2DM) to change their lifestyles and improve their glycated hemoglobin (HbA1c) levels without changes in conventional therapy. Thus, we performed the present study to explore the effectiveness of this combination in Japanese participants with T2DM who had not achieved their glycemic targets. METHODS: In this single-arm exploratory study, participants with T2DM used the TOMOCO™ and Fitbit in addition to the conventional diet/exercise therapy and anti-diabetic drug for 12 weeks. They were provided with feedback/advice by health care providers based on the TOMOCO™ and Fitbit records. The primary endpoint was the change in HbA1c from baseline to the end of the observation period. Data were expressed as mean ± standard deviation. RESULTS: Fifty-nine (96.7\%) of the 61 participants (male, 42 [71.2\%]; age, 60.1 ± 8.7 years; HbA1c level, 7.48 ± 0.37\% at screening) completed the study. At the end of the observation period, the HbA1c was significantly reduced (- 0.41 ± 0.41\%, p {\textless} 0.001). This trend was consistent across the preselected patient characteristics, including sex, age, and body mass index. However, it was more pronounced in the participants with earlier stages of behavioral changes defined by the transtheoretical model at baseline. CONCLUSIONS: The unique features of TOMOCO™ in combination with Fitbit, together with conventional therapy, may promote a healthy lifestyle and thus contribute to improving HbA1c in people with T2DM. CLINICAL TRIAL REGISTRATION: jRCT1070220007.

Effects of night-float shifts on cognitive function among radiology residents (2024)

Emergency Radiology

Authors: Flink, Carl C.; Hobohm, Robert E.; Zhang, Bin; Jacobson, Deborah L.; England, Eric B.

Abstract

BACKGROUND: Many radiology programs utilize a night-float system to mitigate the effects of fatigue, improve patient care, and provide faster report turnaround times. Prior studies have demonstrated an increase in discrepancy rates during night-float shifts. OBJECTIVES: This study was performed to examine the effects of night-float shift work on radiology resident cognition. We hypothesized that there would be diminished cognitive function on testing following night-float shifts when compared to testing following day shifts. METHODS: Diagnostic radiology residents in their second to fifth years of residency at a single institution were recruited to participate in this pilot study. Cognitive function was evaluated using the Lumosity Neurocognitive Performance Tests (NCPT), standardized performance tests that provide real-time, objective measurements of cognitive function. Study participants completed the NCPT in 5 sessions following 5 consecutive day shifts to evaluate their baseline cognitive function. The tests were re-administered at the end of consecutive night-float shifts to assess for any changes. Sleep was objectively monitored using actigraphy devices worn around the wrist during all study weeks. Descriptive and summary statistics were performed. RESULTS: 23 prospectively recruited diagnostic radiology residents working night-float shifts took a mean 13.6 (± 5.1) neurocognitive performance tests during the study period. There was a statistically significant decline in 2 of the 6 cognitive tests administered, signifying a decrease in attention, speed, and complex reasoning ability. Night-float shifts were significantly longer than the day shifts and associated with a significantly higher study volume and cross-sectional study volume. Fitbit data demonstrated that there were no significant differences in level of activity while awake. However, participants slept significantly longer during day shifts. CONCLUSIONS: A sample of 23 radiology residents working night-float shifts demonstrated declines in attention, speed, and complex reasoning ability following sequential administration of standardized neurocognitive performance tests. While the sample size is small, these findings demonstrate the potential deleterious effects of night-float shift work and provide evidence to support further inquiry into this phenomenon.

Efficacy of Activity Trackers in Patients With Heart Failure With Preserved Ejection Fraction (2024)

Cureus

Authors: Kogelschatz, Benjamin; Penn, Brittany A.; Leavitt, Ashlynn J.; Dranow, Elizabeth; Ma, Christy L.; Ryan, John J.

Abstract

Background: Heart failure with preserved ejection fraction (HFpEF) is a common, complex syndrome associated with elevated morbidity and mortality. Patients with HFpEF have a high prevalence of comorbidities, including hypertension, diabetes mellitus, and obesity, which are closely related to the underlying mechanisms of the disease. Lifestyle modification with weight loss and physical activity can improve risk factors and functional outcomes in HFpEF. We sought to observe daily physical activity and determine whether utilizing an activity tracker can enhance functional status in HFpEF patients. Methods: We performed a prospective analysis of 57 patients with HFpEF from 2021 to 2023 at a single academic medical center who utilized a Fitbit to record one year of daily step activity. The patients were evaluated in the ambulatory setting for an initial visit and subsequently at intervals of 3, 6, and 12 months to gather vitals, labs, physical exam, and functional measurements, including the Six-Minute Walk Test (6MWT) and Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12). Associations between variables were assessed using Pearson's r correlation using Stata 18.0. Results: Of the 49 patients who completed the study, the mean age was 68.1 ± 10.2 years, with 67% of patients identifying as female. The average BMI was 36.4 ± 8.6 kg/m2. Across each time interval, the median numbers of steps per day were 4,113 (2,517-6,520) (1-3 months), 4,583 (2,532-6,326) (4-6 months), and 3,957 (2,942-5,982) (7-12 months). There was no statistically significant variation in daily step count (p=0.06). We observed a statistically significant increase of 66 (6-200) feet in the 6MWT (p= 0.002) from baseline (1,175 (910-1,400)) to 12 months (1,321 (1,000-1,550)). The daily step count was highly correlated with the 6MWT across all time points (1-3 months: r= .70, p< .001; 4-6 months: r= .61, p< .001; 7-12 months: r= .69, p< .001). The total KCCQ-12 scores increased by 6.8 (-4.2-19.8) points (p=0.005) from baseline (60.1 (41.7-73.4)) to 12 months (69.8 (50-84.4)). Among the sub-categories of the questionnaire, we observed a positive correlation between physical limitation scores and daily step count (1-3 months: r= .47, p=.001; 4-6 months: r= .63, p< .001; 7-12 months: r= .56, p= .001). Of interest, one patient who was taking over 15,000 daily steps scored their physical limitation 10-20 points lower than those taking less than half the steps and had one of the lowest quality of life scores in the cohort, reflecting the subjective nature of heart failure (HF) symptoms. Conclusion: Fitbit technology offers a convenient means to monitor real-time physical activity in patients with HFpEF. Utilizing a Fitbit to record daily step activity enhances health-related quality of life in this population. In contrast to the improved average total KCCQ-12 score, we did not observe a clinically significant increase in the 6MWT over the course of the year. Our findings establish the utility of daily step count as a valuable surrogate for six-minute walk distance.

Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial (2024)

JMIR mHealth and uHealth

Authors: White, Katie M.; Carr, Ewan; Leightley, Daniel; Matcham, Faith; Conde, Pauline; Ranjan, Yatharth; Simblett, Sara; Dawe-Lane, Erin; Williams, Laura; Henderson, Claire; Hotopf, Matthew

Abstract

Background: Multiparametric remote measurement technologies (RMTs), which comprise smartphones and wearable devices, have the potential to revolutionize understanding of the etiology and trajectory of major depressive disorder (MDD). Engagement with RMTs in MDD research is of the utmost importance for the validity of predictive analytical methods and long-term use and can be conceptualized as both objective engagement (data availability) and subjective engagement (system usability and experiential factors). Positioning the design of user interfaces within the theoretical framework of the Behavior Change Wheel can help maximize effectiveness. In-app components containing information from credible sources, visual feedback, and access to support provide an opportunity to promote engagement with RMTs while minimizing team resources. Randomized controlled trials are the gold standard in quantifying the effects of in-app components on engagement with RMTs in patients with MDD. Objective: This study aims to evaluate whether a multiparametric RMT system with theoretically informed notifications, visual progress tracking, and access to research team contact details could promote engagement with remote symptom tracking over and above the system as usual. We hypothesized that participants using the adapted app (intervention group) would have higher engagement in symptom monitoring, as measured by objective and subjective engagement. Methods: A 2-arm, parallel-group randomized controlled trial (participant-blinded) with 1:1 randomization was conducted with 100 participants with MDD over 12 weeks. Participants in both arms used the RADAR-base system, comprising a smartphone app for weekly symptom assessments and a wearable Fitbit device for continuous passive tracking. Participants in the intervention arm (n=50, 50%) also had access to additional in-app components. The primary outcome was objective engagement, measured as the percentage of weekly questionnaires completed during follow-up. The secondary outcomes measured subjective engagement (system engagement, system usability, and emotional self-awareness). Results: The levels of completion of the Patient Health Questionnaire-8 (PHQ-8) were similar between the control (67/97, 69%) and intervention (66/97, 68%) arms (P value for the difference between the arms=.83, 95% CI -9.32 to 11.65). The intervention group participants reported slightly higher user engagement (1.93, 95% CI -1.91 to 5.78), emotional self-awareness (1.13, 95% CI -2.93 to 5.19), and system usability (2.29, 95% CI -5.93 to 10.52) scores than the control group participants at follow-up; however, all CIs were wide and included 0. Process evaluation suggested that participants saw the in-app components as helpful in increasing task completion. Conclusions: The adapted system did not increase objective or subjective engagement in remote symptom tracking in our research cohort. This study provides an important foundation for understanding engagement with RMTs for research and the methodologies by which this work can be replicated in both community and clinical settings. Trial registration: ClinicalTrials.gov NCT04972474; https://clinicaltrials.gov/ct2/show/NCT04972474. International registered report identifier (irrid): RR2-10.2196/32653. Keywords: app; community; depression; engagement; mobile phone; remote measurement; self-awareness; smartphones; symptom tracking; technology; wearable devices.

Engagement With Daily Symptom Reporting, Passive Smartphone Sensing, and Wearable Device Data Collection During Chemotherapy: Longitudinal Observational Study (2024)

JMIR cancer

Authors: McClaine, Sean; Fedor, Jennifer; Bartel, Christianna; Chen, Leeann; Durica, Krina C.; Low, Carissa A.

Abstract

BACKGROUND: Chemotherapy can cause symptoms that impair quality of life and functioning. Remote monitoring of daily symptoms and activity during outpatient treatment may enable earlier detection and management of emerging toxicities but requires patients, including older and acutely ill patients, to engage with technology to report symptoms through smartphones and to charge and wear mobile devices. OBJECTIVE: This study aimed to identify factors associated with participant engagement with collecting 3 data streams (ie, daily patient-reported symptom surveys, passive smartphone sensing, and a wearable Fitbit device [Google]) during chemotherapy. METHODS: We enrolled 162 patients receiving outpatient chemotherapy into a 90-day prospective study. Patients were asked to install apps on their smartphones to rate daily symptoms and to collect passive sensor data and to wear a Fitbit device for the duration of the study. Participants completed baseline demographic and quality of life questionnaires, and clinical information was extracted from the electronic medical record. We fit a series of logistic generalized estimating equations to evaluate the association between demographic and clinical factors and daily engagement with each data stream. RESULTS: Participants completed daily surveys on 61\% (SD 27\%) of days and collected sufficient smartphone data and wearable sensor data on 73\% (SD 35\%) and 70\% (SD 33\%) of enrolled days, respectively, on average. Relative to White participants, non-White patients demonstrated lower odds of engagement with both symptom surveys (odds ratio [OR] 0.49, 95\% CI 0.29-0.81; P=.006) and wearable data collection (OR 0.35, 95\% CI 0.17-0.73; P=.005). Patients with stage 4 cancer also exhibited lower odds of engagement with symptom reporting than those with earlier stage disease (OR 0.69, 95\% CI 0.48-1.00; P=.048), and patients were less likely to complete symptom ratings on the weekend (OR 0.90, 95\% CI 0.83-0.97; P=.008). Older patients (OR 1.03, 95\% CI 1.01-1.06; P=.01) and those who reported better cognitive functioning at study entry (OR 1.18, 95\% CI 1.03-1.34; P=.02) were more likely to engage with Fitbit data collection, and patients who reported higher levels of depressive symptoms were less likely to engage with smartphone data collection (OR 1.18, 95\% CI 1.03-1.36; P=.02). CONCLUSIONS: Remote patient monitoring during chemotherapy has the potential to improve clinical management, but only if patients engage with these systems. Our results suggest significant associations between demographic and clinical factors and long-term engagement with smartphone and wearable device assessments during chemotherapy. Non-White participants, those with metastatic cancer, or those with existing cognitive impairment may benefit from additional resources to optimize engagement. Contrary to hypotheses, older adults were more likely than younger adults to engage consistently with wearable device assessments.

Evaluation of Machine Learning to Detect Influenza Using Wearable Sensor Data and Patient-Reported Symptoms: Cohort Study (2024)

Journal of Medical Internet Research

Authors: Farooq, Kamran; Lim, Melody; Dennison-Hall, Lawrence; Janson, Finn; Olszewska, Aspen Hazel; Ahmad Zabidi, Muhammad Mamduh; Haratym-Rojek, Anna; Narowski, Karol; Clinch, Barry; Prunotto, Marco; Chawla, Devika; Hunter, Victoria; Ukachukwu, Vincent

Abstract

BACKGROUND: Machine learning offers quantitative pattern recognition analysis of wearable device data and has the potential to detect illness onset and monitor influenza-like illness (ILI) in patients who are infected. OBJECTIVE: This study aims to evaluate the ability of machine-learning algorithms to distinguish between participants who are influenza positive and influenza negative in a cohort of symptomatic patients with ILI using wearable sensor (activity) data and self-reported symptom data during the latent and early symptomatic periods of ILI. METHODS: This prospective observational cohort study used the extreme gradient boosting (XGBoost) classifier to determine whether a participant was influenza positive or negative based on 3 models using symptom-only data, activity-only data, and combined symptom and activity data. Data were collected from the Home Testing of Respiratory Illness (HTRI) study and FluStudy2020, both conducted between December 2019 and October 2020. The model was developed using the FluStudy2020 data and tested on the HTRI data. Analyses included participants in these studies with an at-home influenza diagnostic test result. Fitbit (Google LLC) devices were used to measure participants' steps, heart rate, and sleep parameters. Participants detailed their ILI symptoms, health care-seeking behaviors, and quality of life. Model performance was assessed by area under the curve (AUC), balanced accuracy, recall (sensitivity), specificity, precision (positive predictive value), negative predictive value, and weighted harmonic mean of precision and recall (F2) score. RESULTS: An influenza diagnostic test result was available for 953 and 925 participants in HTRI and FluStudy2020, respectively, of whom 848 (89\%) and 840 (90.8\%) had activity data. For the training and validation sets, the highest performing model was trained on the combined symptom and activity data (training AUC=0.77; validation AUC=0.74) versus symptom-only (training AUC=0.73; validation AUC=0.72) and activity-only (training AUC=0.68; validation AUC=0.65) data. For the FluStudy2020 test set, the performance of the model trained on combined symptom and activity data was closely aligned with that of the symptom-only model (combined symptom and activity test AUC=0.74; symptom-only test AUC=0.74). These results were validated using independent HTRI data (combined symptom and activity evaluation AUC=0.75; symptom-only evaluation AUC=0.74). The top features guiding influenza detection were cough; mean resting heart rate during main sleep; fever; total minutes in bed for the combined model; and fever, cough, and sore throat for the symptom-only model. CONCLUSIONS: Machine-learning algorithms had moderate accuracy in detecting influenza, suggesting that previous findings from research-grade sensors tested in highly controlled experimental settings may not easily translate to scalable commercial-grade sensors. In the future, more advanced wearable sensors may improve their performance in the early detection and discrimination of viral respiratory infections.

Examining a Remote Group-Based Type 2 Diabetes Self-Management Education Program in the COVID-19 Era Using the ORBIT Model: Small 6-Week Feasibility Study (2024)

JMIR formative research

Authors: Hiemstra, Madison S.; Reichert, Sonja M.; Mitchell, Marc S.

Abstract

Background: To date, most group-based diabetes self-management education (DSME) programs for type 2 diabetes (T2D) have been delivered in person. The rapid transition to remote care at the outset of the COVID-19 pandemic presented opportunities to test, evaluate, and iterate a new remote DSME program. Objective: We aim to refine the delivery and evaluation of a multicomponent remote DSME program for adults living with T2D by examining several feasibility outcomes. Methods: We recruited a convenience sample of patients from a London, Canada, outpatient diabetes clinic (serving high-risk, low-income adults) to participate in a 6-week, single cohort feasibility study from November 2020 to March 2021. This small ORBIT phase 1b feasibility study represents the first in a planned series guided by the ORBIT model for developing behavioral interventions for chronic diseases (phase 1: design; phase 2: preliminary testing; phase 3: efficacy; and phase 4: effectiveness). The feasibility of delivering and evaluating a remote DSME program, including (1) live video education classes, (2) individualized physical activity (PA) prescription and counseling, and (3) intermittently scanned continuous glucose and wearable PA monitoring, was assessed. Feasibility outcomes included recruitment and retention rates, program adherence, and acceptability (ie, technology issues and exit survey feedback). PA was assessed with Fitbit Inspire 2 (Fitbit Inc) and estimated glycated hemoglobin (HbA1c) using the FreeStyle Libre (Abbot). Given the small study sample, group- and individual-level data are reported descriptively. Results: A total of 10 adults living with T2D were recruited (female 60%; age 49.9, SD 14.3 years; estimated HbA1c 6.2%, SD 0.5%). Recruitment and retention rates were 29% and 80%, respectively. Participants attended 83% (25/30) and 93% (37/40) of education classes and PA counseling phone calls, respectively. There were 3.2 (SD 2.6) technology issues reported per person, most of which were related to study data transfer. Exit survey responses suggest most participants (8/9, 89%) were "satisfied" with the program. Recognizing the small sample size and the fact that no inferential statistics were conducted, the mean (SD) for the weekly daily step count and estimated HbA1c are provided for illustrative purposes. Participants accumulated 7103 (SD 2900) and 7515 (SD 3169) steps per day at baseline and week 6, respectively. The estimated HbA1c was 6.2% (SD 0.5%) and 6.2% (SD 0.6%) at baseline and week 6, respectively. Conclusions: This ORBIT phase 1b study served to refine the delivery (eg, automatic study data upload process recommended to reduce participant burden) and evaluation (eg, purposeful sampling of participants with baseline HbA1c >8% recommended to address selection bias) of a remote DSME program. Preliminary proof-of-concept testing (ORBIT phase 2) incorporating some of these learnings is now warranted.

Exploring the Applications of Explainability in Wearable Data Analytics: Systematic Literature Review (2024)

Journal of Medical Internet Research

Authors: Abdelaal, Yasmin; Aupetit, Michaël; Baggag, Abdelkader; Al-Thani, Dena

Abstract

Background: Wearable technologies have become increasingly prominent in health care. However, intricate machine learning and deep learning algorithms often lead to the development of "black box" models, which lack transparency and comprehensibility for medical professionals and end users. In this context, the integration of explainable artificial intelligence (XAI) has emerged as a crucial solution. By providing insights into the inner workings of complex algorithms, XAI aims to foster trust and empower stakeholders to use wearable technologies responsibly. Objective: This paper aims to review the recent literature and explore the application of explainability in wearables. By examining how XAI can enhance the interpretability of generated data and models, this review sought to shed light on the possibilities that arise at the intersection of wearable technologies and XAI. Methods: We collected publications from ACM Digital Library, IEEE Xplore, PubMed, SpringerLink, JMIR, Nature, and Scopus. The eligible studies included technology-based research involving wearable devices, sensors, or mobile phones focused on explainability, machine learning, or deep learning and that used quantified self data in medical contexts. Only peer-reviewed articles, proceedings, or book chapters published in English between 2018 and 2022 were considered. We excluded duplicates, reviews, books, workshops, courses, tutorials, and talks. We analyzed 25 research papers to gain insights into the current state of explainability in wearables in the health care context. Results: Our findings revealed that wrist-worn wearables such as Fitbit and Empatica E4 are prevalent in health care applications. However, more emphasis must be placed on making the data generated by these devices explainable. Among various explainability methods, post hoc approaches stand out, with Shapley Additive Explanations as a prominent choice due to its adaptability. The outputs of explainability methods are commonly presented visually, often in the form of graphs or user-friendly reports. Nevertheless, our review highlights a limitation in user evaluation and underscores the importance of involving users in the development process. Conclusions: The integration of XAI into wearable health care technologies is crucial to address the issue of black box models. While wrist-worn wearables are widespread, there is a notable gap in making the data they generate explainable. Post hoc methods such as Shapley Additive Explanations have gained traction for their adaptability in explaining complex algorithms visually. However, user evaluation remains an area in which improvement is needed, and involving users in the development process can contribute to more transparent and reliable artificial intelligence models in health care applications. Further research in this area is essential to enhance the transparency and trustworthiness of artificial intelligence models used in wearable health care technology. Keywords: XAI; analytics; deep learning; explainable artificial intelligence; health informatics; interpretation; machine learning; user experience; wearable; wearable data; wearable sensors.

Exploring the Use of Activity Trackers to Support Physical Activity and Reduce Sedentary Behavior in Adults Diagnosed With Type 2 Diabetes: Qualitative Interview Study Using the RE-AIM Framework (2024)

JMIR diabetes

Authors: Hodgson, William; Kirk, Alison; Lennon, Marilyn; Janssen, Xanne

Abstract

Background: The prevalence of type 2 diabetes in adults worldwide is increasing. Low levels of physical activity and sedentary behavior are major risk factors for developing the disease. Physical activity interventions incorporating activity trackers can reduce blood glucose levels in adults diagnosed with type 2 diabetes. The My Diabetes My Way website is a support and educational platform for people diagnosed with diabetes and health care professionals. Users of the My Diabetes My Way website can upload their Fitbit (Google Inc) activity data into the system but this is not presently being analyzed and used routinely within clinical care. Developers of the My Diabetes My Way system are planning to allow different makes of activity trackers to be integrated with the platform. Objective: This qualitative study aimed to explore (through the RE-AIM [reach, effectiveness, adoption, implementation, and maintenance] framework) views from adults diagnosed with type 2 diabetes and health care professionals on the integration of activity trackers into type 2 diabetes care. Methods: Overall, 12 adults diagnosed with type 2 diabetes and 9 health care professionals (4 general practitioners, 1 consultant, 2 diabetes nurses, 1 practice nurse, and 1 physical activity advisor) were recruited through social media and professional contacts. Semistructured one-to-one interviews were conducted. Abductive thematic analysis was undertaken, and main themes and subthemes were identified. The RE-AIM framework was used to evaluate the themes with respect to the wider use of activity trackers and the My Diabetes My Way platform within type 2 diabetes clinical care. Results: Overall, 6 main themes (awareness, access, cost, promotion, support, and technology and data) and 20 subthemes were identified. Evaluation using the 5 RE-AIM dimensions found that reach could be improved by raising awareness of the My Diabetes My Way platform and the ability to upload activity tracker data into the system. Effectiveness could be improved by implementing appropriate personalized measures of health benefits and providing appropriate support for patients and health care staff. Adoption could be improved by better promotion of the intervention among stakeholders and the development of joint procedures. Implementation could be improved through the development of an agreed protocol, staff training, and introducing measurements of costs. Maintenance could be improved by supporting all patients for long-term engagement and measuring improvements to patients' health. Conclusions: Through this study, we identified how the reach, effectiveness, adoption, implementation, and maintenance of integrating activity trackers into adult type 2 diabetes care could be improved. Keywords: thematic analysis; Fitbit; My Diabetes My Way; RE-AIM framework; activity tracker; clinical care; diabetes care; health promotion; physical activity; sedentary behavior; type 2 diabetes.

Family-Focused Facilitated Fitness: Feasibility and Acceptability of a Couple-Based Physical Activity Intervention for Hematopoietic Cell Transplant Recipients and their Caregiving Partners (2024)

Transplantation and Cellular Therapy

Authors: Langer, Shelby L.; Joseph, Rodney P.; Mistretta, Erin; Tao, Chun; Porter, Laura; Spain, Allison; Khera, Nandita

Abstract

Background: Reductions in physical activity (PA) are common among patients following hematopoietic cell transplantation, and a risk factor for poor physical functioning. PA among spouses/cohabiting partners, who frequently serve as the patient's primary caregiver, may also be reduced due to caregiving demands and limited bandwidth for self-care. In addition, the patient-caregiver relationship can be compromised, and communication patterns disrupted. All PA interventions in the hematopoietic cell transplantation setting have focused entirely on patients, ignoring an opportunity to synergistically engage and benefit the caregiver as well. Objective: To establish the feasibility and acceptability of a couple-based intervention entitled Family-Focused Facilitated Fitness (FFFF), designed to improve PA as assessed by daily step counts among both patients undergoing hematopoietic cell transplantation and their caregivers. Guided by interdependence and communal coping perspectives, FFFF is an 8-week, remotely-delivered intervention that provides training in communication skills and joint problem-solving to help patients and caregivers support one another in PA. Participants are also given a Fitbit to track their steps and weekly individualized step prescription based on the 75th percentile ranked value of their last 7 recorded daily step counts. A priori benchmarks for feasibility and acceptability were as follows: 50% of eligible couples would agree to participate, 70% of couples would attend all 8 sessions, 80% of participants would provide valid Fitbit wear data 4/7 days/ week, and among sessions reviewed for treatment fidelity, 85% of treatment protocol elements would be covered. Study design: Single-arm pilot intervention. Results: Couples were recruited prior to transplant. Among 26 couples approached and deemed eligible, 17 enrolled (65% agreement) and completed baseline assessment. Three couples later withdrew after transplantation but prior to receiving the intervention, resulting in 14 couples commencing the intervention, on average 21 days post-transplant. Four couples subsequently discontinued due to medical complications (n=3) or caregiver schedule (n=1). Among the 10 couples who completed the intervention, the percentage of participants meeting our benchmark of valid Fitbit wear at least 4 days per week was 85% in week 1, 90% in weeks 2-7, and 80% in week 8. Treatment fidelity was 95% on average across 24 sessions reviewed (3 cases). Treatment satisfaction scores were uniformly high across multiple dimensions, with all means above 4 on the 1-5 scale. Daily step counts among those attending all 8 intervention sessions increased from 2249 ± 302 steps/day in week 1 to 4975 ± 1377 steps/day in week 8 among patients, and from 8676 ± 3760 steps/day in week 1 to 9838 ± 3723 steps/day in week 8 among caregivers. Qualitative feedback indicated perceived mental and physical health benefits of the program. Participants also offered suggestions for adaptations to accommodate medical setbacks and constraints. Conclusion: All a priori feasibility benchmarks were met or exceeded. Results offer promise for utility of the program to engage and leverage patient-caregiver dyads to increase PA following transplant. An investigation using a randomized controlled design will be necessary to adequately examine change over time relative to control and its possible impact on clinical and patient-reported outcomes. Keywords: caregiver; couples; hematopoietic cell transplantation; physical activity.

Feasibility and preliminary effects of the Fit2ThriveMB pilot physical activity promotion intervention on physical activity and patient reported outcomes in individuals with metastatic breast cancer (2024)

Breast Cancer Research and Treatment

Authors: Phillips, Siobhan M.; Starikovsky, Julia; Solk, Payton; Desai, Ria; Reading, Jean M.; Hasanaj, Kristina; Wang, Shirlene D.; Cullather, Erin; Lee, Jungwha; Song, Jing; Spring, Bonnie; Gradishar, William

Abstract

PURPOSE: Physical activity research among patients with metastatic breast cancer (MBC) is limited. This study examined the feasibility and potential benefits of Fit2ThriveMB, a tailored mHealth intervention. METHODS: Insufficiently active individuals with MBC (n = 49) were randomized 1:1 to Fit2ThriveMB (Fit2ThriveMB app, Fitbit, and weekly coaching calls) or Healthy Lifestyle attention control (Cancer.Net app and weekly calls) for 12 weeks. Fit2ThriveMB aimed to increase daily steps via an algorithm tailored to daily symptom rating and step goal attainment. The primary outcome was feasibility defined as ≥ 80\% completion rate. Secondary feasibility metrics included meeting daily step goal and wearing the Fitbit ≥ 70\% of study days, fidelity, adherence to intervention features and safety. Secondary outcomes included physical activity, sedentary time, patient reported outcomes (PROs), health-related quality of life (QOL) and social cognitive theory constructs. A subsample (n = 25) completed functional performance tests via video conferencing. RESULTS: The completion rate was 98\% (n = 1 died). No related adverse events were reported. Fit2ThriveMB participants (n = 24) wore the Fitbit 92.7\%, met their step goal 53.1\%, set a step goal 84.6\% and used the app 94.1\% of 84 study days. Intent-to-treat analyses indicated trends toward improvements in activity, QOL, and some PROs, social cognitive theory constructs, and functional performance tests favoring the Fit2ThriveMB group. Significant effects favoring Fit2ThriveMB were observed for self-efficacy and goal-setting. However, some PROs and functional performance improvements favored the control group (p-values {\textgreater} 0.05). CONCLUSIONS: Fit2ThriveMB is feasible and safe for patients with MBC and warrants further evaluation in randomized controlled trials with larger sample sizes. Registration Clinicaltrials.gov NCT04129346, https://clinicaltrials.gov/ct2/show/NCT04129346.

Feasibility characteristics of wrist-worn fitness trackers in health status monitoring for post-COVID patients in remote and rural areas (2024)

PLOS digital health

Authors: Wiebe, Madeleine; Mackay, Marnie; Krishnan, Ragur; Tian, Julie; Larsson, Jakob; Modanloo, Setayesh; Job McIntosh, Christiane; Sztym, Melissa; Elton-Smith, Gail; Rose, Alyssa; Ho, Chester; Greenshaw, Andrew; Cao, Bo; Chan, Andrew; Hayward, Jake

Abstract

Introduction: Common, consumer-grade biosensors mounted on fitness trackers and smartwatches can measure an array of biometrics that have potential utility in post-discharge medical monitoring, especially in remote/rural communities. The feasibility characteristics for wrist-worn biosensors are poorly described for post-COVID conditions and rural populations. Methods: We prospectively recruited patients in rural communities who were enrolled in an at-home rehabilitation program for post-COVID conditions. They were asked to wear a FitBit Charge 2 device and biosensor parameters were analyzed [e.g. heart rate, sleep, and activity]. Electronic patient reported outcome measures [E-PROMS] for mental [bi-weekly] and physical [daily] symptoms were collected using SMS text or email [per patient preference]. Exit surveys and interviews evaluated the patient experience. Results: Ten patients were observed for an average of 58 days and half [N = 5] were monitored for 8 weeks or more. Five patients [50%] had been hospitalized with COVID [mean stay = 41 days] and 4 [36%] had required mechanical ventilation. As baseline, patients had moderate to severe levels of anxiety, depression, and stress; fatigue and shortness of breath were the most prevalent physical symptoms. Four patients [40%] already owned a smartwatch. In total, 575 patient days of patient monitoring occurred across 10 patients. Biosensor data was usable for 91.3% of study hours and surveys were completed 82.1% and 78.7% of the time for physical and mental symptoms, respectively. Positive correlations were observed between stress and resting heart rate [r = 0.360, p<0.01], stress and daily steps [r = 0.335, p<0.01], and anxiety and daily steps [r = 0.289, p<0.01]. There was a trend toward negative correlation between sleep time and physical symptom burden [r = -0.211, p = 0.05]. Patients reported an overall positive experience and identified the potential for wearable devices to improve medical safety and access to care. Concerns around data privacy/security were infrequent. Conclusions: We report excellent feasibility characteristics for wrist-worn biosensors and e-PROMS as a possible substrate for multi-modal disease tracking in post-COVID conditions. Adapting consumer-grade wearables for medical use and scalable remote patient monitoring holds great potential.

Feasibility of at-Home Sleep Monitoring in Adolescents with and without Concussion (2024)

Nature and Science of Sleep

Authors: Donahue, Catherine C.; Smulligan, Katherine L.; Wingerson, Mathew J.; Kniss, Joshua R.; Simon, Stacey L.; Wilson, Julie C.; Howell, David R.

Abstract

Background: Poor sleep is associated with longer recovery following adolescent concussion, making the longitudinal assessment of sleep important for monitoring recovery and identifying sleep disruptions. An important consideration for successful monitoring of sleep following concussion is the feasibility and adherence of a given sleep monitoring tool when used in an at-home environment. Understanding the usability of different sleep monitoring tools is essential for determining their applicability for longitudinal assessment in an ecologically valid environment. Purpose: The purpose of this study was to: (1) report on the adherence and feasibility of at-home sleep monitoring in adolescents following concussion, and (2) compare outcomes of subjective and wearable measures of sleep between adolescents with and without a concussion. Patients and methods: Participants included adolescents within 21 days of a concussion and uninjured controls that participated in four separate, prospective and longitudinal investigations of sleep following concussion. Sleep data was measured with: (1) Dreem Headband; (2) Philips Actiwatch; (3) Fitbit; and (4) subjective sleep diary. Sleep data was collected nightly, and adherence was defined as percentage of nights the participant used the sleep-monitoring tool over the study duration. Independent t-tests and effect sizes were calculated for the following sleep data outcomes as measured by each of the monitoring tools: duration, efficiency, latency, wake after sleep onset. Results: Sleep data for a total of 183 adolescents (104 with concussion, 79 uninjured controls) was assessed. Adherence rates across all devices ranged from 53% to 98%, with the subjective sleep diary showing the highest adherence rate for both groups (concussion: 91%, control: 94%). Across the four different monitoring tools, adolescents with a concussion demonstrated longer duration, latency, wake after sleep onset, and lower (worse) efficiency, with medium to large effect sizes. Conclusion: The results indicate that at-home sleep monitoring is a feasible approach for tracking sleep in adolescents following concussion.

Feasibility of Fit24, a Digital Diabetes Prevention Program for Hispanic Adolescents: Qualitative Evaluation Study (2024)

JMIR formative research

Authors: Soltero, Erica G.; Musaad, Salma M.; O'Connor, Teresia M.; Thompson, Debbe; Norris, Keith; Beech, Bettina M.

Abstract

Background: Digital health interventions are promising for reaching and engaging high-risk youth in disease prevention opportunities; however, few digital prevention interventions have been developed for Hispanic youth, limiting our knowledge of these strategies among this population. Objective: This study qualitatively assessed the feasibility and acceptability of Fit24, a 12-week goal-setting intervention that uses a Fitbit watch (Fitbit Inc) and theoretically grounded SMS text messages to promote physical activity and sleep among Hispanic adolescents (aged between 14 and 16 years) with obesity. Methods: After completing the intervention, a subsample of youth (N=15) participated in an in-depth interview. We categorized the themes into dimensions based on participant perspectives using the Practical, Robust Implementation, and Sustainability Model (PRISM) framework. Results: Participants shared positive perceptions of wearing the Fitbit and receiving SMS text messages. Youth were highly engaged in monitoring their behaviors and perceived increased activity and sleep. Almost all youth organically received social support from a peer or family member and suggested the use of a group chat or team challenge for integrating peers into future interventions. However, most youth also expressed the need to take personal responsibility for the change in their behavior. Barriers that impacted the feasibility of the study included the skin-irritating material on the Fitbit watch band and environmental barriers (eg, lack of resources and school schedules), that limited participation in activity suggestions. Additionally, sync issues with the Fitbit limited the transmission of data, leading to inaccurate feedback. Conclusions: Fit24 is a promising approach for engaging Hispanic youth in a diabetes prevention program. Strategies are needed to address technical issues with the Fitbit and environmental issues such as message timing. While integrating peer social support may be desired by some, peer support strategies should be mindful of youth's desire to foster personal motivation for behavior change. Findings from this study will inform future diabetes prevention trials of Fit24 and other digital health interventions for high-risk pediatric populations.

Feasibility of wearable sensor signals and self-reported symptoms to prompt at-home testing for acute respiratory viruses in the USA (DETECT-AHEAD): a decentralised, randomised controlled trial (2024)

The Lancet. Digital Health

Authors: Quer, Giorgio; Coughlin, Erin; Villacian, Jorge; Delgado, Felipe; Harris, Katherine; Verrant, John; Gadaleta, Matteo; Hung, Ting-Yang; Ter Meer, Janna; Radin, Jennifer M.; Ramos, Edward; Adams, Monique; Kim, Lomi; Chien, Jason W.; Baca-Motes, Katie; Pandit, Jay A.; Talantov, Dmitri; Steinhubl, Steven R.

Abstract

BACKGROUND: Early identification of an acute respiratory infection is important for reducing transmission and enabling earlier therapeutic intervention. We aimed to prospectively evaluate the feasibility of home-based diagnostic self-testing of viral pathogens in individuals prompted to do so on the basis of self-reported symptoms or individual changes in physiological parameters detected via a wearable sensor. METHODS: DETECT-AHEAD was a prospective, decentralised, randomised controlled trial carried out in a subpopulation of an existing cohort (DETECT) of individuals enrolled in a digital-only observational study in the USA. Participants aged 18 years or older were randomly assigned (1:1:1) with a block randomisation scheme stratified by under-represented in biomedical research status. All participants were offered a wearable sensor (Fitbit Sense smartwatch). Participants in groups 1 and 2 received an at-home self-test kit (Alveo be.well) for two acute respiratory viral pathogens: SARS-CoV-2 and respiratory syncytial virus. Participants in group 1 could be alerted through the DETECT study app to take the at-home test on the basis of changes in their physiological data (as detected by our algorithm) or due to self-reported symptoms; those in group 2 were prompted via the app to self-test only due to symptoms. Group 3 served as the control group, without alerts or home testing capability. The primary endpoints, assessed on an intention-to-treat basis, were the number of acute respiratory infections presented (self-reported) and diagnosed (electronic health record), and the number of participants using at-home testing in groups 1 and 2. This trial is registered with ClinicalTrials.gov, NCT04336020. FINDINGS: Between Sept 28 and Dec 30, 2021, 450 participants were recruited and randomly assigned to group 1 (n=149), group 2 (n=151), or group 3 (n=150). 179 (40\%) participants were male, 264 (59\%) were female, and seven (2\%) identified as other. 232 (52\%) were from populations historically under-represented in biomedical research. 118 (39\%) of the 300 participants in groups 1 and 2 were prompted to self-test, with 61 (52\%) successfully completing self-testing. Participants were prompted to home-test more frequently due to symptoms (41 [28\%] in group 1 and 51 [34\%] in group 2) than due to detected physiological changes (26 [17\%] in group 1). Significantly more participants in group 1 received alerts to test than did those in group 2 (67 [45\%] vs 51 [34\%]; p=0·047). Of the 61 individuals who were prompted to test and successfully did so, 19 (31\%) tested positive for a viral pathogen-all for SARS-CoV-2. The individuals diagnosed as positive for SARS-CoV-2 in the electronic health record were eight (5\%) in group 1, four (3\%) in group 2, and two (1\%) in group 3, but it was difficult to confirm if they were tied to symptomatic episodes documented in the trial. There were no adverse events. INTERPRETATION: In this direct-to-participant trial, we showed early feasibility of a decentralised programme to prompt individuals to use a viral pathogen diagnostic test based on symptoms tracked in the study app or physiological changes detected using a wearable sensor. Barriers to adequate participation and performance were also identified, which would need to be addressed before large-scale implementation. FUNDING: Janssen Pharmaceuticals.

Feasibility Study on Menstrual Cycles With Fitbit Device (FEMFIT): Prospective Observational Cohort Study (2024)

JMIR mHealth and uHealth

Authors: Lang, Anna-Lena; Bruhn, Rosa-Lotta; Fehling, Maya; Heidenreich, Anouk; Reisdorf, Jonathan; Khanyaree, Ifrah; Henningsen, Maike; Remschmidt, Cornelius

Abstract

Background: Despite its importance to women's reproductive health and its impact on women's daily lives, the menstrual cycle, its regulation, and its impact on health remain poorly understood. As conventional clinical trials rely on infrequent in-person assessments, digital studies with wearable devices enable the collection of longitudinal subjective and objective measures. Objective: The study aims to explore the technical feasibility of collecting combined wearable and digital questionnaire data and its potential for gaining biological insights into the menstrual cycle. Methods: This prospective observational cohort study was conducted online over 12 weeks. A total of 42 cisgender women were recruited by their local gynecologist in Berlin, Germany, and given a Fitbit Inspire 2 device and access to a study app with digital questionnaires. Statistical analysis included descriptive statistics on user behavior and retention, as well as a comparative analysis of symptoms from the digital questionnaires with metrics from the sensor devices at different phases of the menstrual cycle. Results: The average time spent in the study was 63.3 (SD 33.0) days with 9 of the 42 individuals dropping out within 2 weeks of the start of the study. We collected partial data from 114 ovulatory cycles, encompassing 33 participants, and obtained complete data from a total of 50 cycles. Participants reported a total of 2468 symptoms in the daily questionnaires administered during the luteal phase and menses. Despite difficulties with data completeness, the combined questionnaire and sensor data collection was technically feasible and provided interesting biological insights. We observed an increased heart rate in the mid and end luteal phase compared with menses and participants with severe premenstrual syndrome walked substantially fewer steps (average daily steps 10,283, SD 6277) during the luteal phase and menses compared with participants with no or low premenstrual syndrome (mean 11,694, SD 6458). Conclusions: We demonstrate the feasibility of using an app-based approach to collect combined wearable device and questionnaire data on menstrual cycles. Dropouts in the early weeks of the study indicated that engagement efforts would need to be improved for larger studies. Despite the challenges of collecting wearable data on consecutive days, the data collected provided valuable biological insights, suggesting that the use of questionnaires in conjunction with wearable data may provide a more complete understanding of the menstrual cycle and its impact on daily life. The biological findings should motivate further research into understanding the relationship between the menstrual cycle and objective physiological measurements from sensor devices. Keywords: PMS; digital health; menstrual cycle; mobile app; premenstrual syndrome; sensor data; wearable device; women’s health.

From intention to behavior: Within- and between-person moderators of the relationship between intention and physical activity (2024)

Psychology of Sport and Exercise

Authors: Knapova, Lenka; Cho, Young Won; Chow, Sy-Miin; Kuhnova, Jitka; Elavsky, Steriani

Abstract

Intention is a proximal predictor of behavior in many theories of behavior change, but intentions to be physically active do not always translate to actual physical activity. Little research has examined intensive longitudinal changes in physical activity and corresponding within-person moderators needed to elucidate the mechanisms, hurdles, and facilitators of individuals' everyday physical activity behaviors. The present study set out to evaluate the possible moderators of the intention-physical activity relationship across within-person and between-person levels, including cross-level interactions. Data comprise the first intensive measurement burst (14 days) of the longitudinal prospective Healthy Aging in Industrial Environment (HAIE) study, with N = 1135 participants (N = 10,030 person-days), aged 18-65. Physical activity was operationalized as step counts measured objectively using Fitbit Charge 3/4 fitness monitor. Intention, barriers to physical activity, and social support for physical activity were measured daily via smartphone surveys. Stable characteristics, i.e., physical activity habit and exercise identity, were measured using an online questionnaire. A multilevel moderation regression model with Bayesian estimator was fitted. At the within-person level, the relation between intention and steps was weaker on days when barriers were more severe than usual for a given person (Estimate = -0.267; CI95 = [-0.340, -0.196]) and social support was below average for a given person (Est = 0.143; CI95 = [0.023, 0.262]). Additionally, the daily intention-behavior relationship was stronger for people with lower average severity of barriers (Est = -0.153; CI95 = [-0.268, -0.052]), higher exercise identity (Est = 0.300; CI95 = [0.047, 0.546]), men (Est = -1.294, CI95 = [-1.854, -0.707]), and older individuals (Est = 0.042, CI95 = [0.017, 0.064]). At the between-person level, only physical activity habit strengthened the intention-behavior link (Est = 0.794; CI95 = [0.090, 1.486]). Our results underscore the need to separate the between-person differences from the within-person fluctuations to better understand the individual dynamics in physical activity behaviors. Personalized interventions aimed at helping individuals translate intentions to actual physical activity could be tailored and become more intensive when there is a higher risk of intention-behavior gap on a given day for a specific individual (i.e., a day with more severe barriers and less social support), by increasing the dosage or deploying more precisely targeted intervention strategies and components. In addition, interventionists should take gender and age into account when tailoring everyday strategies to help individuals act on their intentions. Keywords: Barriers; Intention; Intention-behavior gap; Physical activity; Social support.

Healthy at Home for COPD: An Integrated Digital Monitoring, Treatment, and Pulmonary Rehabilitation Intervention (2024)

Research Square

Authors: O'Connor, Laurel; Behar, Stephanie; Tarrant, Seanan; Stamegna, Pamela; Pretz, Caitlin; Shirshac, Jeanne; Scornavacca, Thomas; Wilkie, Tracey; Fisher, Kimberly; Tigas, Emil; Mullen, Marie; Hyder, Michael; Wong, Steven; Savage, Brendon; Toomey, Shaun; Wang, Biqi; Zai, Adrian; Alper, Eric; Lindenauer, Peter; Dickson, Eric; Broach, John; McManus, David; Kheterpal, Vik; Soni, Apurv

Abstract

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbidity and mortality in the United States. Frequent exacerbations result in higher use of emergency services and hospitalizations, leading to poor patient outcomes and high costs. OBJECTIVE: Demonstrate the feasibility of a multimodal, digitally enhanced remote monitoring, treatment, and tele-pulmonary rehabilitation intervention among patients with COPD. METHODS: In this pilot clinical trial, community-dwelling adults with moderate-severe COPD were enrolled in a multimodal digital monitoring and treatment program including a Fitbit wearable device, study app that tracked COPD-related symptoms, on-demand mobile integrated health (MIH) services for acute home-based treatment, and tele-pulmonary-rehabilitation. Participants were enrolled in the program for six months. COPD severity and health-related quality of life assessments were performed at baseline, 3 months, and 6 months. Primary feasibility outcomes include recruitment and retention rate, and participant protocol fidelity, which were reported descriptively. Exploratory clinical outcomes included patient-reported quality of life, activation, and intervention satisfaction. RESULTS: Over 18 months, 1,333 patients were approached and 100 (7.5\%) were enrolled (mean age 66, 52\% female). Ninety-six participants (96\%) remained in the study for the full enrollment period. Fifty-five (55\%) participated in tele-pulmonary-rehabilitation. Participants wore the Fitbit for a median of 114 days (IQR 183.6) and 16.85 hours/day (4.05), resulting in a median of 1133 minutes (243) per day. Completion rates for scheduled instruments ranged from 78-93\%. Nearly all participants (85\%) performed COPD ecological momentary assessment at least once with a median of 4.85 recordings. On average, a 2.48-point improvement (p=0.03) in COPD Assessment Test Score was observed from baseline to study completion. The adherence and symptom improvement metrics were not associated with baseline patient activation measures. CONCLUSIONS: A multimodal intervention combining preventative care, symptom and biometric monitoring, and home treatment was feasible in adults living with COPD. Participants demonstrated high protocol fidelity and engagement and reported improved quality of life.

Heart Rate Monitoring Among Breast Cancer Survivors: Quantitative Study of Device Agreement in a Community-Based Exercise Program (2024)

JMIR cancer

Authors: Page, Lindsey L.; Fanning, Jason; Phipps, Connor; Berger, Ann; Reed, Elizabeth; Ehlers, Diane

Abstract

BACKGROUND: Exercise intensity (eg, target heart rate [HR]) is a fundamental component of exercise prescription to elicit health benefits in cancer survivors. Despite the validity of chest-worn monitors, their feasibility in community and unsupervised exercise settings may be challenging. As wearable technology continues to improve, consumer-based wearable sensors may represent an accessible alternative to traditional monitoring, offering additional advantages. OBJECTIVE: The purpose of this study was to examine the agreement between the Polar H10 chest monitor and Fitbit Inspire HR for HR measurement in breast cancer survivors enrolled in the intervention arm of a randomized, pilot exercise trial. METHODS: Participants included breast cancer survivors (N=14; aged 38-72 years) randomized to a 12-week aerobic exercise program. This program consisted of three 60-minute, moderate-intensity walking sessions per week, either in small groups or one-on-one, facilitated by a certified exercise physiologist and held at local community fitness centers. As originally designed, the exercise prescription included 36 supervised sessions at a fitness center. However, due to the COVID-19 pandemic, the number of supervised sessions varied depending on whether participants enrolled before or after March 2020. During each exercise session, HR (in beats per minute) was concurrently measured via a Polar H10 chest monitor and a wrist-worn Fitbit Inspire HR at 5 stages: pre-exercise rest; midpoint of warm-up; midpoint of exercise session; midpoint of cool-down; and postexercise recovery. The exercise physiologist recorded the participant's HR from each device at the midpoint of each stage. HR agreement between the Polar H10 and Fitbit Inspire HR was assessed using Lin concordance correlation coefficient (rc) with a 95\% CI. Lin rc ranges from 0 to 1.00, with 0 indicating no concordance and 1.00 indicating perfect concordance. Relative error rates were calculated to examine differences across exercise session stages. RESULTS: Data were available for 200 supervised sessions across the sample (session per participant: mean 13.33, SD 13.7). By exercise session stage, agreement between the Polar H10 monitor and the Fitbit was highest during pre-exercise seated rest (rc=0.76, 95\% CI 0.70-0.81) and postexercise seated recovery (rc=0.89, 95\% CI 0.86-0.92), followed by the midpoint of exercise (rc=0.63, 95\% CI 0.55-0.70) and cool-down (rc=0.68, 95\% CI 0.60-0.74). The agreement was lowest during warm-up (rc=0.39, 95\% CI 0.27-0.49). Relative error rates ranged from -3.91\% to 3.09\% and were greatest during warm-up (relative error rate: mean -3.91, SD 11.92\%). CONCLUSIONS: The Fitbit overestimated HR during peak exercise intensity, posing risks for overexercising, which may not be safe for breast cancer survivors' fitness levels. While the Fitbit Inspire HR may be used to estimate exercise HR, precautions are needed when considering participant safety and data interpretation. TRIAL REGISTRATION: Clinicaltrials.gov NCT03980626; https://clinicaltrials.gov/study/NCT03980626?term=NCT03980626\&rank=1.

Improving multimodal physical function in adults with heterogeneous chronic pain; Protocol for a multisite feasibility RCT (2024)

Contemporary Clinical Trials

Authors: Hooker, Julia E.; Brewer, Julie R.; McDermott, Katherine; Kanaya, Millan; Somers, Tamara J.; Keefe, Francis; Kelleher, Sarah; Fisher, Hannah M.; Burns, John; Wilson, Rebecca; Kulich, Ronald; Polykoff, Gary; Parker, Robert A.; Greenberg, Jonathan; Vranceanu, Ana-Maria; THRIVE Study TeamJennifer Plumb-Vilardaga, PhD. Shannon Miller, Allison Diachina, Sara Hogan, Latrice Yates

Abstract

Background: Chronic pain is associated with substantial impairment in physical function, which has been identified as a top concern among persons with pain. GetActive-Fitbit, a mind-body activity program, is feasible, acceptable, and associated with improvement in physical function among primarily White, sedentary individuals with pain. In preparation for a multisite efficacy trial, we must examine feasibility across multiple sites with diverse patient populations. Here we describe the protocol of a multisite, feasibility RCT comparing GetActive-Fitbit with a time- and attention-matched educational comparison (Healthy Living for Pain). We aim to 1) test multisite fidelity of clinician training; 2) evaluate multisite feasibility benchmarks, including recruitment of chronic pain patients taking <5000 steps/day and racial and ethnic minorities; and 3) optimize fidelity and study protocol in preparation for a future multisite efficacy trial. Methods: Clinician training fidelity was assessed via roleplays and mock group sessions. Feasibility (i.e., recruitment, acceptability, credibility, adherence, satisfaction), multimodal physical function (e.g., self-report, 6-Minute Walk Test, step-count), and other psychosocial outcomes are assessed at baseline, posttest, and 6 months. Protocol optimization will be assessed using exit interviews and cross-site meetings. Results: The trial is ongoing. Clinician training is complete. 87 participants have been recruited. 54 completed baseline assessments and randomization, 44 are mid-intervention, and 9 have completed the intervention and posttest. Conclusions: This study addresses the critical need for feasible, acceptable mind-body-activity interventions for chronic pain that follow evidence-based guidelines and improve all aspects of physical function across diverse populations. Results will inform a future fully-powered multisite efficacy trial.

Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis (2024)

Journal of Medical Internet Research

Authors: Zhang, Yuezhou; Folarin, Amos A.; Sun, Shaoxiong; Cummins, Nicholas; Ranjan, Yatharth; Rashid, Zulqarnain; Stewart, Callum; Conde, Pauline; Sankesara, Heet; Laiou, Petroula; Matcham, Faith; White, Katie M.; Oetzmann, Carolin; Lamers, Femke; Siddi, Sara; Simblett, Sara; Vairavan, Srinivasan; Myin-Germeys, Inez; Mohr, David C.; Wykes, Til; Haro, Josep Maria; Annas, Peter; Penninx, Brenda Wjh; Narayan, Vaibhav A.; Hotopf, Matthew; Dobson, Richard Jb; RADAR-CNS consortium

Abstract

BACKGROUND: Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings. OBJECTIVE: This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts. METHODS: Data were sourced from a large longitudinal mHealth study, wherein participants' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score. RESULTS: Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2\% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (β=-93.61, P{\textless}.001), increased sleep variability (β=0.96, P{\textless}.001), and delayed circadian rhythms (ie, sleep onset: β=0.55, P=.001; sleep offset: β=1.12, P{\textless}.001; M10 onset: β=0.73, P=.003; HR acrophase: β=0.71, P=.001). Notably, the negative association with daily steps was more pronounced in spring (β of PHQ-8 × spring = -31.51, P=.002) and summer (β of PHQ-8 × summer = -42.61, P{\textless}.001) compared with winter. Additionally, the significant correlation with delayed M10 onset was observed solely in summer (β of PHQ-8 × summer = 1.06, P=.008). Moreover, compared with winter, participants experienced a shorter sleep duration by 16.6 minutes, an increase in daily steps by 394.5, a delay in M10 onset by 20.5 minutes, and a delay in HR peak time by 67.9 minutes during summer. CONCLUSIONS: Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.

Modeling engagement with a digital behavior change intervention (HeartSteps II): An exploratory system identification approach (2024)

Journal of Biomedical Informatics

Authors: De La Torre, Steven A.; El Mistiri, Mohamed; Hekler, Eric; Klasnja, Predrag; Marlin, Benjamin; Pavel, Misha; Spruijt-Metz, Donna; Rivera, Daniel E.

Abstract

OBJECTIVE: Digital behavior change interventions (DBCIs) are feasibly effective tools for addressing physical activity. However, in-depth understanding of participants' long-term engagement with DBCIs remains sparse. Since the effectiveness of DBCIs to impact behavior change depends, in part, upon participant engagement, there is a need to better understand engagement as a dynamic process in response to an individual's ever-changing biological, psychological, social, and environmental context. METHODS: The year-long micro-randomized trial (MRT) HeartSteps II provides an unprecedented opportunity to investigate DBCI engagement among ethnically diverse participants. We combined data streams from wearable sensors (Fitbit Versa, i.e., walking behavior), the HeartSteps II app (i.e. page views), and ecological momentary assessments (EMAs, i.e. perceived intrinsic and extrinsic motivation) to build the idiographic models. A system identification approach and a fluid analogy model were used to conduct autoregressive with exogenous input (ARX) analyses that tested hypothesized relationships between these variables inspired by Self-Determination Theory (SDT) with DBCI engagement through time. RESULTS: Data from 11 HeartSteps II participants was used to test aspects of the hypothesized SDT dynamic model. The average age was 46.33 (SD=7.4) years, and the average steps per day at baseline was 5,507 steps (SD=6,239). The hypothesized 5-input SDT-inspired ARX model for app engagement resulted in a 31.75 \% weighted RMSEA (31.50 \% on validation and 31.91 \% on estimation), indicating that the model predicted app page views almost 32 \% better relative to the mean of the data. Among Hispanic/Latino participants, the average overall model fit across inventories of the SDT fluid analogy was 34.22 \% (SD=10.53) compared to 22.39 \% (SD=6.36) among non-Hispanic/Latino Whites, a difference of 11.83 \%. Across individuals, the number of daily notification prompts received by the participant was positively associated with increased app page views. The weekend/weekday indicator and perceived daily busyness were also found to be key predictors of the number of daily application page views. CONCLUSIONS: This novel approach has significant implications for both personalized and adaptive DBCIs by identifying factors that foster or undermine engagement in an individual's respective context. Once identified, these factors can be tailored to promote engagement and support sustained behavior change over time.

Optimization of mHealth behavioral interventions for patients with chronic lymphocytic leukemia: the HEALTH4CLL study (2024)

Journal of Cancer Survivorship: Research and Practice

Authors: Lee, Che Young; Gordon, Max J.; Markofski, Melissa M.; LaVoy, Emily C.; Peterson, Susan K.; Li, Liang; Fares, Sara; Baum, Miranda; Pace, Margaret; Walsh, Danielle; Ferrajoli, Alessandra; Basen-Engquist, Karen

Abstract

Purpose: This pilot study of a diet and physical activity intervention (HEALTH4CLL) was conducted to reduce fatigue and improve physical function (PF) in patients with chronic lymphocytic leukemia (CLL). Methods: The HEALTH4CLL study used a randomized factorial design based on the multiphase optimization strategy (MOST). Patients received diet, exercise, and body weight management instructional materials plus a Fitbit and were randomized to undergo one of 16 combinations of 4 evidence-based mHealth intervention strategies over 16 weeks. Patients' fatigue, PF, health-related quality of life, behavior changes, and program satisfaction and retention were assessed. Paired t-tests were used to examine changes in outcomes from baseline to follow-up among patients. Factorial analysis of variance examined effective intervention components and their combinations regarding improvement in fatigue and PF scores. Results: Among 31 patients, we observed significant improvements in fatigue (+ 11.8; t = 4.08, p = 0.001) and PF (+ 2.6; t = 2.75, p = 0.01) scores. The combination of resistance and aerobic exercise with daily self-monitoring was associated with improved fatigue scores (β = 3.857, SE = 1.617, p = 0.027). Analysis of the individual components of the MOST design demonstrated greater improvement in the PF score with resistance plus aerobic exercise than with aerobic exercise alone (β = 2.257, SE = 1.071, p = 0.048). Conclusions: Combined aerobic and resistance exercise and daily self-monitoring improved PF and reduced fatigue in patients with CLL. Implications for cancer survivors: This pilot study supported the feasibility of a low-touch mHealth intervention for survivors of CLL and provided preliminary evidence that exercising, particularly resistance exercise, can improve their symptoms and quality of life. Keywords: Cancer; Exercise; Non-Hodgkin lymphoma; Nutrition; Physical activity; Skeletal muscle function.

Participatory development of an mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED) (2024)

BMC public health

Authors: Novak, Jan; Jurkova, Katerina; Lojkaskova, Anna; Jaklova, Andrea; Kuhnova, Jitka; Pfeiferova, Marketa; Kral, Norbert; Janek, Michael; Omcirk, Dan; Malisova, Katerina; Maes, Iris; Dyck, Delfien Van; Wahlich, Charlotte; Ussher, Michael; Elavsky, Steriani; Cimler, Richard; Pelclova, Jana; Tufano, James J.; Steffl, Michal; Seifert, Bohumil; Yates, Tom; Harris, Tess; Vetrovsky, Tomas

Abstract

BACKGROUND: The escalating global prevalence of type 2 diabetes and prediabetes presents a major public health challenge. Physical activity plays a critical role in managing (pre)diabetes; however, adherence to physical activity recommendations remains low. The ENERGISED trial was designed to address these challenges by integrating mHealth tools into the routine practice of general practitioners, aiming for a significant, scalable impact in (pre)diabetes patient care through increased physical activity and reduced sedentary behaviour. METHODS: The mHealth intervention for the ENERGISED trial was developed according to the mHealth development and evaluation framework, which includes the active participation of (pre)diabetes patients. This iterative process encompasses four sequential phases: (a) conceptualisation to identify key aspects of the intervention; (b) formative research including two focus groups with (pre)diabetes patients (n = 14) to tailor the intervention to the needs and preferences of the target population; (c) pre-testing using think-aloud patient interviews (n = 7) to optimise the intervention components; and (d) piloting (n = 10) to refine the intervention to its final form. RESULTS: The final intervention comprises six types of text messages, each embodying different behaviour change techniques. Some of the messages, such as those providing interim reviews of the patients' weekly step goal or feedback on their weekly performance, are delivered at fixed times of the week. Others are triggered just in time by specific physical behaviour events as detected by the Fitbit activity tracker: for example, prompts to increase walking pace are triggered after 5 min of continuous walking; and prompts to interrupt sitting following 30 min of uninterrupted sitting. For patients without a smartphone or reliable internet connection, the intervention is adapted to ensure inclusivity. Patients receive on average three to six messages per week for 12 months. During the first six months, the text messaging is supplemented with monthly phone counselling to enable personalisation of the intervention, assistance with technical issues, and enhancement of adherence. CONCLUSIONS: The participatory development of the ENERGISED mHealth intervention, incorporating just-in-time prompts, has the potential to significantly enhance the capacity of general practitioners for personalised behavioural counselling on physical activity in (pre)diabetes patients, with implications for broader applications in primary care.

Physical Activity and Sedentary Time Among U.S. Adolescents Before and During COVID-19: Findings From a Large Cohort Study (2024)

AJPM focus

Authors: Hunt, Ethan T.; Brazendale, Keith; De Moraes, Augusto C. F.; Malkani, Raja; Heredia, Natalia I.; Pfledderer, Christopher D.; Brown, Denver M.; Hoelscher, Deanna M.; Beets, Michael W.; Weaver, Robert G.

Abstract

Introduction: Evidence suggests that adolescents engage in less physical activity during the summer break. Less is known regarding physical activity during the summer months of the COVID-19 pandemic. Methods: Utilizing data from the Adolescent Brain Cognitive Development study, the authors examined daily activity measured by Fitbit Charge 2 devices before and after the onset of the COVID-19 pandemic during school and summer months. Linear models estimated activity during pre-COVID-19 school, pre-COVID-19 summer, COVID-19 school, and COVID-19 summer. Results: Participants (N=7,179, aged 11.96 years, 51% female, 51% White) accumulated 8,671.0 (95% CI=8,544.7; 8,797.3) steps, 32.5 (95% CI=30.8, 32.3) minutes of moderate-to-vigorous physical activity, and 507.2 (95% CI=504.2, 510.2) minutes of sedentary time. During COVID-19 school, adolescents accumulated fewer daily steps and minutes of moderate-to-vigorous physical activity (-1,782.3 steps [95% CI= -2,052.7; -1,511.8] and -6.2 minutes [95% CI= -8.4, -4.0], respectively). Adolescents accumulated more minutes of daily sedentary time (29.6 minutes [95% CI=18.9, 40.3]) during COVID-19 school months than during the pre-COVID-19 school months. During pre-COVID-19 summer months, adolescents accumulated 1,255.1 (95% CI=745.3; 1,765.0) more daily steps than during COVID-19 months. Boys accumulated more daily steps and moderate-to-vigorous physical activity (2,011.5 steps [95% CI=1,271.9; 2,751.0] and 7.9 minutes [95% CI=1.4, 14.4], respectively) during the summer before COVID-19 than in summer during COVID-19. Both girls and boys accumulated more minutes of sedentary time during COVID-19 school months (47.4 [95% CI=27.5, 67.3] and 51.2 [95% CI=22.8, 79.7], respectively) than during COVID-19 summer months. Conclusions: Societal restrictions during COVID-19 negatively impacted activity levels in the U.S., particularly during the summer months during COVID-19. Keywords: COVID-19; adolescents; physical activity; summer.

Physical activity decreases in patients on the liver transplant waiting list and influences postoperative outcome-a prospective cohort study (2024)

Hepatobiliary Surgery and Nutrition

Authors: Magyar, Christian T. J.; Bühlmann, Lea; Becchetti, Chiara; Beekman, Lara; Candinas, Daniel; Beldi, Guido; Kim-Fuchs, Corina; Berzigotti, Annalisa; Banz, Vanessa

Abstract

BACKGROUND: Physical deconditioning affects patients suffering from end-stage liver disease (ESLD). Liver transplantation (LT) is the only curative option for ESLD. Growing evidence suggests that pre-habilitation is beneficial in reducing post-surgical morbidity and mortality. We investigated physical activity (PA) in patients awaiting LT in a country with long waiting times. METHODS: Prospective, single center, longitudinal study in Bern, Switzerland between June 2019 and February 2020 (halted due to SARS-CoV-2 pandemic), with follow-up data up to six months post-transplant. Patients were instructed to use a wrist tracker (FitBit) to monitor PA, which was assessed using mixed-effects generalized linear models. The study was approved by the local ethics committee (BASEC ID 2019-00606). RESULTS: Thirty-five patients were included [71\% male, median 59 years, body mass index (BMI) 28 kg/m2, lab Model End-Stage Liver Disease (MELD) 11], 17 (49\%) pre-frail and 5 (14\%) frail according to the Liver Frailty Index (LFI). Twenty-eight patients underwent transplantation with 0 ninety-day mortality and 15 (53.6\%) composite adverse clinical outcome. Median daily steps were 4,661 [interquartile range (IQR), 1,685-8,609] and weekly moderate PA (MPA) was 41 min (IQR, 0-127 min). Longitudinal analysis showed that female patients and patients on nutritional support had an increase in MPA between weeks 20 and 40. A significant decrease was seen in MPA after week 40, whilst no significant association was seen with age, Child-Pugh Score, LFI or quality of life at time of inclusion. MPA was significantly associated with the occurrence of the composite clinical endpoint after week 30 of waiting time (odds ratio 0.882, P=0.026). World Health Organization (WHO)-recommended MPA was significantly associated with less adverse composite clinical outcomes (P{\textless}0.001). CONCLUSIONS: In patients listed for LT, MPA decreased over time, showing a significant association with adverse outcome, specifically after week 30 on the waiting list. Our data support the implementation of routine pre-habilitation in patients awaiting LT.

Pilot evaluation on an adapted tele-behavioral activation to increase physical activity in persons with depression: a single-arm pilot study (2024)

BMC psychology

Authors: Rethorst, Chad D.; Trombello, Joseph M.; Chen, Patricia M.; Carmody, Thomas J.; Goodman, Lynnel C.; Lazalde, Alejandra; Trivedi, Madhukar H.

Abstract

BACKGROUND: Physical activity has the potential to improve physical and mental health outcomes of persons with depression. However, feasible and acceptable strategies to integrate physical activity interventions into real-world settings are needed. OBJECTIVE: To assess the feasibility and acceptability of a manualized Behavioral Activation intervention aimed to increase physical activity in persons with depression (defined as a PHQ-9 score ≥ 10). METHODS: A single-arm pilot study was conducted. The intervention consisted of 8 tele-therapy sessions delivered over a 10-week period. Measures of feasibility included screening, enrollment, intervention adherence, outcome data availability, and intervention fidelity. Acceptability was assessed with a post-intervention survey and qualitatively through focus groups and interviews. Preliminary efficacy of the intervention was assessed by evaluating pre-to-post changes in physical activity and depressive symptoms. RESULTS: All feasibility metrics exceeded predetermined feasibility goal metrics with the exception of Fitbit wear and screening rate, which was due to a greater than anticipated enrollment rate. Participants (n = 15) reported perceived benefits from the intervention and convenience in attending tele-therapy sessions. Depressive symptoms, as measured by the PHQ-9 improved (16.8 at enrollment to 10.1 post intervention, Cohen's d = 1.13). Self-reported moderate-to-vigorous physical activity (MVPA) increased from 22.0 min/week at baseline to 36.67 min/week post-intervention (d = 0.58). Physical activity as measured by the Fitbit showed little change (daily step 5543.29 during Week 1 to 6177.48 during Week 10, (d = 0.14); MVPA 21.23 min/week during Week 1 to 19.22 at Week 10 (d = 0.0.06). CONCLUSIONS: Results of the pilot study suggest the intervention is feasible to deliver and acceptable to participants. Preliminary results suggest the intervention may be effective in improving depressive symptoms and increasing self-reported physical activity. TRIAL REGISTRATION: ClinicalTrials.gov NCT04990401, Registered July 21, 2021.

Rationale, Design, and Baseline Characteristics of Participants in the Health@NUS mHealth Augmented Cohort Study Examining Student-to-Work Life Transition: Protocol for a Prospective Cohort Study (2024)

JMIR research protocols

Authors: Chua, Xin Hui; Edney, Sarah Martine; Müller, Andre Matthias; Petrunoff, Nicholas A.; Whitton, Clare; Tay, Zoey; Goh, Claire Marie Jie Lin; Chen, Bozhi; Park, Su Hyun; Rebello, Salome A.; Low, Alicia; Chia, Janelle; Koek, Daphne; Cheong, Karen; van Dam, Rob M.; Müller-Riemenschneider, Falk

Abstract

BACKGROUND: Integration of mobile health data collection methods into cohort studies enables the collection of intensive longitudinal information, which gives deeper insights into individuals' health and lifestyle behavioral patterns over time, as compared to traditional cohort methods with less frequent data collection. These findings can then fill the gaps that remain in understanding how various lifestyle behaviors interact as students graduate from university and seek employment (student-to-work life transition), where the inability to adapt quickly to a changing environment greatly affects the mental well-being of young adults. OBJECTIVE: This paper aims to provide an overview of the study methodology and baseline characteristics of participants in Health@NUS, a longitudinal study leveraging mobile health to examine the trajectories of health behaviors, physical health, and well-being, and their diverse determinants, for young adults during the student-to-work life transition. METHODS: University students were recruited between August 2020 and June 2022 in Singapore. Participants would complete biometric assessments and questionnaires at 3 time points (baseline, 12-, and 24-month follow-up visits) and use a Fitbit smartwatch and smartphone app to continuously collect physical activity, sedentary behavior, sleep, and dietary data over the 2 years. Additionally, up to 12 two-week-long bursts of app-based ecological momentary surveys capturing lifestyle behaviors and well-being would be sent out among the 3 time points. RESULTS: Interested participants (n=1556) were screened for eligibility, and 776 participants were enrolled in the study between August 2020 and June 2022. Participants were mostly female (441/776, 56.8\%), of Chinese ethnicity (741/776, 92\%), undergraduate students (759/776, 97.8\%), and had a mean BMI of 21.9 (SD 3.3) kg/m2, and a mean age of 22.7 (SD 1.7) years. A substantial proportion were overweight (202/776, 26.1\%) or obese (42/776, 5.4\%), had indicated poor mental well-being (World Health Organization-5 Well-Being Index ≤50; 291/776, 37.7\%), or were at higher risk for psychological distress (Kessler Psychological Distress Scale ≥13; 109/776, 14.1\%). CONCLUSIONS: The findings from this study will provide detailed insights into the determinants and trajectories of health behaviors, health, and well-being during the student-to-work life transition experienced by young adults. TRIAL REGISTRATION: ClinicalTrials.gov NCT05154227; https://clinicaltrials.gov/study/NCT05154227. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56749.

Real-time biopsychosocial antecedents and correlates of functional neurological symptoms in daily life: A pilot remote monitoring technology study (2024)

Psychiatry Research

Authors: Pick, Susannah; Millman, L. S. Merritt; Davies, Jessica; Hodsoll, John; Stanton, Biba; David, Anthony S.; Edwards, Mark J.; Goldstein, Laura H.; Mehta, Mitul A.; Nicholson, Timothy R.; Reinders, A. a. T. S.; Winston, Joel S.; Chalder, Trudie; Hotopf, Matthew

Abstract

Functional neurological symptom disorder (FNSD) is a neuropsychiatric diagnosis referring to symptoms resembling those of neurological disorders, occurring without causal neuropathology. FNSD has a complex biopsychosocial aetiology but its mechanisms are poorly understood. Remote monitoring technologies (RMT) could provide critical insights into functional neurological symptoms (FNS) in real-world contexts. We examined the feasibility and acceptability of a novel RMT protocol, to identify psychobiological correlates and antecedents of FNS in everyday life. Seventeen individuals with FNS (seizures/motor) and 17 healthy controls (HC) completed ecological momentary assessments (EMA) eight times daily for 1-week, reporting FNS severity, associated physical and psychological symptoms, and subjectively significant events. Sleep quality was reported daily. Physiological variables were measured using wearable Fitbit 5 devices. Multilevel modelling examined variables associated with FNS variability. Average EMA completion rates were good in both groups (≥80\%). At week-level, the FNS group reported significantly greater subjective arousal, pain, fatigue, dissociation, negative affect, daily events, stressful events, and sleep duration, compared to HC. Objective sleep disturbance and duration, and resting heartrate, were also significantly greater in the FNS sample. FNS severity correlated significantly with daily events, affect, subjective arousal, pain, fatigue and sleep disturbance, at day- or within-day levels. Daily events and negative affect were the most prominent time-lagged predictors of within-day moment-to-moment FNS severity. RMTs are feasible and acceptable tools for investigation of FNS in real-world settings, revealing daily events and negative affect as possible triggers of FNS. Interventions targeting affective reactivity and regulation might be beneficial in this group. Larger-scale, longer-term RMT studies are needed in this population.

Real-World Accuracy of Wearable Activity Trackers for Detecting Medical Conditions: Systematic Review and Meta-Analysis (2024)

JMIR mHealth and uHealth

Authors: Singh, Ben; Chastin, Sebastien; Miatke, Aaron; Curtis, Rachel; Dumuid, Dorothea; Brinsley, Jacinta; Ferguson, Ty; Szeto, Kimberley; Simpson, Catherine; Eglitis, Emily; Willems, Iris; Maher, Carol

Abstract

Background: Wearable activity trackers, including fitness bands and smartwatches, offer the potential for disease detection by monitoring physiological parameters. However, their accuracy as specific disease diagnostic tools remains uncertain. Objective: This systematic review and meta-analysis aims to evaluate whether wearable activity trackers can be used to detect disease and medical events. Methods: Ten electronic databases were searched for studies published from inception to April 1, 2023. Studies were eligible if they used a wearable activity tracker to diagnose or detect a medical condition or event (eg, falls) in free-living conditions in adults. Meta-analyses were performed to assess the overall area under the curve (%), accuracy (%), sensitivity (%), specificity (%), and positive predictive value (%). Subgroup analyses were performed to assess device type (Fitbit, Oura ring, and mixed). The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Diagnostic Test Accuracy Studies. Results: A total of 28 studies were included, involving a total of 1,226,801 participants (age range 28.6-78.3). In total, 16 (57%) studies used wearables for diagnosis of COVID-19, 5 (18%) studies for atrial fibrillation, 3 (11%) studies for arrhythmia or abnormal pulse, 3 (11%) studies for falls, and 1 (4%) study for viral symptoms. The devices used were Fitbit (n=6), Apple watch (n=6), Oura ring (n=3), a combination of devices (n=7), Empatica E4 (n=1), Dynaport MoveMonitor (n=2), Samsung Galaxy Watch (n=1), and other or not specified (n=2). For COVID-19 detection, meta-analyses showed a pooled area under the curve of 80.2% (95% CI 71.0%-89.3%), an accuracy of 87.5% (95% CI 81.6%-93.5%), a sensitivity of 79.5% (95% CI 67.7%-91.3%), and specificity of 76.8% (95% CI 69.4%-84.1%). For atrial fibrillation detection, pooled positive predictive value was 87.4% (95% CI 75.7%-99.1%), sensitivity was 94.2% (95% CI 88.7%-99.7%), and specificity was 95.3% (95% CI 91.8%-98.8%). For fall detection, pooled sensitivity was 81.9% (95% CI 75.1%-88.1%) and specificity was 62.5% (95% CI 14.4%-100%). Conclusions: Wearable activity trackers show promise in disease detection, with notable accuracy in identifying atrial fibrillation and COVID-19. While these findings are encouraging, further research and improvements are required to enhance their diagnostic precision and applicability.

Relationship Between Heart Rate and Perceived Stress in Intensive Care Unit Residents: Exploratory Analysis Using Fitbit Data (2024)

JMIR formative research

Authors: Wang, Ruijing; Rezaeian, Olya; Asan, Onur; Zhang, Linghan; Liao, Ting

Abstract

Background: Intensive care unit (ICU) residents are exposed to high stress levels due to the intense nature of their work, which can impact their mental health and job performance. Heart rate measured through wearable devices has the potential to provide insights into residents' self-reported stress and aid in developing targeted interventions. Objective: This exploratory study aims to analyze continuous heart rate data and self-reported stress levels and stressors in ICU residents to examine correlations between physiological responses, stress levels, and daily stressors reported. Methods: A secondary data analysis was conducted on heart rate measurements and stress assessments collected from 57 ICU residents over a 3-week period using Fitbit Charge 3 devices. These devices captured continuous physiological data alongside daily surveys that assessed stress levels and identified stressors. The study used Spearman rank correlation, point-biserial correlation analysis, 2-tailed paired t tests, and mixed-effect models to analyze the relationship between heart rate features and stress indicators. Results: The findings reveal complex interactions between stress levels and heart rate patterns. The correlation analysis between stress levels and median heart rate values across different percentile ranges showed that lower percentile heart rates (bottom 5%, 10%, 25%, and 50%) had modest correlations with stress, whereas higher percentiles (top 50%, 25%, 10%, and 5%) did not correlate significantly (all P>.05). The 2-tailed paired t test indicated significant differences in stress levels reported in midday versus end-of-day surveys (P<.001), although these changes in stress levels were not consistently reflected in heart rate patterns. Additionally, we explored and found that stressors related to "other health" issues had the highest positive correlation with stress level changes from midday to end-of-day surveys. However, the weak effect of these stressors on peak heart rate suggests that their impact on physiological measures like heart rate is not yet clear. According to our mixed-effects model, stress levels significantly influenced heart rate variations when hierarchical data were taken into account (P=.03), meaning that as the stress level increased, there was a significant increase in mean heart rate. Conclusions: This study highlights the complexity of using heart rate as an indicator of stress, particularly in high-stress environments like the ICU. Our findings suggest that while heart rate is found to correlate with self-reported stress in the mixed-effect model, its impact is modest, and it should be combined with other physiological and psychological measures to obtain a more accurate and comprehensive assessment of residents' stress levels. Keywords: Fitbit; health care worker; heart rate; intensive care unit; mental health; occupational health; perceived stress; physician; provider; resident; secondary data analysis; self-reported; stress; trainee; wearable.

Relationship between physical activity and biomarkers of pathology and neuroinflammation in preclinical autosomal-dominant Alzheimer's disease (2024)

Alzheimer's \& Dementia (New York, N. Y.)

Authors: Guzmán-Vélez, Edmarie; Rivera-Hernández, Angelys; Fabrega, Sofia; Oliveira, Gabriel; Martínez, Jairo E.; Baena, Ana; Picard, Glen; Lopera, Francisco; Arnold, Steven E.; Taylor, J. Andrew; Quiroz, Yakeel T.

Abstract

Objective: Physical activity (PA) has been linked to reduced Alzheimer's disease (AD) risk. However, less is known about its effects in the AD preclinical stage. We aimed to investigate whether greater PA was associated with lower plasma biomarkers of AD pathology, neural injury, reactive astrocytes, and better cognition in individuals with autosomal-dominant AD due to the presenilin-1 E280A mutation who are virtually guaranteed to develop dementia. Methods: Twenty-eight cognitively unimpaired mutation carriers (ages x̄ = 29.28) wore a FitBit Charge-4 for 14 days. We calculated their average steps to measure locomotion, and Training Impulse (TRIMP) to quantify the intensity and duration of PAs using heart rate. Plasma amyloid beta 42/40 ratio, phosphorylated tau 181, neurofilament light chain, and glial fibrillary acidic protein (GFAP) were measured. Cognition was assessed with the Consortium to Establish a Registry for Alzheimer's Disease word list learning and delayed recall, Trail Making Test Part A, and Wechsler Adult Intelligence Scale-version IV Digit Span Backward. We conducted multiple linear regressions controlling for age, sex, body mass index, and education. Results: There were no associations among steps or TRIMP with plasma biomarkers or cognition. Greater TRIMP was related to higher GFAP levels. Conclusions: PA was not associated with cognition or plasma biomarkers. However, greater intensity and duration of PAs were related to higher GFAP. Participants engaged very little in moderate to vigorous PA. Therefore, light PA may not exert a significant protective effect in preclinical AD. Future work with larger samples and longitudinal data is needed to elucidate further the potential impact of PA on AD progression in the preclinical stages. Highlights: Locomotion (average steps) was not associated with plasma biomarkers or cognition.Greater training load (training impulse) was related to higher glial fibrillary acidic protein levels in mutation carriers.Light physical activity may not suffice to exert a protective effect on Alzheimer's disease. Keywords: early onset Alzheimer's disease; exercise; glial fibrillary acidic protein; neurofilament light chain; phosphorylated tau 181; presenilin‐1 E280A.

Sleep Behavior in Royal Australian Navy Shift Workers by Shift and Exposure to the SleepTank App (2024)

Military Medicine

Authors: Devine, Jaime K.; Cooper, Nadine; Choynowski, Jake; Hursh, Steven R.

Abstract

Introduction: Rotating shiftwork schedules are known to disrupt sleep in a manner that can negatively impact safety. Consumer sleep technologies (CSTs) may be a useful tool for sleep tracking, but the standard feedback provided by CSTs may not be salient to shift-working populations. SleepTank is an app that uses the total sleep time data scored by a CST to compute a percentage that equates hours of sleep to the fuel in a car and warns the user to sleep when the "tank" is low. Royal Australian Navy aircraft maintenance workers operating on a novel rotational shift schedule were given Fitbit Versa 2s to assess sleep timing, duration, and efficiency across a 10-week period. Half of the participants had access to just the Fitbit app while the other half had access to Fitbit and the SleepTank app. The goal of this study was to evaluate differences in sleep behavior between shifts using an off-the-shelf CST and to investigate the potential of the SleepTank app to increase sleep duration during the 10-week rotational shift work schedule. Materials and methods: Royal Australian Navy volunteers agreed to wear a Fitbit Versa 2 with the SleepTank app (SleepTank condition), or without the SleepTank app (Controls), for up to 10 weeks from May to July 2023 during the trial of a novel shift rotation schedule. Participants from across 6 units worked a combination of early (6:00 AM to 2:00 PM), day (7:30 AM to 4:30 PM), late (4:00 PM to 12:00 AM), and night shifts (12:00 AM to 6:00 AM) or stable day shifts (6:00 AM to 4:00 PM). Differences in sleep behavior (time in bed, total sleep time, bedtime, wake time, sleep efficiency [SE]) between conditions and shift types were tested using Analysis of Variance. This study was approved by the Australian Departments of Defence and Veterans' Affairs Human Research Ethics Committee. Results: Thirty-four participants completed the full study (n = 17 Controls; n = 17 SleepTank). There was a significant effect of shift type on 24-hour time in bed (TIB24; F(4,9) = 8.15, P < .001, η2 = 0.15) and total sleep time (TST24; F(4,9) = 8.54, P < .001, η2 = 0.18); both were shorter in early shifts and night shifts compared to other shift types. TIB24 and TST24 were not significantly different between conditions, but there was a trend for greater SE in the SleepTank condition relative to Controls (F(1,9) = 2.99, P = .08, η2 = 0.11). Conclusions: Sleep data collected by Fitbit Versa 2s indicated shorter sleep duration (TIB24, TST24) for Royal Australian Navy workers during early and late shifts relative to stable day shifts. Access to the SleepTank app did not greatly influence measures of sleep duration but may be protective against fatigue by affecting SE. Further research is needed to evaluate the utility of the SleepTank app as a means of improving sleep hygiene in real-world, shift-working environments.

Supervised machine learning to predict smoking lapses from Ecological Momentary Assessments and sensor data: Implications for just-in-time adaptive intervention development (2024)

PLOS digital health

Authors: Perski, Olga; Kale, Dimitra; Leppin, Corinna; Okpako, Tosan; Simons, David; Goldstein, Stephanie P.; Hekler, Eric; Brown, Jamie

Abstract

Specific moments of lapse among smokers attempting to quit often lead to full relapse, which highlights a need for interventions that target lapses before they might occur, such as just-in-time adaptive interventions (JITAIs). To inform the decision points and tailoring variables of a lapse prevention JITAI, we trained and tested supervised machine learning algorithms that use Ecological Momentary Assessments (EMAs) and wearable sensor data of potential lapse triggers and lapse incidence. We aimed to identify a best-performing and feasible algorithm to take forwards in a JITAI. For 10 days, adult smokers attempting to quit were asked to complete 16 hourly EMAs/day assessing cravings, mood, activity, social context, physical context, and lapse incidence, and to wear a Fitbit Charge 4 during waking hours to passively collect data on steps and heart rate. A series of group-level supervised machine learning algorithms (e.g., Random Forest, XGBoost) were trained and tested, without and with the sensor data. Their ability to predict lapses for out-of-sample (i) observations and (ii) individuals were evaluated. Next, a series of individual-level and hybrid (i.e., group- and individual-level) algorithms were trained and tested. Participants (N = 38) responded to 6,124 EMAs (with 6.9% of responses reporting a lapse). Without sensor data, the best-performing group-level algorithm had an area under the receiver operating characteristic curve (AUC) of 0.899 (95% CI = 0.871-0.928). Its ability to classify lapses for out-of-sample individuals ranged from poor to excellent (AUCper person = 0.524-0.994; median AUC = 0.639). 15/38 participants had adequate data for individual-level algorithms to be constructed, with a median AUC of 0.855 (range: 0.451-1.000). Hybrid algorithms could be constructed for 25/38 participants, with a median AUC of 0.692 (range: 0.523 to 0.998). With sensor data, the best-performing group-level algorithm had an AUC of 0.952 (95% CI = 0.933-0.970). Its ability to classify lapses for out-of-sample individuals ranged from poor to excellent (AUCper person = 0.494-0.979; median AUC = 0.745). 11/30 participants had adequate data for individual-level algorithms to be constructed, with a median AUC of 0.983 (range: 0.549-1.000). Hybrid algorithms could be constructed for 20/30 participants, with a median AUC of 0.772 (range: 0.444 to 0.968). In conclusion, high-performing group-level lapse prediction algorithms without and with sensor data had variable performance when applied to out-of-sample individuals. Individual-level and hybrid algorithms could be constructed for a limited number of individuals but had improved performance, particularly when incorporating sensor data for participants with sufficient wear time. Feasibility constraints and the need to balance multiple success criteria in the JITAI development and implementation process are discussed.

Text Messages to Promote Physical Activity in Patients With Cardiovascular Disease: A Micro-Randomized Trial of a Just-In-Time Adaptive Intervention (2024)

Circulation. Cardiovascular Quality and Outcomes

Authors: Golbus, Jessica R.; Shi, Jieru; Gupta, Kashvi; Stevens, Rachel; Jeganathan, V. Swetha E.; Luff, Evan; Boyden, Thomas; Mukherjee, Bhramar; Kohnstamm, Sarah; Taralunga, Vlad; Kheterpal, Vik; Kheterpal, Sachin; Resnicow, Kenneth; Murphy, Susan; Dempsey, Walter; Klasnja, Predrag; Nallamothu, Brahmajee K.

Abstract

BACKGROUND: Text messages may enhance physical activity levels in patients with cardiovascular disease, including those enrolled in cardiac rehabilitation. However, the independent and long-term effects of text messages remain uncertain. METHODS: The VALENTINE study (Virtual Application-supported Environment to Increase Exercise) was a micro-randomized trial that delivered text messages through a smartwatch (Apple Watch or Fitbit Versa) to participants initiating cardiac rehabilitation. Participants were randomized 4× per day over 6-months to receive no text message or a message encouraging low-level physical activity. Text messages were tailored on contextual factors (eg, weather). Our primary outcome was step count 60 minutes following a text message, and we used a centered and weighted least squares mean method to estimate causal effects. Given potential measurement differences between devices determined a priori, data were assessed separately for Apple Watch and Fitbit Versa users over 3 time periods corresponding to the initiation (0-30 days), maintenance (31-120 days), and completion (121-182 days) of cardiac rehabilitation. RESULTS: One hundred eight participants were included with 70 552 randomizations over 6 months; mean age was 59.5 (SD, 10.7) years with 36 (32.4\%) female and 68 (63.0\%) Apple Watch participants. For Apple Watch participants, text messages led to a trend in increased step count by 10\% in the 60-minutes following a message during days 1 to 30 (95\% CI, -1\% to +20\%), with no effect from days 31 to 120 (+1\% [95\% CI, -4\% to +5\%]), and a significant 6\% increase during days 121 to 182 (95\% CI, +0\% to +11\%). For Fitbit users, text messages significantly increased step count by 17\% (95\% CI, +7\% to +28\%) in the 60-minutes following a message in the first 30 days of the study with no effect subsequently. CONCLUSIONS: In patients undergoing cardiac rehabilitation, contextually tailored text messages may increase physical activity, but this effect varies over time and by device. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04587882.

The Comprehensive Resilience-building psychosocial Intervention (CREST) for people with dementia in the community: a feasibility and acceptability study (2024)

Pilot and Feasibility Studies

Authors: Casey, Dympna; Doyle, Priscilla; Gallagher, Niamh; O'Sullivan, Grace; Smyth, Siobhán; Devane, Declan; Murphy, Kathy; Clarke, Charlotte; Woods, Bob; Dröes, Rose-Marie; Windle, Gill; Murphy, Andrew W.; Foley, Tony; Timmons, Fergus; Gillespie, Paddy; Hobbins, Anna; Newell, John; Abedin, Jaynal; Domegan, Christine; Irving, Kate; Whelan, Barbara

Abstract

BACKGROUND: A dementia diagnosis can lead to a decline in cognitive, social, and physical health, but people with dementia can live meaningful lives and participate actively in society with psychosocial support. This single-arm, non-randomised feasibility study explored the feasibility and acceptability of a Comprehensive REsilience-building psychoSocial intervenTion (CREST) for people with dementia, their caregivers, General Practitioners (GPs), and the public. METHODS: Nine people with dementia and their primary caregivers living in the community (n = 9 dyads) completed the CREST intervention which had three components (cognitive stimulation therapy [CST], physical exercise, and dementia education). Quantitative secondary outcomes were assessed at baseline and following the 15-week intervention; qualitative interviews were conducted during and post-intervention. All study components were assessed against pre-defined criteria, to determine the feasibility of conducting a future definitive trial. RESULTS: Recruitment of people with dementia and their caregiver was a significant challenge and led to considerable delays to the onset and conduct of the intervention. Only 13\% of eligible GP practices agreed to assist in recruitment and achieved a 6\% enrolment rate; a community-based recruitment strategy proved more effective, yielding a 29\% enrolment rate. However, once recruited, participants maintained high attendance and adherence to the content of each component with average adherence rates of 98\% for CST, exercise sessions and caregiver education. Adherence to secondary exercise measures was lower, with home exercise diary completion at 37\% and Fitbit wear adherence at 80\% during the day and 67\% at night. The people with dementia felt their concentration and fitness had improved over the 15-week intervention and particularly enjoyed the social aspects (e.g. group classes, exercising with partners from the community). Caregivers felt they had better knowledge and understanding following their education component and reported that the social aspects (interacting and sharing experiences with each other) were important. Overall, participants reported that the three components of the intervention were feasible and acceptable. In addition, the quantitative measures and health economic tools employed were feasible. However, the secondary elements of the exercise component (recording home exercise diaries and Fitbit use) were not considered feasible. Overall, pre-defined criteria for progression to a definitive intervention were fulfilled in terms of acceptability, retention and fidelity but not recruitment. CONCLUSION: While overall, the CREST intervention was feasible and acceptable to participants, significant difficulties with recruitment of people with dementia and their caregiver through GP practices impacted the viability of delivering the intervention. Recruitment through community-based groups proved a more feasible option and further work is needed to overcome barriers to recruiting this cohort before a larger-scale trial can be conducted. TRIAL REGISTRATION: ISRCTN25294519.

The effects of COVID-19 lockdown and reopening on rest-activity rhythms in Singaporean working adults: A longitudinal age group comparison study (2024)

Sleep Health

Authors: Qin, Shuo; Ong, Ju Lynn; Chia, Janelle; Low, Alicia; Lee, Charmaine; Koek, Daphne; Cheong, Karen; Chee, Michael Wei Liang

Abstract

Study objectives: COVID-19 mobility restrictions disrupted daily rhythms worldwide, but how this rhythm disruption differs across age groups is unclear. We examined the course of age-related differences in trajectories of rest-activity rhythm during the COVID-19 pandemic lockdown and reopening in Singapore. We also evaluated the association of these patterns with mental well-being. Methods: 24-hour step count data (Fitbit) were obtained from 617 younger (age range: 21-40) and 602 older adults (age range: 55-70) from January 2020 (baseline) through lockdown (April 2020) and reopening periods until August 2021. Nonparametric rest-activity rhythm metrics: interdaily stability, intradaily variability and most active 10-hour period (M10) were computed. Longitudinal changes in rest-activity rhythm, age-related differences in changes, and the associations between mental well-being and these changes were assessed using nonlinear latent-growth models. Results: In younger adults, mobility restrictions during lockdown caused significant decline in interdaily stability and M10, alongside significant increase in intradaily variability. However, in older adults, changes were confined to increased intradaily variability and decreased M10. Older adults also showed less change in intradaily variability and M10 compared to younger adults. Gradual recovery of rest-activity rhythm metrics during reopening was observed, with interdaily stability and M10 remaining lower after 15months post-lockdown. In younger but not older adults, a larger decline in interdaily stability was associated with poorer mental well-being 15months post-lockdown. Conclusion: Younger adults appear more vulnerable than older adults to mobility restrictions as reflected in their rest-activity rhythm metrics. A significant disruption of daily routine may have long-lasting effects on younger adults' mental well-being. Statement of significance: Although stringent mobility restrictions imposed to curb the spread of COVID-19 were imposed primarily to protect older adults, we found that younger adults were more vulnerable to rhythm disruption arising from mobility restrictions. Disrupted rhythm stability was associated with poorer mental well-being 15months after the lockdown ended in younger but not older adults. These asymmetric long-term effects on mental health on younger relative to older adults should be kept in mind when planning for large-scale catastrophes linked to mobility restrictions.

The relationship between wearable-derived sleep features and relapse in Major Depressive Disorder (2024)

Journal of Affective Disorders

Authors: Matcham, F.; Carr, E.; Meyer, N.; White, K. M.; Oetzmann, C.; Leightley, D.; Lamers, F.; Siddi, S.; Cummins, N.; Annas, P.; de Girolamo, G.; Haro, J. M.; Lavelle, G.; Li, Q.; Lombardini, F.; Mohr, D. C.; Narayan, V. A.; Penninx, B. W. H. J.; Coromina, M.; Riquelme Alacid, G.; Simblett, S. K.; Nica, R.; Wykes, T.; Brasen, J. C.; Myin-Germeys, I.; Dobson, R. J. B.; Folarin, A. A.; Ranjan, Y.; Rashid, Z.; Dineley, J.; Vairavan, S.; Hotopf, M.; RADAR-CNS consortium

Abstract

BACKGROUND: Changes in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD were used to describe the longitudinal effects of sleep duration, quality, and regularity on subsequent depression relapse and severity. METHODS: Data were collected as part of a longitudinal observational mobile Health (mHealth) cohort study in people with recurrent MDD. Participants wore a Fitbit device and completed regular outcome assessments via email for a median follow-up of 541 days. We used multivariable regression models to test the effects of sleep features on depression outcomes. We considered respondents with at least one assessment of relapse (n = 218) or at least one assessment of depression severity (n = 393). RESULTS: Increased intra-individual variability in total sleep time, greater sleep fragmentation, lower sleep efficiency, and more variable sleep midpoints were associated with worse depression outcomes. Adjusted Population Attributable Fractions suggested that an intervention to increase sleep consistency in adults with MDD could reduce the population risk for depression relapse by up to 22 \%. LIMITATIONS: Limitations include a potentially underpowered primary outcome due to the smaller number of relapses identified than expected. CONCLUSION: Our study demonstrates a role for consumer-grade activity trackers in estimating relapse risk and depression severity in people with recurrent MDD. Variability in sleep duration and midpoint may be useful targets for stratified interventions.

Using formative process evaluation to improve program implementation and accessibility of competitive group-based physical activity in the TEAM-PA trial (2024)

The International Journal of Behavioral Nutrition and Physical Activity

Authors: Sweeney, Allison M.; Wilson, Dawn K.; Zarrett, Nicole; Simmons, Timothy; Mansfield, Makayla; Decker, Lindsay

Abstract

BACKGROUND: This study demonstrates how formative process evaluation was used to assess implementation and improve dose and fidelity in the Together Everyone Achieves More Physical Activity (TEAM-PA) randomized controlled trial. TEAM-PA uses a randomized group cohort design to evaluate the efficacy of a group-based intervention for increasing physical activity among African American women. METHODS: Intervention groups met for 10 weeks and were co-led by female African American facilitators, with intervention sessions consisting of group feedback, a health curriculum, group-based physical activity games, and group-based goal-setting. Drawing from a multi-theoretical framework, the intervention targeted social affiliation using collaborative and competitive group strategies, including essential elements focused on group-based behavioral skills, peer-to-peer positive communication, collectivism, optimal challenge, social facilitation, and peer to peer challenges. Formative process evaluation was used to monitor reach, dose, and fidelity, and implement feedback and solutions. RESULTS: Across two cohorts, four groups (n = 54) were randomized to the TEAM-PA intervention. On average 84.8\% of participants attended each week, which exceeded the a priori criteria. Results from the systematic observations indicated that on average 93\% of the dose items were completed in each session and adequate levels of fidelity were achieved at both the facilitator and group-levels. Participants were compliant with wearing the FitBits (6.73 ± 0.42 days/week) and most participants successfully contributed to meeting the group-based goals. The use of open-ended items also revealed the need for additional modifications to the group-based PA games, including allowing for individuals to take breaks, incorporating a broader range of exercises, minimizing activities that required bending/reaching down without assistance, and providing facilitators with additional training for implementing the games. Initial evidence suggests that these changes were successful in increasing participants' comprehension of the games from Cohort 1 (M = 1.83, SD = 0.71) to Cohort 2 (M = 3.33, SD = 0.69). CONCLUSION: Findings from this study demonstrated high levels of reach, dose, and fidelity, while also highlighting strategies for implementing competitive group-based PA games that are accessible across physical fitness levels. Formative process evaluation, including open-ended items and collaborative brainstorming, holds tremendous potential for improving future interventions. TRIAL REGISTRATION: This study was registered on Clinicaltrials.gov (\# NCT05519696) on August 22, 2022 prior to the enrollment of the first participant on September 12, 2022 ( https://clinicaltrials.gov/study/NCT05519696?term=NCT05519696\&rank=1 ).

Validity of a Consumer-Based Wearable to Measure Clinical Parameters in Patients With Chronic Obstructive Pulmonary Disease and Healthy Controls: Observational Study (2024)

JMIR mHealth and uHealth

Authors: Hermans, Fien; Arents, Eva; Blondeel, Astrid; Janssens, Wim; Cardinaels, Nina; Calders, Patrick; Troosters, Thierry; Derom, Eric; Demeyer, Heleen

Abstract

BACKGROUND: Consumer-based wearables are becoming more popular and provide opportunities to track individual's clinical parameters remotely. However, literature about their criterion and known-groups validity is scarce. OBJECTIVE: This study aimed to assess the validity of the Fitbit Charge 4, a wrist-worn consumer-based wearable, to measure clinical parameters (ie, daily step count, resting heart rate [RHR], heart rate variability [HRV], respiratory rate [RR], and oxygen saturation) in patients with chronic obstructive pulmonary disease (COPD) and healthy controls in free-living conditions in Belgium by comparing it with medical-grade devices. METHODS: Participants wore the Fitbit Charge 4 along with three medical-grade devices: (1) Dynaport MoveMonitor for 7 days, retrieving daily step count; (2) Polar H10 for 5 days, retrieving RHR, HRV, and RR; and (3) Nonin WristOX2 3150 for 4 nights, retrieving oxygen saturation. Criterion validity was assessed by investigating the agreement between day-by-day measures of the Fitbit Charge 4 and the corresponding reference devices. Known-groups validity was assessed by comparing patients with COPD and healthy controls. RESULTS: Data of 30 patients with COPD and 25 age- and gender-matched healthy controls resulted in good agreement between the Fitbit Charge 4 and the corresponding reference device for measuring daily step count (intraclass correlation coefficient [ICC2,1]=0.79 and ICC2,1=0.85, respectively), RHR (ICC2,1=0.80 and ICC2,1=0.79, respectively), and RR (ICC2,1=0.84 and ICC2,1=0.77, respectively). The agreement for HRV was moderate (healthy controls: ICC2,1=0.69) to strong (COPD: ICC2,1=0.87). The agreement in measuring oxygen saturation in patients with COPD was poor (ICC2,1=0.32). The Fitbit device overestimated the daily step count and underestimated HRV in both groups. While RHR and RR were overestimated in healthy controls, no difference was observed in patients with COPD. Oxygen saturation was overestimated in patients with COPD. The Fitbit Charge 4 detected significant differences in daily step count, RHR, and RR between patients with COPD and healthy controls, similar to those identified by the reference devices, supporting known-groups validity. CONCLUSIONS: Although the Fitbit Charge 4 shows mainly moderate to good agreement, measures of clinical parameters deviated from the reference devices, indicating that monitoring patients remotely and interpreting parameters requires caution. Differences in clinical parameters between patients with COPD and healthy controls that were measured by the reference devices were all detected by the Fitbit Charge 4.

Variations in objectively measured sleep parameters in patients with different premature ejaculation syndromes (2024)

The Journal of Sexual Medicine

Authors: Wu, Xu; Zhang, Yuyang; Jiang, Hui; Zhang, Xiansheng

Abstract

BACKGROUND: Poor sleep quality is now a cause of sexual dysfunction. AIM: To investigate variations in sleep quality among patients with different types of premature ejaculation (PE) and a control group. METHODS: Patients with PE were categorized into groups according to 4 types: lifelong (LPE), acquired (APE), variable (VPE), and subjective (SPE). Basic demographic information about the participants was first collected, and then clinical data were obtained. OUTCOMES: Outcomes included the 5-item International Index of Erectile Function, Premature Ejaculation Diagnostic Tool, 7-item Generalized Anxiety Disorder, 9-item Patient Health Questionnaire, Pittsburgh Sleep Quality Index, self-estimated intravaginal ejaculation latency time (minutes), and sleep monitoring parameters obtained from a wearable device (Fitbit Charge 2). RESULTS: A total of 215 participants were enrolled in the study, of which 136 patients with PE were distributed as follows: LPE (31.62\%), APE (42.65\%), VPE (10.29\%), and SPE (15.44\%). Subjective scales showed that patients with APE were accompanied by a higher prevalence of erectile dysfunction, anxiety, and depression, as well as poorer sleep quality (assessed by the Pittsburgh Sleep Quality Index). The results of objective sleep parameters revealed that average durations of sleep onset latency (minutes) and wake after sleep onset (minutes) in patients with APE (mean ± SD; 20.03 ± 9.14, 55 ± 23.15) were significantly higher than those with LPE (15.07 ± 5.19, 45.09 ± 20.14), VPE (13.64 ± 3.73, 38.14 ± 11.53), and SPE (14.81 ± 4.33, 42.86 ± 13.14) and the control group (12.48 ± 3.45, 37.14 ± 15.01; P {\textless} .05). The average duration of rapid eye movement (REM; minutes) in patients with APE (71.34 ± 23.18) was significantly lower than that in patients with LPE (79.67 ± 21.53), VPE (85.93 ± 6.93), and SPE (80.86 ± 13.04) and the control group (86.56 ± 11.93; P {\textless} .05). Similarly, when compared with the control group, patients with LPE had significantly longer durations of sleep onset latency and wake after sleep onset and a significantly shorter duration of REM sleep. CLINICAL IMPLICATIONS: Our study suggests that clinicians should pay attention not only to male physical assessment but also to mental health and sleep quality. STRENGTHS AND LIMITATIONS: This study suggests that changes in sleep structure occur in patients with PE, which may provide some direction for future research. However, the cross-sectional study design does not allow us to conclude that sleep is a risk factor for PE. CONCLUSION: After controlling for traditional parameters such as age, erectile dysfunction, anxiety, and depression, sleep parameters are independently associated with PE. Patients with APE and LPE show significant alterations in sleep parameters, with patients with APE having notably poorer sleep quality, whereas patients with VPE and SPE have sleep parameters similar to controls.

A culturally tailored personaliseD nutrition intErvention in South ASIan women at risk of Gestational Diabetes Mellitus (DESI-GDM): a randomised controlled trial protocol (2023)

BMJ open

Authors: Stennett, Rosain N.; Adamo, Kristi B.; Anand, Sonia S.; Bajaj, Harpreet S.; Bangdiwala, Shrikant I.; Desai, Dipika; Gerstein, Hertzel C.; Kandasamy, Sujane; Khan, Farah; Lear, Scott A.; McDonald, Sarah D.; Pocsai, Tayler; Ritvo, Paul; Rogge, Andrea; Schulze, Karleen M.; Sherifali, Diana; Stearns, Jennifer C.; Wahi, Gita; Williams, Natalie C.; Zulyniak, Michael A.; de Souza, Russell J.

Abstract

INTRODUCTION: South Asians are more likely to develop gestational diabetes mellitus (GDM) than white Europeans. Diet and lifestyle modifications may prevent GDM and reduce undesirable outcomes in both the mother and offspring. Our study seeks to evaluate the effectiveness and participant acceptability of a culturally tailored, personalised nutrition intervention on the glucose area under the curve (AUC) after a 2-hour 75 g oral glucose tolerance test (OGTT) in pregnant women of South Asian ancestry with GDM risk factors. METHODS AND ANALYSIS: A total of 190 South Asian pregnant women with at least 2 of the following GDM risk factors-prepregnancy body mass index{\textgreater}23, age{\textgreater}29, poor-quality diet, family history of type 2 diabetes in a first-degree relative or GDM in a previous pregnancy will be enrolled during gestational weeks 12-18, and randomly assigned in a 1:1 ratio to: (1) usual care, plus weekly text messages to encourage walking and paper handouts or (2) a personalised nutrition plan developed and delivered by a culturally congruent dietitian and health coach; and FitBit to track steps. The intervention lasts 6-16 weeks, depending on week of recruitment. The primary outcome is the glucose AUC from a three-sample 75 g OGTT 24-28 weeks' gestation. The secondary outcome is GDM diagnosis, based on Born-in-Bradford criteria (fasting glucose{\textgreater}5.2 mmol/L or 2 hours post load{\textgreater}7.2 mmol/L). ETHICS AND DISSEMINATION: The study has been approved by the Hamilton Integrated Research Ethics Board (HiREB \#10942). Findings will be disseminated among academics and policy-makers through scientific publications along with community-orientated strategies. TRIAL REGISTRATION NUMBER: NCT03607799.

A Digital Coach (E-Supporter 1.0) to Support Physical Activity and a Healthy Diet in People With Type 2 Diabetes: Acceptability and Limited Efficacy Testing (2023)

JMIR formative research

Authors: Hietbrink, Eclaire A. G.; Oude Nijeweme-d'Hollosy, Wendy; Middelweerd, Anouk; Konijnendijk, Annemieke A. J.; Schrijver, Laura K.; Ten Voorde, Anouk S.; Fokkema, Elise M. S.; Laverman, Gozewijn D.; Vollenbroek-Hutten, Miriam M. R.

Abstract

Background: A healthy lifestyle, including regular physical activity and a healthy diet, is increasingly part of type 2 diabetes (T2D) management. As many people with T2D have difficulty living and maintaining a healthy lifestyle, there is a need for effective interventions. eHealth interventions that incorporate behavior change theories and tailoring are considered effective tools for supporting a healthy lifestyle. The E-Supporter 1.0 digital coach contains eHealth content for app-based eHealth interventions and offers tailored coaching regarding physical activity and a healthy diet for people with T2D. Objective: This study aimed to assess the acceptability of E-Supporter 1.0 and explore its limited efficacy on physical activity, dietary behavior, the phase of behavior change, and self-efficacy levels. Methods: Over a span of 9 weeks, 20 individuals with T2D received daily motivational messages and weekly feedback derived from behavioral change theories and determinants through E-Supporter 1.0. The acceptability of the intervention was assessed using telephone-conducted, semistructured interviews. The interview transcripts were coded using inductive thematic analysis. The limited efficacy of E-Supporter 1.0 was explored using the Fitbit Charge 2 to monitor step count to assess physical activity and questionnaires to assess dietary behavior (using the Dutch Healthy Diet index), phase of behavior change (using the single-question Self-Assessment Scale Stages of Change), and self-efficacy levels (using the Exercise Self-Efficacy Scale). Results: In total, 5 main themes emerged from the interviews: perceptions regarding remote coaching, perceptions regarding the content, intervention intensity and duration, perceived effectiveness, and overall appreciation. The participants were predominantly positive about E-Supporter 1.0. Overall, they experienced E-Supporter 1.0 as a useful and easy-to-use intervention to support a better lifestyle. Participants expressed a preference for combining E-Supporter with face-to-face guidance from a health care professional. Many participants found the intensity and duration of the intervention to be acceptable, despite the coaching period appearing relatively short to facilitate long-term behavior maintenance. As expected, the degree of tailoring concerning the individual and external factors that influence a healthy lifestyle was perceived as limited. The limited efficacy testing showed a significant improvement in the daily step count (z=-2.040; P=.04) and self-efficacy levels (z=-1.997; P=.046) between baseline and postintervention. Diet was improved through better adherence to Dutch dietary guidelines. No significant improvement was found in the phase of behavior change (P=.17), as most participants were already in the maintenance phase at baseline. Conclusions: On the basis of this explorative feasibility study, we expect E-Supporter 1.0 to be an acceptable and potentially useful intervention to promote physical activity and a healthy diet in people with T2D. Additional work needs to be done to further tailor the E-Supporter content and evaluate its effects more extensively on lifestyle behaviors. Keywords: acceptability; eHealth; formative evaluation; lifestyle change; limited efficacy; mobile phone; nutrition; physical activity; type 2 diabetes.

A multi-site trial of an electronic health integrated physical activity promotion intervention in breast and endometrial cancers survivors: MyActivity study protocol (2023)

Contemporary Clinical Trials

Authors: Cadmus-Bertram, Lisa; Solk, Payton; Agnew, Megan; Starikovsky, Julia; Schmidt, Christian; Morelli, Whitney A.; Hodgson, Vanessa; Freeman, Hannah; Muller, Laura; Mishory, Abby; Naxi, Sondra; Carden, Lillian; Tevaarwerk, Amye J.; Wolter, Melanie; Barber, Emma; Spencer, Ryan; Sesto, Mary E.; Gradishar, William; Gangnon, Ronald; Spring, Bonnie; Nahum-Shani, Inbal; Phillips, Siobhan M.

Abstract

Despite the known benefits of moderate-to-vigorous physical activity (MVPA) for breast and endometrial cancer survivors, most are insufficiently active, interventions response is heterogeneous, and MVPA programming integration into cancer care is limited. A stepped care approach, in which the least resource-intensive intervention is delivered first and additional components are added based on individual response, is one strategy to enhance uptake of physical activity programming. However, the most effective intervention augmentation strategies are unknown. In this singly randomized trial of post-treatment, inactive breast and endometrial cancer survivors (n = 323), participants receive a minimal intervention including a Fitbit linked with their clinic's patient portal and, in turn, the electronic health record (EHR) with weekly feedback delivered via the portal. MVPA progress summaries are sent to participants' oncology team via the EHR. MVPA adherence is evaluated at 4, 8, 12, 16 and 20 weeks; non-responders (those meeting ≤80% of the MVPA goal over previous 4 weeks) at each timepoint are randomized once for the remainder of the 24-week intervention to one of two "step-up" conditions: (1) online gym or (2) coaching calls, while responders continue with the minimal Fitbit+EHR intervention. The primary outcome is ActiGraph-measured MVPA at 24 and 48 weeks. Secondary outcomes include symptom burden and functional performance at 24 and 48 weeks. This trial will inform development of an effective, scalable, and tailored intervention for survivors by identifying non-responders and providing them with the intervention augmentations necessary to increase MVPA and improve health outcomes. Clinical Trials Registration # NCT04262180.

A Series of Remote Melatonin Supplement Interventions for Poor Sleep: Protocol for a Feasibility Pilot Study for a Series of Personalized (N-of-1) Trials (2023)

JMIR Research Protocols

Authors: Butler, Mark; D’Angelo, Stefani; Perrin, Alexandra; Rodillas, Jordyn; Miller, Danielle; Arader, Lindsay; Chandereng, Thevaa; Cheung, Ying Kuen; Shechter, Ari; Davidson, Karina W.

Abstract

Background: Poor sleep, defined as short-duration or poor-quality sleep, is a frequently reported condition with many deleterious effects including poorer cognitive functioning, increased accidents, and poorer health. Melatonin has been shown to be an efficacious treatment to manage symptoms of poor sleep. However, the treatment effects of melatonin on sleep can vary greatly between participants. Personalized, or N-of-1, trial designs represent a method for identifying the best treatment for individual participants. Although using N-of-1 trials of melatonin to treat poor sleep is possible, the feasibility, acceptability, and effectiveness of N-of-1 trials using melatonin are unknown. Using the National Institutes of Health Stage Model for Behavioral Intervention Development, a stage IB (intervention refinement, modification, and adaptation and pilot testing) design appeared to be needed to address these feasibility questions. Objective: This trial series evaluates the feasibility, acceptability, and effectiveness of a series of personalized interventions for remote delivery of melatonin dose (3 and 0.5 mg) versus placebo supplements for self-reported poor sleep among 60 participants. The goal of this study is to provide valuable information about implementing remote N-of-1 randomized controlled trials to improve poor sleep. Methods: Participants will complete a 2-week baseline followed by six 2-week alternating intervention periods of 3 mg of melatonin, 0.5 mg of melatonin, and placebo. Participants will be randomly assigned to 2 intervention orders. The feasibility and acceptability of the personalized trial approach will be determined with participants’ ratings of usability and satisfaction with the remote, personalized intervention delivery system. The effectiveness of the intervention will be measured using participants’ self-reported sleep quality and duration and Fitbit tracker–measured sleep duration and efficiency. Additional measures will include ecological momentary assessment measures of fatigue, stress, pain, mood, concentration, and confidence as well as measures of participant adherence to the intervention, use of the Fitbit tracker, and survey data collection. Results: As of the submission of this protocol, recruitment for this National Institutes of Health stage IB personalized trial series is approximately 78.3\% complete (47/60). We expect recruitment and data collection to be finalized by June 2023. Conclusions: Evaluating the feasibility, acceptability, and effectiveness of a series of personalized interventions of melatonin will address the longer term aim of this program of research—is integrating N-of-1 trials useful patient care? The personalized trial series results will be published in a peer-reviewed journal and will follow the CONSORT (Consolidated Standards of Reporting Trials) extension for N-of-1 trials (CENT 2015) reporting guidelines. This trial series was approved by the Northwell Health institutional review board. Trial Registration: ClinicalTrials.gov NCT05349188; https://www.clinicaltrials.gov/study/NCT05349188

URL

Accuracy in detecting atrial fibrillation in single-lead ECGs: an online survey comparing the influence of clinical expertise and smart devices (2023)

Swiss Medical Weekly

Authors: Weidlich, Simon; Mannhart, Diego; Serban, Teodor; Krisai, Philipp; Knecht, Sven; Du Fay de Lavallaz, Jeanne; Müller, Tatjana; Schaer, Beat; Osswald, Stefan; Kühne, Michael; Sticherling, Christian; Badertscher, Patrick

Abstract

BACKGROUND: Manual interpretation of single-lead ECGs (SL-ECGs) is often required to confirm a diagnosis of atrial fibrillation. However accuracy in detecting atrial fibrillation via SL-ECGs may vary according to clinical expertise and choice of smart device. AIMS: To compare the accuracy of cardiologists, internal medicine residents and medical students in detecting atrial fibrillation via SL-ECGs from five different smart devices (Apple Watch, Fitbit Sense, KardiaMobile, Samsung Galaxy Watch, Withings ScanWatch). Participants were also asked to assess the quality and readability of SL-ECGs. METHODS: In this prospective study (BaselWearableStudy, NCT04809922), electronic invitations to participate in an online survey were sent to physicians at major Swiss hospitals and to medical students at Swiss universities. Participants were asked to classify up to 50 SL-ECGs (from ten patients and five devices) into three categories: sinus rhythm, atrial fibrillation or inconclusive. This classification was compared to the diagnosis via a near-simultaneous 12-lead ECG recording interpreted by two independent cardiologists. In addition, participants were asked their preference of each manufacturer's SL-ECG. RESULTS: Overall, 450 participants interpreted 10,865 SL-ECGs. Sensitivity and specificity for the detection of atrial fibrillation via SL-ECG were 72\% and 92\% for cardiologists, 68\% and 86\% for internal medicine residents, 54\% and 65\% for medical students in year 4-6 and 44\% and 58\% for medical students in year 1-3; p {\textless}0.001. Participants who stated prior experience in interpreting SL-ECGs demonstrated a sensitivity and specificity of 63\% and 81\% compared to a sensitivity and specificity of 54\% and 67\% for participants with no prior experience in interpreting SL-ECGs (p {\textless}0.001). Of all participants, 107 interpreted all 50 SL-ECGs. Diagnostic accuracy for the first five interpreted SL-ECGs was 60\% (IQR 40-80\%) and diagnostic accuracy for the last five interpreted SL-ECGs was 80\% (IQR 60-90\%); p {\textless}0.001. No significant difference in the accuracy of atrial fibrillation detection was seen between the five smart devices; p = 0.33. SL-ECGs from the Apple Watch were considered as having the best quality and readability by 203 (45\%) and 226 (50\%) participants, respectively. CONCLUSION: SL-ECGs can be challenging to interpret. Accuracy in correctly identifying atrial fibrillation depends on clinical expertise, while the choice of smart device seems to have no impact.

Accuracy of 11 Wearable, Nearable, and Airable Consumer Sleep Trackers: Prospective Multicenter Validation Study (2023)

JMIR mHealth and uHealth

Authors: Lee, Taeyoung; Cho, Younghoon; Cha, Kwang Su; Jung, Jinhwan; Cho, Jungim; Kim, Hyunggug; Kim, Daewoo; Hong, Joonki; Lee, Dongheon; Keum, Moonsik; Kushida, Clete A.; Yoon, In-Young; Kim, Jeong-Whun

Abstract

Background: Consumer sleep trackers (CSTs) have gained significant popularity because they enable individuals to conveniently monitor and analyze their sleep. However, limited studies have comprehensively validated the performance of widely used CSTs. Our study therefore investigated popular CSTs based on various biosignals and algorithms by assessing the agreement with polysomnography. Objective: This study aimed to validate the accuracy of various types of CSTs through a comparison with in-lab polysomnography. Additionally, by including widely used CSTs and conducting a multicenter study with a large sample size, this study seeks to provide comprehensive insights into the performance and applicability of these CSTs for sleep monitoring in a hospital environment. Methods: The study analyzed 11 commercially available CSTs, including 5 wearables (Google Pixel Watch, Galaxy Watch 5, Fitbit Sense 2, Apple Watch 8, and Oura Ring 3), 3 nearables (Withings Sleep Tracking Mat, Google Nest Hub 2, and Amazon Halo Rise), and 3 airables (SleepRoutine, SleepScore, and Pillow). The 11 CSTs were divided into 2 groups, ensuring maximum inclusion while avoiding interference between the CSTs within each group. Each group (comprising 8 CSTs) was also compared via polysomnography. Results: The study enrolled 75 participants from a tertiary hospital and a primary sleep-specialized clinic in Korea. Across the 2 centers, we collected a total of 3890 hours of sleep sessions based on 11 CSTs, along with 543 hours of polysomnography recordings. Each CST sleep recording covered an average of 353 hours. We analyzed a total of 349,114 epochs from the 11 CSTs compared with polysomnography, where epoch-by-epoch agreement in sleep stage classification showed substantial performance variation. More specifically, the highest macro F1 score was 0.69, while the lowest macro F1 score was 0.26. Various sleep trackers exhibited diverse performances across sleep stages, with SleepRoutine excelling in the wake and rapid eye movement stages, and wearables like Google Pixel Watch and Fitbit Sense 2 showing superiority in the deep stage. There was a distinct trend in sleep measure estimation according to the type of device. Wearables showed high proportional bias in sleep efficiency, while nearables exhibited high proportional bias in sleep latency. Subgroup analyses of sleep trackers revealed variations in macro F1 scores based on factors, such as BMI, sleep efficiency, and apnea-hypopnea index, while the differences between male and female subgroups were minimal. Conclusions: Our study showed that among the 11 CSTs examined, specific CSTs showed substantial agreement with polysomnography, indicating their potential application in sleep monitoring, while other CSTs were partially consistent with polysomnography. This study offers insights into the strengths of CSTs within the 3 different classes for individuals interested in wellness who wish to understand and proactively manage their own sleep. Keywords: Fitbit Sense 2, Amazon Halo Rise, SleepRoutine; airables; artificial intelligence; comparative study; consumer sleep trackers; deep learning; multicenter study; nearables; polysomnography; sleep monitoring; sleep stage; wearables.

Accuracy of a Standalone Atrial Fibrillation Detection Algorithm Added to a Popular Wristband and Smartwatch: Prospective Diagnostic Accuracy Study (2023)

Journal of Medical Internet Research

Authors: Selder, Jasper L.; Te Kolste, Henryk Jan; Twisk, Jos; Schijven, Marlies; Gielen, Willem; Allaart, Cornelis P.

Abstract

BACKGROUND: Silent paroxysmal atrial fibrillation (AF) may be difficult to diagnose, and AF burden is hard to establish. In contrast to conventional diagnostic devices, photoplethysmography (PPG)-driven smartwatches or wristbands allow for long-term continuous heart rhythm assessment. However, most smartwatches lack an integrated PPG-AF algorithm. Adding a standalone PPG-AF algorithm to these wrist devices might open new possibilities for AF screening and burden assessment. OBJECTIVE: The aim of this study was to assess the accuracy of a well-known standalone PPG-AF detection algorithm added to a popular wristband and smartwatch, with regard to discriminating AF and sinus rhythm, in a group of patients with AF before and after cardioversion (CV). METHODS: Consecutive consenting patients with AF admitted for CV in a large academic hospital in Amsterdam, the Netherlands, were asked to wear a Biostrap wristband or Fitbit Ionic smartwatch with Fibricheck algorithm add-on surrounding the procedure. A set of 1-min PPG measurements and 12-lead reference electrocardiograms was obtained before and after CV. Rhythm assessment by the PPG device-software combination was compared with the 12-lead electrocardiogram. RESULTS: A total of 78 patients were included in the Biostrap-Fibricheck cohort (156 measurement sets) and 73 patients in the Fitbit-Fibricheck cohort (143 measurement sets). Of the measurement sets, 19/156 (12\%) and 7/143 (5\%), respectively, were not classifiable by the PPG algorithm due to bad quality. The diagnostic performance in terms of sensitivity, specificity, positive predictive value, negative predictive value, and accuracy was 98\%, 96\%, 96\%, 99\%, 97\%, and 97\%, 100\%, 100\%, 97\%, and 99\%, respectively, at an AF prevalence of {\textasciitilde}50\%. CONCLUSIONS: This study demonstrates that the addition of a well-known standalone PPG-AF detection algorithm to a popular PPG smartwatch and wristband without integrated algorithm yields a high accuracy for the detection of AF, with an acceptable unclassifiable rate, in a semicontrolled environment.

Addressing the Chronic Pain-Early Cognitive Decline Comorbidity Among Older Adults: Protocol for the Active Brains Remote Efficacy Trial (2023)

JMIR research protocols

Authors: Vranceanu, Ana-Maria; Choukas, Nathaniel R.; Rochon, Elizabeth A.; Duarte, Brooke; Pietrzykowski, Malvina O.; McDermott, Katherine; Hooker, Julia E.; Kulich, Ronald; Quiroz, Yakeel T.; Parker, Robert A.; Macklin, Eric A.; Ritchie, Christine; Active Brains Project; Mace, Ryan A.

Abstract

BACKGROUND: Chronic pain and early cognitive decline, which are costly to treat and highly prevalent among older adults, commonly co-occur, exacerbate one another over time, and can accelerate the development and progression of Alzheimer disease and related dementias. We developed the first mind-body activity program (Active Brains [AB]) tailored to the needs of older adults with chronic pain and early cognitive decline. Results from our previous study strongly supported the feasibility of conducting AB remotely and provided evidence for improvements in outcomes. OBJECTIVE: We are conducting a single-blinded, National Institutes of Health stage-2, randomized clinical trial to establish the efficacy of AB versus a time-matched and dose-matched education control (Health Enhancement Program [HEP]) in improving self-reported and objective outcomes of physical, cognitive, and emotional functions in 260 participants. The methodology described in this paper was informed by the lessons learned from the first year of the trial. METHODS: Participants are identified and recruited through multidisciplinary clinician-referred individuals (eg, pain psychologists and geriatricians), the Rally Research platform, social media, and community partnerships. Interested participants complete eligibility screening and electronic informed consent. Baseline assessments include self-report, performance-based measures (eg, 6-min walk test) and objective measures (eg, Repeatable Battery for the Assessment of Neuropsychological Status). Participants are mailed a wrist-worn ActiGraph device (ActiGraph LLC) to passively monitor objective function (eg, steps) during the week between the baseline assessment and the beginning of the programs, which they continue to wear throughout the programs. After baseline assessments, participants are randomized to either AB or HEP and complete 8 weekly, remote, group sessions with a Massachusetts General Hospital psychologist. The AB group receives a Fitbit (Fitbit Inc) to help reinforce increased activity. Assessments are repeated after the intervention and at the 6-month follow-up. Coprimary outcomes include multimodal physical function (self-report, performance based, and objective). Secondary outcomes are cognitive function (self-report and objective), emotional function, and pain. RESULTS: We began recruitment in July 2022 and recruited 37 participants across 4 cohorts. Of them, all (n=37, 100\%) have completed the baseline assessment, 26 (70\%) have completed the posttest assessment, and 9 (24\%) are actively enrolled in the intervention (total dropout: n=2, 5\%). In the three cohorts (26/37, 70\%) that have completed the AB or HEP, 26 (100\%) participants completed all 8 group sessions (including minimal makeups), and watch adherence (1937/2072, 93.48\%, average across ActiGraph and Fitbit devices) has been excellent. The fourth cohort is ongoing (9/37, 24\%), and we plan to complete enrollment by March 2026. CONCLUSIONS: We aim to establish the efficacy of the AB program over a time-matched and dose-matched control in a live video-based trial and test the mechanisms through theoretically driven mediators and moderators. Findings will inform the development of a future multisite effectiveness-implementation trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT05373745; https://classic.clinicaltrials.gov/ct2/show/NCT05373745. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47319.

Advancing Understanding of Just-in-Time States for Supporting Physical Activity (Project JustWalk JITAI): Protocol for a System ID Study of Just-in-Time Adaptive Interventions (2023)

JMIR research protocols

Authors: Park, Junghwan; Kim, Meelim; El Mistiri, Mohamed; Kha, Rachael; Banerjee, Sarasij; Gotzian, Lisa; Chevance, Guillaume; Rivera, Daniel E.; Klasnja, Predrag; Hekler, Eric

Abstract

BACKGROUND: Just-in-time adaptive interventions (JITAIs) are designed to provide support when individuals are receptive and can respond beneficially to the prompt. The notion of a just-in-time (JIT) state is critical for JITAIs. To date, JIT states have been formulated either in a largely data-driven way or based on theory alone. There is a need for an approach that enables rigorous theory testing and optimization of the JIT state concept. OBJECTIVE: The purpose of this system ID experiment was to investigate JIT states empirically and enable the empirical optimization of a JITAI intended to increase physical activity (steps/d). METHODS: We recruited physically inactive English-speaking adults aged ≥25 years who owned smartphones. Participants wore a Fitbit Versa 3 and used the study app for 270 days. The JustWalk JITAI project uses system ID methods to study JIT states. Specifically, provision of support systematically varied across different theoretically plausible operationalizations of JIT states to enable a more rigorous and systematic study of the concept. We experimentally varied 2 intervention components: notifications delivered up to 4 times per day designed to increase a person's steps within the next 3 hours and suggested daily step goals. Notifications to walk were experimentally provided across varied operationalizations of JIT states accounting for need (ie, whether daily step goals were previously met or not), opportunity (ie, whether the next 3 h were a time window during which a person had previously walked), and receptivity (ie, a person previously walked after receiving notifications). Suggested daily step goals varied systematically within a range related to a person's baseline level of steps per day (eg, 4000) until they met clinically meaningful targets (eg, averaging 8000 steps/d as the lower threshold across a cycle). A series of system ID estimation approaches will be used to analyze the data and obtain control-oriented dynamical models to study JIT states. The estimated models from all approaches will be contrasted, with the ultimate goal of guiding rigorous, replicable, empirical formulation and study of JIT states to inform a future JITAI. RESULTS: As is common in system ID, we conducted a series of simulation studies to formulate the experiment. The results of our simulation studies illustrated the plausibility of this approach for generating informative and unique data for studying JIT states. The study began enrolling participants in June 2022, with a final enrollment of 48 participants. Data collection concluded in April 2023. Upon completion of the analyses, the results of this study are expected to be submitted for publication in the fourth quarter of 2023. CONCLUSIONS: This study will be the first empirical investigation of JIT states that uses system ID methods to inform the optimization of a scalable JITAI for physical activity. TRIAL REGISTRATION: ClinicalTrials.gov NCT05273437; https://clinicaltrials.gov/ct2/show/NCT05273437. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52161.

Ambulation for Latency during Expectant Management of PPROM: A Randomized Controlled Trial (AMBLE) (2023)

American journal of obstetrics \& gynecology MFM

Authors: Pineles, Beth L.; Vial, Mallory; Castro, Ms Tania; Ghorayeb, Tala; Ajishegiri, Ms Oluwadare; Sadek, Sandra; Pedroza, Claudia; Blackwell, Sean C.; Chauhan, Suneet P.; Sibai, Baha M.

Abstract

Background: Individuals hospitalized with preterm prelabor rupture of the membranes (PPROM) are often advised to limit their activity or adhere to bedrest. Some evidence suggests that greater activity is associated with longer latency and improved outcomes, but no high-quality evidence from a randomized-controlled trial exists. Objective: To evaluate whether encouragement to ambulate at least 2,000 steps daily impacts latency among individuals with PPROM compared with usual care. Study design: Multisite unblinded, two-arm randomized trial of individuals at 23 0/7 to 35 0/7 weeks gestation undergoing inpatient expectant management of PPROM with planned delivery at least 7 days away. Each participant wore a Fitbit InspireTM that tracked steps. The intervention arm was encouraged (verbal and Fitbit-based reminders) to reach a goal of 2,000 steps per day. The usual care arm was allowed ad lib activity with no step goal or reminders. The primary outcome was latency (days) from randomization to delivery. Secondary analyses included composite neonatal and maternal clinical outcomes and maternal mental health survey results. Statistical analyses were intent-to-treat under a Bayesian framework using neutral priors (a priori assumed 50:50 likelihood of longer latency in either arm). 100 participants were required to have 80% power to demonstrate a 4-day difference in latency with 75% certainty (Bayesian probability). Results: Among 163 eligible individuals, 100 (61%) were randomized, and after loss to follow-up, 95 were analyzed. Gestational age at randomization was 29 3/7 weeks (interquartile range [IQR] 26 2/7, 31 5/7) in the intervention arm and 27 4/7 weeks (IQR 25 4/7, 29 6/7) in the usual care arm. Median step counts were 1,690/day in the intervention arm (IQR 1,031-2,641) and 1,338/day in the usual care arm (IQR 784-1,913). Median days of latency were 9 days in the intervention arm (IQR 4-17) and 6 days in the usual care arm (IQR 2-14). The primary analysis indicated a 65% posterior probability that the intervention increased latency versus usual care (posterior relative risk [RR] 1.09; 95% credible interval [CrI], 0.70-1.71). The RR for composite neonatal adverse outcome was 0.55 (95% CrI 0.32-0.82) with 99% posterior probability of intervention benefit and for composite maternal adverse outcome was 0.94 (95% CrI 0.72-1.20), with 70% posterior probability of intervention benefit. There was a 94% posterior probability of the intervention arm having a greater decrease in maternal stress score from baseline to before delivery compared with the usual care arm (mean arm difference 3.24 points [95% CrI -7.23-0.79]). Adjustment for gestational age at randomization had minimal impact on secondary outcome results. Conclusions: Individuals with PPROM randomized to encouragement to ambulate had a longer latency to delivery and improved neonatal and mental health outcomes with similar maternal clinical outcomes compared to usual care. Keywords: PROM; Walking; bedrest; exercise; limited activity; modified activity; pregnancy; prematurity; preterm delivery; preterm labor; preterm prelabor rupture of membranes; preterm premature rupture of membranes.

An overview of the together everyone achieves more physical activity (TEAM-PA) trial to increase physical activity among African American women (2023)

Contemporary Clinical Trials

Authors: Sweeney, Allison M.; Wilson, Dawn K.; Zarrett, Nicole; Martin, Pamela; Hardin, James W.; Fairchild, Amanda; Mitchell, Sheryl; Decker, Lindsay

Abstract

Background: The Together Everyone Achieves More Physical Activity (TEAM-PA) trial is a randomized controlled trial testing the efficacy of a group-based intervention for increasing physical activity (PA) among insufficiently active African American women. Design: The TEAM-PA trial uses a group cohort design, is implemented at community sites, and will involve 360 African American women. The trial compares a 10-week group-based intervention vs. a standard group-delivered PA comparison program. Measures include minutes of total PA/day using 7-day accelerometer estimates (primary outcome), and body mass index, blood pressure, waist circumference, walking speed, sedentary behavior, light physical activity, and the percentage achieving ≥150 min of moderate to vigorous PA/week (secondary outcomes) at baseline, post-intervention, and 6-months post-intervention. Intervention: The intervention integrates elements from Social Cognitive Theory, Self-Determination Theory, Group Dynamics Theory, and a focus on collectivism to evaluate different components of social affiliation (relatedness, reciprocal support, group cohesion, and collective efficacy). The intervention integrates shared goal-setting via Fitbits, group-based problem-solving, peer-to-peer positive communication, friendly competition, and cultural topics related to collectivism. Compared to the standard group-delivered PA program, participants in the intervention are expected to show greater improvements from baseline to post- and 6-month follow-up on minutes of total PA/day and secondary outcomes. Social affiliation variables (vs. individual-level factors) will be evaluated as mediators of the treatment effect. Implications: The results of the TEAM-PA trial will determine the efficacy of the intervention and identify which aspects of social affiliation are most strongly related to increased PA among African American women. Trial registration: This study was registered on Clinicaltrials.gov (# NCT05519696) in August 2022 prior to initial participant enrollment.

Assessment of 24-hour physical behaviour in adults via wearables: a systematic review of validation studies under laboratory conditions (2023)

The International Journal of Behavioral Nutrition and Physical Activity

Authors: Giurgiu, Marco; Ketelhut, Sascha; Kubica, Claudia; Nissen, Rebecca; Doster, Ann-Kathrin; Thron, Maximiliane; Timm, Irina; Giurgiu, Valeria; Nigg, Claudio R.; Woll, Alexander; Ebner-Priemer, Ulrich W.; Bussmann, Johannes B. J.

Abstract

Background: Wearable technology is used by consumers and researchers worldwide for continuous activity monitoring in daily life. Results of high-quality laboratory-based validation studies enable us to make a guided decision on which study to rely on and which device to use. However, reviews in adults that focus on the quality of existing laboratory studies are missing. Methods: We conducted a systematic review of wearable validation studies with adults. Eligibility criteria were: (i) study under laboratory conditions with humans (age ≥ 18 years); (ii) validated device outcome must belong to one dimension of the 24-hour physical behavior construct (i.e., intensity, posture/activity type, and biological state); (iii) study protocol must include a criterion measure; (iv) study had to be published in a peer-reviewed English language journal. Studies were identified via a systematic search in five electronic databases as well as back- and forward citation searches. The risk of bias was assessed based on the QUADAS-2 tool with eight signaling questions. Results: Out of 13,285 unique search results, 545 published articles between 1994 and 2022 were included. Most studies (73.8% (N = 420)) validated an intensity measure outcome such as energy expenditure; only 14% (N = 80) and 12.2% (N = 70) of studies validated biological state or posture/activity type outcomes, respectively. Most protocols validated wearables in healthy adults between 18 and 65 years. Most wearables were only validated once. Further, we identified six wearables (i.e., ActiGraph GT3X+, ActiGraph GT9X, Apple Watch 2, Axivity AX3, Fitbit Charge 2, Fitbit, and GENEActiv) that had been used to validate outcomes from all three dimensions, but none of them were consistently ranked with moderate to high validity. Risk of bias assessment resulted in 4.4% (N = 24) of all studies being classified as "low risk", while 16.5% (N = 90) were classified as "some concerns" and 79.1% (N = 431) as "high risk". Conclusion: Laboratory validation studies of wearables assessing physical behaviour in adults are characterized by low methodological quality, large variability in design, and a focus on intensity. Future research should more strongly aim at all components of the 24-hour physical behaviour construct, and strive for standardized protocols embedded in a validation framework.

Comparison of Polysomnography, Single-Channel Electroencephalogram, Fitbit, and Sleep Logs in Patients With Psychiatric Disorders: Cross-Sectional Study (2023)

Journal of Medical Internet Research

Authors: Kawai, Keita; Iwamoto, Kunihiro; Miyata, Seiko; Okada, Ippei; Fujishiro, Hiroshige; Noda, Akiko; Nakagome, Kazuyuki; Ozaki, Norio; Ikeda, Masashi

Abstract

BACKGROUND: Sleep disturbances are core symptoms of psychiatric disorders. Although various sleep measures have been developed to assess sleep patterns and quality of sleep, the concordance of these measures in patients with psychiatric disorders remains relatively elusive. OBJECTIVE: This study aims to examine the degree of agreement among 3 sleep recording methods and the consistency between subjective and objective sleep measures, with a specific focus on recently developed devices in a population of individuals with psychiatric disorders. METHODS: We analyzed 62 participants for this cross-sectional study, all having data for polysomnography (PSG), Zmachine, Fitbit, and sleep logs. Participants completed questionnaires on their symptoms and estimated sleep duration the morning after the overnight sleep assessment. The interclass correlation coefficients (ICCs) were calculated to evaluate the consistency between sleep parameters obtained from each instrument. Additionally, Bland-Altman plots were used to visually show differences and limits of agreement for sleep parameters measured by PSG, Zmachine, Fitbit, and sleep logs. RESULTS: The findings indicated a moderate agreement between PSG and Zmachine data for total sleep time (ICC=0.46; P{\textless}.001), wake after sleep onset (ICC=0.39; P=.002), and sleep efficiency (ICC=0.40; P=.006). In contrast, Fitbit demonstrated notable disagreement with PSG (total sleep time: ICC=0.08; wake after sleep onset: ICC=0.18; sleep efficiency: ICC=0.10) and exhibited particularly large discrepancies from the sleep logs (total sleep time: ICC=-0.01; wake after sleep onset: ICC=0.05; sleep efficiency: ICC=-0.02). Furthermore, subjective and objective concordance among PSG, Zmachine, and sleep logs appeared to be influenced by the severity of the depressive symptoms and obstructive sleep apnea, while these associations were not observed between the Fitbit and other sleep instruments. CONCLUSIONS: Our study results suggest that Fitbit accuracy is reduced in the presence of comorbid clinical symptoms. Although user-friendly, Fitbit has limitations that should be considered when assessing sleep in patients with psychiatric disorders.

Data-efficient machine learning methods in the ME-TIME study: Rationale and design of a longitudinal study to detect atrial fibrillation and heart failure from wearables (2023)

Cardiovascular Digital Health Journal

Authors: Naseri, Arman; Tax, David; van der Harst, Pim; Reinders, Marcel; van der Bilt, Ivo

Abstract

Background: Smartwatches enable continuous and noninvasive time series monitoring of cardiovascular biomarkers like heart rate (from photoplethysmograms), step counter, skin temperature, et cetera; as such, they have promise in assisting in early detection and prevention of cardiovascular disease. Although these biomarkers may not be directly useful to physicians, a machine learning (ML) model could find clinically relevant patterns. Unfortunately, ML models typically need supervised (ie, annotated) data, and labeling of large amounts of continuous data is very labor intensive. Therefore, ML methods that are data efficient, ie, needing a low number of labels, are required to detect potential clinical value in patterns found in wearable data. Objective: The primary study objective of the ME-TIME (Machine Learning Enabled Time Series Analysis in Medicine) study is to design an ML model that can detect atrial fibrillation (AF) and heart failure (HF) from wearable data in a data-efficient manner. To achieve this, self-supervised and weakly supervised learning techniques are used. Methods: Two hundred subjects (100 reference, 50 AF, and 50 HF) are being invited to participate in wearing a Fitbit fitness tracker for 3 months. Interested volunteers are sent a questionnaire to determine their health, in particular cardiovascular health. Volunteers without any (history of) serious illness are assigned to the reference group. Participants with AF and HF are recruited in the Haga teaching hospital in The Hague, The Netherlands. Results: Enrollment commenced on May 1, 2022, and as of the time of this report, 62 subjects have been included in the study. Preliminary analysis of the data reveals significant inter-subject variability. Notably, we identified heart rate recovery curves and time-delayed correlations between heart rate and step count as potential strong indicators for heart disease. Conclusion: Using self-supervised and multiple-instance learning techniques, we hypothesize that patterns specific to AF and HF can be found in continuous data obtained from smartwatches. Keywords: Artificial intelligence; Atrial fibrillation; Heart failure; Machine learning; Multiple-instance learning; Self-supervised learning; Smartwatch; Wearables; mHealth.

Daytime Sleep-Tracking Performance of Four Commercial Wearable Devices During Unrestricted Home Sleep (2023)

Nature and Science of Sleep

Authors: Chinoy, Evan D.; Cuellar, Joseph A.; Jameson, Jason T.; Markwald, Rachel R.

Abstract

Purpose: Previous studies have found that many commercial wearable devices can accurately track sleep-wake patterns in laboratory or home settings. However, nearly all previous studies tested devices under conditions with fixed time in bed (TIB) and during nighttime sleep episodes only. Despite its relevance to shift workers and others with irregular sleep schedules, it is largely unknown how devices track daytime sleep. Therefore, we tested the sleep-tracking performance of four commercial wearable devices during unrestricted home daytime sleep. Participants and Methods: Participants were 16 healthy young adults (6 men, 10 women; 26.6 ± 4.6 years, mean ± SD) with habitual daytime sleep schedules. Participants slept at home for 1 week under unrestricted conditions (ie, self-selecting TIB) using a set of four commercial wearable devices and completed reference sleep logs. Wearables included the Fatigue Science ReadiBand, Fitbit Inspire HR, Oura Ring, and Polar Vantage V Titan. Daytime sleep episode TIB biases and frequencies of missed and false-positive daytime sleep episodes were examined. Results: TIB bias was low in general for all devices on most daytime sleep episodes, but some exhibited large biases (eg, > 1 h). Total missed daytime sleep episodes were as follows: Fatigue Science: 3.6%; Fitbit: 4.8%; Oura: 6.0%; Polar: 37.3%. Missed episodes occurred most often when TIB was short (eg, naps < 4 h). Conclusion: When daytime sleep episodes were recorded, the devices generally exhibited similar performance for tracking TIB (ie, most episodes had low bias). However, the devices failed to detect some daytime episodes, which occurred most often when TIB was short, but varied across devices (especially Polar, which missed over one-third of episodes). Findings suggest that accurate daytime sleep tracking is largely achievable with commercial wearable devices. However, performance differences for missed recordings suggest that some devices vary in reliability (especially for naps), but improvements could likely be made with changes to algorithm sensitivities.

URL

Development of a Mobile Health Snacktivity App to Promote Physical Activity in Inactive Adults (SnackApp): Intervention Mapping and User Testing Study (2023)

JMIR formative research

Authors: Sanders, James P.; Gokal, Kajal; Thomas, Jonah J. C.; Rawstorn, Jonathan C.; Sherar, Lauren B.; Maddison, Ralph; Greaves, Colin J.; Esliger, Dale; Daley, Amanda J.; Snacktivity Investigators

Abstract

BACKGROUND: Despite the unequivocal evidence demonstrating the benefits of being physically active, many people do not meet the recommended guidelines of at least 150 minutes of moderate- to vigorous-intensity physical activity per week. This can be changed with the development and implementation of innovative interventions. The use of mobile health (mHealth) technologies has been suggested as a mechanism to offer people innovative health behavior change interventions. OBJECTIVE: This study aims to outline the systematic, theory-driven processes and user testing applied to the development of a smartphone-based physical activity app (SnackApp) to promote participation in a novel physical activity intervention called Snacktivity. The acceptability of the app was explored and reported. METHODS: Intervention mapping involves a 6-step process, the first 4 of which were presented in this study. These steps were used to develop the SnackApp for use within the Snacktivity intervention. The first step involved a needs assessment, which included composing an expert planning group, patient and public involvement group, and gathering the views of the public on Snacktivity and the public perception of the use of wearable technology to support Snacktivity. This first step aimed to determine the overall purpose of the Snacktivity intervention. Steps 2 to 4 involved determining the intervention objectives, the behavior change theory and techniques on which the intervention is based, and the development of the intervention resources (ie, SnackApp). After the completion of steps 1 to 3 of the intervention mapping process, the SnackApp was developed and linked to a commercial physical activity tracker (Fitbit Versa Lite) for the automated capture of physical activity. SnackApp includes provisions for goal setting, activity planning, and social support. Stage 4 involved users (inactive adults, N=15) testing the SnackApp for 28 days. App engagement (mobile app use analytics) was analyzed to determine app use and to inform the further development of SnackApp. RESULTS: Over the study period (step 4), participants engaged with SnackApp an average of 77 (SD 80) times. On average, participants used the SnackApp for 12.6 (SD 47) minutes per week, with most of the time spent on the SnackApp dashboard and engaging, on average, 14 (SD 12.1) times, lasting 7 to 8 minutes per week. Overall, male participants used the SnackApp more than female participants did. The app rating score was 3.5 (SD 0.6) out of 5, suggesting that SnackApp was rated as fair to good. CONCLUSIONS: This study outlines and reports data regarding the development of an innovative mHealth app using a systematic, theory-driven framework. This approach can guide the development of future mHealth programs. User testing of the SnackApp suggested that physically inactive adults will engage with the SnackApp, indicating its applicability of use in the Snacktivity physical activity intervention.

Ecological Momentary Assessments and Passive Sensing in the Prediction of Short-Term Suicidal Ideation in Young Adults (2023)

JAMA network open

Authors: Czyz, Ewa K.; King, Cheryl A.; Al-Dajani, Nadia; Zimmermann, Lauren; Hong, Victor; Nahum-Shani, Inbal

Abstract

IMPORTANCE: Advancements in technology, including mobile-based ecological momentary assessments (EMAs) and passive sensing, have immense potential to identify short-term suicide risk. However, the extent to which EMA and passive data, particularly in combination, have utility in detecting short-term risk in everyday life remains poorly understood. OBJECTIVE: To examine whether and what combinations of self-reported EMA and sensor-based assessments identify next-day suicidal ideation. DESIGN, SETTING, AND PARTICIPANTS: In this intensive longitudinal prognostic study, participants completed EMAs 4 times daily and wore a sensor wristband (Fitbit Charge 3) for 8 weeks. Multilevel machine learning methods, including penalized generalized estimating equations and classification and regression trees (CARTs) with repeated 5-fold cross-validation, were used to optimize prediction of next-day suicidal ideation based on time-varying features from EMAs (affective, cognitive, behavioral risk factors) and sensor data (sleep, activity, heart rate). Young adult patients who visited an emergency department with recent suicidal ideation and/or suicide attempt were recruited. Identified via electronic health record screening, eligible individuals were contacted remotely to complete enrollment procedures. Participants (aged 18 to 25 years) completed 14 708 EMA observations (64.4\% adherence) and wore a sensor wristband approximately half the time (55.6\% adherence). Data were collected between June 2020 and July 2021. Statistical analysis was performed from January to March 2023. MAIN OUTCOMES AND MEASURES: The outcome was presence of next-day suicidal ideation. RESULTS: Among 102 enrolled participants, 83 (81.4\%) were female; 6 (5.9\%) were Asian, 5 (4.9\%) were Black or African American, 9 (8.8\%) were more than 1 race, and 76 (74.5\%) were White; mean (SD) age was 20.9 (2.1) years. The best-performing model incorporated features from EMAs and showed good predictive accuracy (mean [SE] cross-validated area under the receiver operating characteristic curve [AUC], 0.84 [0.02]), whereas the model that incorporated features from sensor data alone showed poor prediction (mean [SE] cross-validated AUC, 0.56 [0.02]). Sensor-based features did not improve prediction when combined with EMAs. Suicidal ideation-related features were the strongest predictors of next-day ideation. When suicidal ideation features were excluded, an alternative EMA model had acceptable predictive accuracy (mean [SE] cross-validated AUC, 0.76 [0.02]). Both EMA models included features at different timescales reflecting within-day, end-of-day, and time-varying cumulative effects. CONCLUSIONS AND RELEVANCE: In this prognostic study, self-reported risk factors showed utility in identifying near-term suicidal thoughts. Best-performing models required self-reported information, derived from EMAs, whereas sensor-based data had negligible predictive accuracy. These results may have implications for developing decision algorithms identifying near-term suicidal thoughts to guide risk monitoring and intervention delivery in everyday life.

Effect of digital monitoring and counselling on self-management ability in patients with rheumatoid arthritis: a randomised controlled trial (2023)

Rheumatology (Oxford, England)

Authors: Li, Linda C.; Xie, Hui; Feehan, Lynne M.; Shaw, Chris; Lu, Na; Ramachandran, Smruthi; Wang, Ellen; Therrien, Stephanie; Mucha, Julia; Hoens, Alison M.; English, Kelly; Davidson, Eileen; Liu-Ambrose, Teresa; Backman, Catherine L.; Esdaile, John M.; Miller, Kimberly J.; Lacaille, Diane

Abstract

OBJECTIVES: To assess a remote physiotherapist (PT) counselling intervention using self-monitoring tools for improving self-management ability, physical activity participation, and health outcomes in people with rheumatoid arthritis (RA). METHODS: Eligible participants were randomly assigned to receive group education, a Fitbit®, a self-monitoring app, and PT counselling phone calls (Immediate Group). The Delayed Group received a monthly e-newsletter until week 26, and then the intervention. The primary outcome was Patient Activation Measure (PAM-13). Participants were assessed at baseline, 27 weeks (the primary end point) and 53 weeks. Secondary outcomes included disease activity, pain, fatigue, depression, sitting/walking habits, daily physical activity time, and daily awake sedentary time. Generalized Linear Mixed-effect Models (GLMMs) were used to assess the effect of the intervention on the change of each outcome measure from the initiation to 27 weeks after the intervention. RESULTS: Analysis included 131 participants (91.6\% women; 80.2\% completed during the COVID-19 pandemic). The mean change of PAM-13 at 27 weeks was 4.6 (SD = 14.7) in the Immediate Group vs -1.6 (SD = 12.5) in the Delayed Group. The mean change in Delayed Group at 53 weeks (after the 26-week intervention) was 3.6 (SD = 14.6). Overall, the intervention improved PAM-13 at 27 weeks post-intervention from the GLMM analysis (adjusted coefficient: 5.3; 95\% CI: 2.0, 8.7; p = {\textless}0.001). Favourable intervention effects were also found in disease activity, fatigue, depression, and self-reported walking habit. CONCLUSION: Remote counselling paired with self-monitoring tools improved self-management ability in people with RA. Findings of secondary outcomes indicate that the intervention had a positive effect on symptom management.

Efficacy of the Aim2Be Intervention in Changing Lifestyle Behaviors Among Adolescents With Overweight and Obesity: Randomized Controlled Trial (2023)

Journal of Medical Internet Research

Authors: Tugault-Lafleur, Claire N.; De-Jongh González, Olivia; Macdonald, Janice; Bradbury, Jennifer; Warshawski, Tom; Ball, Geoff D. C.; Morrison, Katherine; Ho, Josephine; Hamilton, Jill; Buchholz, Annick; Mâsse, Louise

Abstract

Background: Aim2Be is a gamified lifestyle app designed to promote lifestyle behavior changes among Canadian adolescents and their families. Objective: The primary aim was to test the efficacy of the Aim2Be app with support from a live coach to reduce weight outcomes (BMI Z score [zBMI]) and improve lifestyle behaviors among adolescents with overweight and obesity and their parents versus a waitlist control group over 3 months. The secondary aim was to compare health trajectories among waitlist control participants over 6 months (before and after receiving access to the app), assess whether support from a live coach enhanced intervention impact, and evaluate whether the app use influenced changes among intervention participants. Methods: A 2-arm parallel randomized controlled trial was conducted from November 2018 to June 2020. Adolescents aged 10 to 17 years with overweight or obesity and their parents were randomized into an intervention group (Aim2Be with a live coach for 6 months) or a waitlist control group (Aim2Be with no live coach; accessed after 3 months). Adolescents' assessments at baseline and at 3 and 6 months included measured height and weight, 24-hour dietary recalls, and daily step counts measured with a Fitbit. Data on self-reported physical activity, screen time, fruit and vegetable intake, and sugary beverage intake of adolescents and parents were also collected. Results: A total of 214 parent-child participants were randomized. In our primary analyses, there were no significant differences in zBMI or any of the health behaviors between the intervention and control groups at 3 months. In our secondary analyses, among waitlist control participants, zBMI (P=.02), discretionary calories (P=.03), and physical activity outside of school (P=.001) declined, whereas daily screen time increased (P<.001) after receiving access to the app compared with before receiving app access. Adolescents randomized to Aim2Be with live coaching reported more time being active outside of school compared with adolescents who used Aim2Be with no coaching over 3 months (P=.001). App use did not modify any changes in outcomes among adolescents in the intervention group. Conclusions: The Aim2Be intervention did not improve zBMI and lifestyle behaviors in adolescents with overweight and obesity compared with the waitlist control group over 3 months. Future studies should explore the potential mediators of changes in zBMI and lifestyle behaviors as well as predictors of engagement. Trial registration: ClinicalTrials.gov NCT03651284; https://clinicaltrials.gov/ct2/show/study/NCT03651284.

Evaluation of the effectiveness of sleep hygiene education and FITBIT devices on quality of sleep and psychological worry: a pilot quasi-experimental study among first-year college students (2023)

Frontiers in Public Health

Authors: Bani Issa, Wegdan; Hijazi, Heba; Radwan, Hadia; Saqan, Roba; Al-Sharman, Alham; Samsudin, A. B. Rani; Fakhry, Randa; Al-Yateem, Nabeel; Rossiter, Rachel C.; Ibrahim, Ali; Moustafa, Ibrahim; Naja, Farah; Alameddine, Mohamad; Abbas, Nada; Abdelrahim, Dana N.; Al-Shujairi, Arwa; Awad, Manal

Abstract

BACKGROUND: College students report disturbed sleep patterns that can negatively impact their wellbeing and academic performance. OBJECTIVES: This study examined the effect of a 4-week sleep hygiene program that included sleep education and actigraph sleep trackers (FITBITs) on improving sleep quality and reducing psychological worry without control group. DESIGN SETTINGS AND PARTICIPANTS: A pilot quasi-experimental design, participants were randomly selected medical and health sciences from a university students in the United-Arab-Emirates. METHODS: Students were asked to wear FITBITs and log their daily sleep data and completed the Pittsburgh Sleep Quality Index (PSQI) and Penn State Worry Questionnaire (PSWQ). Extensive sleep hygiene education was delivered via lectures, a WhatsApp group, and the Blackboard platform. In total, 50 students completed pre-and post-assessments and returned FITBIT data. RESULTS: There was a significant difference in the prevalence of good sleep postintervention compared with pre-intervention (46\% vs. 28\%; p = 0.0126). The mean PSQI score was significantly lower post-intervention compared with pre-intervention (6.17 ± 3.16 vs. 7.12.87; p = 0.04, Cohen's d 0.33). After the intervention, subjective sleep quality, sleep latency, and daytime dysfunction were significantly improved compared with pre-intervention (p {\textless} 0.05). In addition, FITBIT data showed total sleep time and the number of restless episodes per night were significantly improved postintervention compared with pre-intervention (p = 0.013). The mean PSWQ score significantly decreased from pre-intervention to p = 0.049, Cohen' d = 0.25. The correlation between PSQI and PSWQ scores was significant post-intervention (β = 0.40, p = 0.02). CONCLUSION: Our results may inform university educational policy and curricular reform to incorporate sleep hygiene awareness programs to empower students and improve their sleep habits.

Examining changes in vascular function, arterial stiffness and systemic inflammation during hospitalization and recovery from an acute exacerbation of chronic obstructive pulmonary disease (2023)

Scientific Reports

Authors: Fuhr, Desi P.; Brotto, Andrew R.; Rowe, Brian H.; Bhutani, Mohit; Rosychuk, Rhonda J.; Stickland, Michael K.

Abstract

An acute exacerbation of COPD (AECOPD) is associated with increased risk of cardiovascular (CV) events. The elevated risk during an AECOPD may be related to changes in vascular function, arterial stiffness, and systemic inflammation; the time course of these measures and their corresponding recovery are poorly understood. Further, physical activity is reduced during an AECOPD, and physical activity may influence the cardiovascular responses to an AECOPD. The purpose of the study was to examine the acute impact of an AECOPD requiring hospitalization on vascular function, arterial stiffness, and systemic inflammation and examine whether physical activity modulates these variables during recovery. Patients hospitalized for an AECOPD were prospectively recruited and compared to control patients with stable COPD. Vascular function, arterial stiffness, and systemic inflammation (CRP, IL-6) were measured at hospital admission, hospital discharge and within 14 days of discharge. Physical activity was electronically tracked daily while in hospital and for 7 days following discharge using a Fitbit. One hundred and twenty-one patients with an AECOPD requiring hospitalization and 33 control patients with stable COPD were enrolled in the study. Vascular function was significantly lower, and systemic inflammation higher at hospital admission in patients with an AECOPD compared to stable COPD. Significant improvements in vascular function and inflammation were observed within 14 days of hospital discharge; however, vascular function remained lower than stable COPD. Physical activity was low at admission and increased following discharge; however, physical activity was unrelated to measures of vascular function or inflammation at any time point. An AECOPD requiring hospitalization is associated with impaired vascular function that persists during recovery. These findings provide a mechanistic link to help explain the enduring increase in CV risk and mortality following a severe AECOPD event.Clinical trial registration: ClinicalTrials.gov \#NCT01949727; Registered: 09/20/2013.

Exploring Variations in Sleep Perception: Comparative Study of Chatbot Sleep Logs and Fitbit Sleep Data (2023)

JMIR mHealth and uHealth

Authors: Jang, Hyunchul; Lee, Siwoo; Son, Yunhee; Seo, Sumin; Baek, Younghwa; Mun, Sujeong; Kim, Hoseok; Kim, Icktae; Kim, Junho

Abstract

Background: Patient-generated health data are important in the management of several diseases. Although there are limitations, information can be obtained using a wearable device and time-related information such as exercise time or sleep time can also be obtained. Fitbits can be used to acquire sleep onset, sleep offset, total sleep time (TST), and wakefulness after sleep onset (WASO) data, although there are limitations regarding the depth of sleep and satisfaction; therefore, the patient's subjective response is still important information that cannot be replaced by wearable devices. Objective: To effectively use patient-generated health data related to time such as sleep, it is first necessary to understand the characteristics of the time response recorded by the user. Therefore, the aim of this study was to analyze the characteristics of individuals' time perception in comparison with wearable data. Methods: Sleep data were acquired for 2 weeks using a Fitbit. Participants' sleep records were collected daily through chatbot conversations while wearing the Fitbit, and the two sets of data were statistically compared. Results: In total, 736 people aged 30-59 years were recruited for this study, and the sleep data of 543 people who wore a Fitbit and responded to the chatbot for more than 7 days on the same day were analyzed. Research participants tended to respond to sleep-related times on the hour or in 30-minute increments, and each participant responded within the range of 60-90 minutes from the value measured by the Fitbit. On average for all participants, the chat responses and the Fitbit data were similar within a difference of approximately 15 minutes. Regarding sleep onset, the participant response was 8 minutes and 39 seconds (SD 58 minutes) later than that of the Fitbit data, whereas with respect to sleep offset, the response was 5 minutes and 38 seconds (SD 57 minutes) earlier. The participants' actual sleep time (AST) indicated in the chat was similar to that obtained by subtracting the WASO from the TST measured by the Fitbit. The AST was 13 minutes and 39 seconds (SD 87 minutes) longer than the time WASO was subtracted from the Fitbit TST. On days when the participants reported good sleep, they responded 19 (SD 90) minutes longer on the AST than the Fitbit data. However, for each sleep event, the probability that the participant's AST was within ±30 and ±60 minutes of the Fitbit TST-WASO was 50.7% and 74.3%, respectively. Conclusions: The chatbot sleep response and Fitbit measured time were similar on average and the study participants had a slight tendency to perceive a relatively long sleep time if the quality of sleep was self-reported as good. However, on a participant-by-participant basis, it was difficult to predict participants' sleep duration responses with Fitbit data. Individual variations in sleep time perception significantly affect patient responses related to sleep, revealing the limitations of objective measures obtained through wearable devices. Keywords: Fitbit; PGHD; chat; patient-generated health data; self-report; sleep; sleep diary; sleep log; sleep time; wearables.

Feasibility and scalability of a fitness tracker study: Results from a longitudinal analysis of persons with multiple sclerosis (2023)

Frontiers in Digital Health

Authors: Sieber, Chloé; Haag, Christina; Polhemus, Ashley; Sylvester, Ramona; Kool, Jan; Gonzenbach, Roman; von Wyl, Viktor

Abstract

Background: Consumer-grade fitness trackers offer exciting opportunities to study persons with chronic diseases in greater detail and in their daily-life environment. However, attempts to bring fitness tracker measurement campaigns from tightly controlled clinical environments to home settings are often challenged by deteriorating study compliance or by organizational and resource limitations. Objectives: By revisiting the study design and patient-reported experiences of a partly remote study with fitness trackers (BarKA-MS study), we aimed to qualitatively explore the relationship between overall study compliance and scalability. On that account, we aimed to derive lessons learned on strengths, weaknesses, and technical challenges for the conduct of future studies. Methods: The two-phased BarKA-MS study employed Fitbit Inspire HR and electronic surveys to monitor physical activity in 45 people with multiple sclerosis in a rehabilitation setting and in their natural surroundings at home for up to 8 weeks. We examined and quantified the recruitment and compliance in terms of questionnaire completion and device wear time. Furthermore, we qualitatively evaluated experiences with devices according to participants' survey-collected reports. Finally, we reviewed the BarKA-MS study conduct characteristics for its scalability according to the Intervention Scalability Assessment Tool checklist. Results: Weekly electronic surveys completion reached 96%. On average, the Fitbit data revealed 99% and 97% valid wear days at the rehabilitation clinic and in the home setting, respectively. Positive experiences with the device were predominant: only 17% of the feedbacks had a negative connotation, mostly pertaining to perceived measurement inaccuracies. Twenty-five major topics and study characteristics relating to compliance were identified. They broadly fell into the three categories: "effectiveness of support measures", "recruitment and compliance barriers", and "technical challenges". The scalability assessment revealed that the highly individualized support measures, which contributed greatly to the high study compliance, may face substantial scalability challenges due to the strong human involvement and limited potential for standardization. Conclusion: The personal interactions and highly individualized participant support positively influenced study compliance and retention. But the major human involvement in these support actions will pose scalability challenges due to resource limitations. Study conductors should anticipate this potential compliance-scalability trade-off already in the design phase.

Fitbit Data to Assess Functional Capacity in Patients Before Elective Surgery: Pilot Prospective Observational Study (2023)

Journal of Medical Internet Research

Authors: Angelucci, Alessandra; Greco, Massimiliano; Canali, Stefano; Marelli, Giovanni; Avidano, Gaia; Goretti, Giulia; Cecconi, Maurizio; Aliverti, Andrea

Abstract

Background: Preoperative assessment is crucial to prevent the risk of complications of surgical operations and is usually focused on functional capacity. The increasing availability of wearable devices (smartwatches, trackers, rings, etc) can provide less intrusive assessment methods, reduce costs, and improve accuracy. Objective: The aim of this study was to present and evaluate the possibility of using commercial smartwatch data, such as those retrieved from the Fitbit Inspire 2 device, to assess functional capacity before elective surgery and correlate such data with the current gold standard measure, the 6-Minute Walk Test (6MWT) distance. Methods: During the hospital visit, patients were evaluated in terms of functional capacity using the 6MWT. Patients were asked to wear the Fitbit Inspire 2 for 7 days (with flexibility of -2 to +2 days) after the hospital visit, before their surgical operation. Resting heart rate and daily steps data were retrieved directly from the smartwatch. Feature engineering techniques allowed the extraction of heart rate over steps (HROS) and a modified version of Non-Exercise Testing Cardiorespiratory Fitness. All measures were correlated with 6MWT. Results: In total, 31 patients were enrolled in the study (n=22, 71% men; n=9, 29% women; mean age 76.06, SD 4.75 years). Data were collected between June 2021 and May 2022. The parameter that correlated best with the 6MWT was the Non-Exercise Testing Cardiorespiratory Fitness index (r=0.68; P<.001). The average resting heart rate over the whole acquisition period for each participant had r=-0.39 (P=.03), even if some patients did not wear the device at night. The correlation of the 6MWT distance with the HROS evaluated at 1% quantile was significant, with Pearson coefficient of -0.39 (P=.04). Fitbit step count had a fair correlation of 0.59 with 6MWT (P<.001). Conclusions: Our study is a promising starting point for the adoption of wearable technology in the evaluation of functional capacity of patients, which was strongly correlated with the gold standard. The study also identified limitations in the availability of metrics, variability of devices, accuracy and quality of data, and accessibility as crucial areas of focus for future studies.

GamerFit-ASD beta test: adapting an evidence-based exergaming and telehealth coaching intervention for autistic youth (2023)

Frontiers in Pediatrics

Authors: Hatfield, Daniel P.; Must, Aviva; Kennedy, Winston; Staiano, Amanda E.; Slavet, James; Sabelli, Rachael A.; Curtin, Carol; Bandini, Linda G.; Nauta, Phillip; Stuetzle, Christopher; Bowling, April B.

Abstract

BACKGROUND: Health disparities faced by autistic youth are exacerbated by inadequate physical activity (PA) and sleep, whereas healthy PA and sleep may improve mood and function. Adaptive Game Squad (AGS) is an evidence-based telehealth coaching and exergaming intervention to improve PA and sleep for adolescents with diverse neurodevelopmental and psychiatric conditions. This study aimed to adapt AGS for autistic youth ages 10-15 years; beta-test the modified intervention for feasibility, accessibility, and engagement; and further refine the intervention for a larger planned demonstration pilot. METHODS: Interdisciplinary experts adapted AGS to create GamerFit-ASD, a 12-week intervention that included a progressive exergame schedule, Fitbit step-tracking, weekly health coaching, and health tip/exercise videos. For beta testing, the intervention was shortened to a 4-week trial with 5 parent/child dyads. Children completed exit surveys and parents and children were interviewed about intervention feasibility, accessibility, and engagement. Exit survey data were summarized with descriptive statistics. Qualitative data were analyzed using a modified grounded-theory approach. RESULTS: All participants (n = 5; ages 10-14 years) attended all 4 planned coaching sessions and completed an average of 9 of 12 planned exergame challenges for a weekly average of 50 min. All participants reported enjoying coaching sessions, 4 of 5 reported enjoying exergames, and 3 of 5 reported enjoying on-demand exercise videos. In interviews, children generally reported finding participation feasible, exergaming challenges active and fun, and coaches friendly and helpful. Parents reported high feasibility of supporting their children's involvement and valued child goal-setting and intervention flexibility; however, some found telehealth sessions overly scripted. Several adaptations to coaching scripts, coach training, and parent materials were made for the larger demonstration pilot, including changes to reduce scriptedness of coaching sessions, to provide parents with more information specific to autism, and to make video content more appropriate to children's needs/preferences. DISCUSSION: A telehealth coaching and exergaming intervention appears feasible, accessible, and engaging for autistic youth aged 10-15. Future studies with larger, more diverse samples, longer study durations and/or follow-up periods, and more rigorous study designs are needed to advance understanding of the appropriateness and effectiveness of this type of intervention for this population.

Harnessing technology and gamification to increase adult physical activity: a cluster randomized controlled trial of the Columbia Moves pilot (2023)

The International Journal of Behavioral Nutrition and Physical Activity

Authors: Monroe, Courtney M.; Cai, Bo; Edney, Sarah; Jake-Schoffman, Danielle E.; Brazendale, Keith; Bucko, Agnes; Armstrong, Bridget; Yang, Chih-Hsiang; Turner-McGrievy, Gabrielle

Abstract

Background: The use of health technologies and gamification to promote physical activity has increasingly been examined, representing an opportunistic method for harnessing social support inherent within existing social ties. However, these prior studies have yielded mixed findings and lacked long-term follow-up periods. Thus, a pilot cluster randomized controlled trial was conducted to gauge the feasibility and preliminary efficacy of a digital gamification-based physical activity promotion approach among teams of insufficiently active adults with existing social ties. Methods: Teams (N = 24; 116 total participants) were randomized to either a 12-week intervention (Fitbit, step goals, app, feedback; TECH) or the same program plus gamification (TECH + Gamification). Mixed effects models were used to compare group differences in treatment adherence, and changes in social support, steps, and moderate-to-vigorous physical activity at 12 weeks and 52 weeks from baseline, adjusted for sociodemographic characteristics and team size. Results: TECH had a lower mean number of days of Fitbit self-monitoring versus TECH + Gamification during the intervention (adjusted difference: -.30; 95% CI, -.54 to -.07; P = .01). Post-intervention, TECH had 47% lower odds of self-monitoring 7 days per week versus TECH + Gamification (.53; 95% CI, .31 to .89; P = .02). No differences were observed between TECH + Gamification and TECH in increases in social support (0.04; 95% CI, -.21 to .29; P = .76), ActiGraph-measured daily steps (-425; 95% CI, -1065 to 215; P = .19), or moderate-to-vigorous physical activity minutes (-3.36; 95% CI, -8.62 to 1.91; P = .21) from baseline to 12 weeks or in the regression of these improvements by 1 year (Ps > .05). Although not significant in the adjusted models (Ps > .05), clinically meaningful differences in Fitbit-measured daily steps (TECH, 7041 ± 2520; TECH + Gamification, 7988 ± 2707) and active minutes (TECH, 29.90 ± 29.76; TECH + Gamification, 36.38 ± 29.83) were found during the intervention. Conclusions: A gamified physical activity intervention targeting teams of adults with existing social ties was feasible and facilitated favorable, clinically meaningful additive physical activity effects while in place but did not drive enhanced, long-term physical activity participation. Future investigations should explore optimal team dynamics and more direct ways of leveraging social support (training teams; gamifying social support).

Health-related impact of illness associated with excessive daytime sleepiness in patients with obstructive sleep apnea (2023)

Postgraduate Medicine

Authors: Grandner, Michael A.; Min, Jae S.; Saad, Ragy; Leary, Eileen B.; Eldemir, Lev; Hyman, Danielle

Abstract

OBJECTIVES: This real-world study aimed to characterize the impact of illness of excessive daytime sleepiness (EDS) in patients with obstructive sleep apnea (OSA) who are adherent to continuous positive airway pressure (CPAP). METHODS: This cross-sectional study surveyed participants in Evidation Health's Achievement app (November 2020-January 2021), a mobile consumer platform that encourages users to develop healthy habits and provides incentives to participate in research. Participants were US-resident adults who self-reported a physician diagnosis of OSA and adherence to CPAP (≥4 hours/night, ≥5 nights/week) for≥6 months. The survey included the Functional Outcomes of Sleep Questionnaire-Short Version (FOSQ-10), Epworth Sleepiness Scale (ESS), and questions regarding comorbidities, CPAP use, caffeine consumption, and physical activity. EDS was defined as ESS score {\textgreater}10. There were more female than male participants; therefore, data were reported separately for females/males. RESULTS: In total, 476 participants (female, n = 283 [59\%]; mean [SD] age, 49.7 [10.8] years; obese, 74.4\%) completed the survey; 209 had EDS (mean [SD] ESS, 13.8 [2.5]) and 267 did not (mean [SD] ESS, 6.3 [2.5]). Self-reported duration of CPAP use was consistent between the EDS/no EDS cohorts, with most participants using CPAP for 7 to 9 hours/night, 7 nights/week. Participants with EDS commonly reported anxiety ([EDS/no EDS] males: 31.5\%/20.0\%; females: 53.7\%/39.5\%), depression (males: 35.6\%/24.2\%; females: 55.9\%/44.9\%), and insomnia (males: 19.2\%/6.7\%; females: 25.7\%/12.9\%) and showed impairment on the FOSQ-10 ([EDS/no EDS] males: 80.8\%/35.0\%; females: 91.9\%/53.1\%). Participants with EDS reported that sleepiness 'very often' prevented physical activity and influenced dietary choices. CONCLUSION: EDS influences choices related to physical activity, caffeine consumption, and diet in patients who are adherent with CPAP. More research is needed to understand the association between EDS and choices of CPAP-adherent patients. Future research should explore the health-related consequences of residual EDS associated with OSA and whether they can be mitigated by improving EDS.

'I saw it as a marriage-You can't have one without the other': A qualitative study of patient and physiotherapist experiences with a therapeutic combined strength and aerobic physical activity exercise programme for hip osteoarthritis (2023)

Musculoskeletal Care

Authors: Allison, Kim; Hall, Michelle; Dobson, Fiona; Lawford, Belinda J.; Bennell, Kim; Spiers, Libby; Hinman, Rana S.

Abstract

INTRODUCTION: To explore physiotherapist and patient experiences with, and acceptability of, a 12-week physiotherapist-guided combined strength and aerobic physical activity exercise programme for hip osteoarthritis (OA). METHODS: A qualitative study using semi-structured interviews with 13 people with hip OA and four physiotherapists. Patients underwent a 12-week home exercise programme customised by weekly visits with one of the four physiotherapists. The programme aimed for patients to participate in 150 min of moderate-intensity aerobic physical activity, and 20-30 min of strengthening exercise 2-3 times per week in concordance with American College of Sports Medicine (ACSM) dosage guidelines. Following the programme, patients and physiotherapists participated in individual semi-structured interviews to explore the acceptability of the exercise programme and barriers and facilitators to participation. Data were audio-recorded, transcribed and analysed using a thematic approach. RESULTS: Five over-arching themes (supporting subthemes) were identified from both patient and physiotherapist interviews: (i) positive outcomes (functional improvements, pain relief, empowerment through experience, commitment to continue); (ii) combined benefits of aerobic and strength exercises (complimentary effects, strengthening exercises key); (iii) valuing support from the physiotherapist (personalised care, skill performance feedback, coach effect, accountability); (iv) motivation and opportunity for exercise (positive symptom loop, integration into daily routine, prior exercise experience, Fitbit motivation); and (v) time-consuming commitment (physiotherapy visit frequency, travel inconvenience, time for exercise). CONCLUSIONS: Experiences of participants in this study indicate that, although time-consuming, a combined aerobic physical activity and strengthening programme prescribed at ACSM dosage guidelines is acceptable and confers positive outcomes in individuals with hip OA.

Learning in a Virtual Environment to Improve Type 2 Diabetes Outcomes: A Randomized Controlled Trial (2023)

JMIR formative research

Authors: Johnson, Constance; D'Eramo Melkus, Gail; Reagan, Louise; Pan, Wei; Amarasekara, Sathya; Pereira, Katherine; Hassell, Nancy; Nowlin, Sarah; Vorderstrasse, Allison

Abstract

Background: Given the importance of self-management in type 2 diabetes mellitus (T2DM) (T2D), a major aspect of health is providing diabetes self-management education and support (DSME/S). There are known barriers including access, availability, and lack of follow through on referral to education programs. Virtual education and support have increased in use, particularly over the last few years. Objective: The purpose of the Diabetes LIVE (Learning in a Virtual Environment) study was to compare the effects of the LIVE intervention (educational 3D world) on diet and physical activity behaviors, behavioral and metabolic outcomes in adults with T2DM over 12 months to an online DSME/S control website. Methods: The LIVE study was a 52-week multi-site randomized controlled trial with longitudinal repeated measures. Participants were randomized to Diabetes LIVE (n =101) or a web control site (n=110). Both contained the same educational materials, but the VE was synchronous and interactive and the other was a flat website. Data were collected at baseline, 3, 6, and 12 months using surveys, clinical, laboratory, and Fitbit measures. Descriptive statistics for baseline characteristics and demographics were used. The effects of the intervention on outcomes were initially examined by comparing the means and standard deviations across the four time points of the outcomes between study arms, followed by multilevel modeling on trajectories of the outcomes over the 12 months. Results: 211 participants consented to participate in this trial. The mean age of participants was 58.85 (+10.1) years, and a majority were White (60.2%), non-Hispanic (93.8%), married (56.3%), and female (59.2%). Mean A1c at baseline was 7.64% (+1.79) and the mean BMI was 33.51 (+7.25). We examined weight loss status vs. randomized group, where data with no weight change were eliminated, and we found a statistically significant difference with the LIVE group experiencing more weight loss than the WebControl group (P=.04). There were no statistically significant differences between groups in changes in physical activity and dietary outcomes, but each group showed an increase in physical activity. Both groups experienced a decrease in mean A1c, systolic and diastolic blood pressure, cholesterol, and triglycerides over the course of 12 months of study participation, including those participants whose baseline A1c was 8.6 or higher. Conclusions: This study confirmed that there were minor positive changes on metabolic controlglycemic targets in both groups over the 12-month study period, however, the majority of the participants began with optimal metabolic controlA1c levels. We did find clinically relevant metabolic changes in those who began with an A1c level >8.6% in both groups. This study provided a variety of resources to our participants in both study groups, and we conclude that a toolkit with a variety of services would be helpful to improving self-care in the future for persons with T2DM.

Long-term participant retention and engagement patterns in an app and wearable-based multinational remote digital depression study (2023)

NPJ digital medicine

Authors: Zhang, Yuezhou; Pratap, Abhishek; Folarin, Amos A.; Sun, Shaoxiong; Cummins, Nicholas; Matcham, Faith; Vairavan, Srinivasan; Dineley, Judith; Ranjan, Yatharth; Rashid, Zulqarnain; Conde, Pauline; Stewart, Callum; White, Katie M.; Oetzmann, Carolin; Ivan, Alina; Lamers, Femke; Siddi, Sara; Rambla, Carla Hernández; Simblett, Sara; Nica, Raluca; Mohr, David C.; Myin-Germeys, Inez; Wykes, Til; Haro, Josep Maria; Penninx, Brenda W. J. H.; Annas, Peter; Narayan, Vaibhav A.; Hotopf, Matthew; Dobson, Richard J. B.; RADAR-CNS consortium

Abstract

Recent growth in digital technologies has enabled the recruitment and monitoring of large and diverse populations in remote health studies. However, the generalizability of inference drawn from remotely collected health data could be severely impacted by uneven participant engagement and attrition over the course of the study. We report findings on long-term participant retention and engagement patterns in a large multinational observational digital study for depression containing active (surveys) and passive sensor data collected via Android smartphones, and Fitbit devices from 614 participants for up to 2 years. Majority of participants (67.6\%) continued to remain engaged in the study after 43 weeks. Unsupervised clustering of participants' study apps and Fitbit usage data showed 3 distinct engagement subgroups for each data stream. We found: (i) the least engaged group had the highest depression severity (4 PHQ8 points higher) across all data streams; (ii) the least engaged group (completed 4 bi-weekly surveys) took significantly longer to respond to survey notifications (3.8 h more) and were 5 years younger compared to the most engaged group (completed 20 bi-weekly surveys); and (iii) a considerable proportion (44.6\%) of the participants who stopped completing surveys after 8 weeks continued to share passive Fitbit data for significantly longer (average 42 weeks). Additionally, multivariate survival models showed participants' age, ownership and brand of smartphones, and recruitment sites to be associated with retention in the study. Together these findings could inform the design of future digital health studies to enable equitable and balanced data collection from diverse populations.

Machine Learning Approaches to Classify Self-Reported Rheumatoid Arthritis Health Scores Using Activity Tracker Data (2023)

JMIR formative research

Authors: Rao, Kaushal; Speier, William; Meng, Yiwen; Wang, Jinhan; Ramesh, Nidhi; Xie, Fenglong; Su, Yujie; Nowell, Benjamin; Curtis, Jeffrey; Arnold, Corey

Abstract

BACKGROUND: The increasing use of activity trackers in mobile health studies to passively collect physical data has shown promise to lessen participation burden to provide actively contributed patient reported outcome (PRO) information. Our goal was to develop machine learning models to classify patient-reported outcome (PRO) scores using Fitbit data from a cohort of patients with rheumatoid arthritis (RA). OBJECTIVE: The increasing use of activity trackers in mobile health studies to passively collect physical data has shown promise to lessen participation burden to provide actively contributed patient reported outcome (PRO) information. Our goal was to develop machine learning models to classify patient-reported outcome (PRO) scores using Fitbit data from a cohort of patients with rheumatoid arthritis (RA). METHODS: Two different models were built to classify PRO scores; a random forest (RF) Classifier model that treated each week of observations independently when making weekly predictions of PRO scores, and a hidden Markov model (HMM) that additionally took correlations between successive weeks into account. Analyses compared model evaluation metrics for: 1) a binary task of distinguishing a normal PRO score from a severe PRO score, and 2) a multiclass task of classifying a PRO score state for a given week. RESULTS: For both the binary and multiclass tasks, the HMM significantly (p {\textless} 0.05) outperformed the RF for most PRO scores, and the highest AUC, Pearson's Correlation coefficient, and Cohen's Kappa coefficient were 0.751, 0.458, and 0.450 respectively. CONCLUSIONS: While further validation of our results and evaluation in a real-world setting yet remains, this study demonstrates the ability of physical activity tracker data to classify health status over time in patients with RA and enables the possibility of scheduling preventive clinical interventions as needed. If patient outcomes can be monitored in real time, there is potential to improve clinical care for patients with other chronic conditions.

Measurement properties of device-based physical activity instruments in ambulatory adults with physical disabilities and/or chronic diseases: a scoping review (2023)

BMC sports science, medicine \& rehabilitation

Authors: Brandenbarg, Pim; Hoekstra, Femke; Barakou, Ioulia; Seves, Bregje L.; Hettinga, Florentina J.; Hoekstra, Trynke; van der Woude, Lucas H. V.; Dekker, Rienk; Krops, Leonie A.

Abstract

BACKGROUND: People with physical disabilities and/or chronic diseases tend to have an inactive lifestyle. Monitoring physical activity levels is important to provide insight on how much and what types of activities people with physical disabilities and/or chronic diseases engage in. This information can be used as input for interventions to promote a physically active lifestyle. Therefore, valid and reliable physical activity measurement instruments are needed. This scoping review aims 1) to provide a critical mapping of the existing literature and 2) directions for future research on measurement properties of device-based instruments assessing physical activity behavior in ambulant adults with physical disabilities and/or chronic diseases. METHODS: Four databases (MEDLINE, CINAHL, Web of Science, Embase) were systematically searched from 2015 to April 16th 2023 for articles investigating measurement properties of device-based instruments assessing physical activity in ambulatory adults with physical disabilities and/or chronic diseases. For the majority, screening and selection of eligible studies were done in duplicate. Extracted data were publication data, study data, study population, device, studied measurement properties and study outcome. Data were synthesized per device. RESULTS: One hundred three of 21566 Studies were included. 55 Consumer-grade and 23 research-grade devices were studied on measurement properties, using 14 different physical activity outcomes, in 23 different physical disabilities and/or chronic diseases. ActiGraph (n = 28) and Fitbit (n = 39) devices were most frequently studied. Steps (n = 68) was the most common used physical activity outcome. 97 studies determined validity, 11 studies reliability and 6 studies responsiveness. CONCLUSION: This scoping review shows a large variability in research on measurement properties of device-based instruments in ambulatory adults with physical disabilities and/or chronic diseases. The variability highlights a need for standardization of and consensus on research in this field. The review provides directions for future research.

Menstruation-related symptoms are associated with physical activity and midpoint of sleep: a pilot study (2023)

Frontiers in Global Women's Health

Authors: Masuda, Hazuki; Okada, Shima

Abstract

Introduction: Menstruation-related symptoms (MRSs) significantly impact women's health and contribute to economic burdens worldwide. Current interventions, primarily pharmacological ones, have limitations and side effects that underscore the need for alternative management strategies. This study explores the association between MRSs and lifestyle factors, specifically physical activity and sleep timing across menstrual cycle phases, to inform non-pharmacological intervention development. Methods: Fourteen female students from Ritsumeikan University, Japan, with regular menstrual cycles (25-38 days), not on hormonal treatment or engaged in shift work, participated in this observational study. Using a Fitbit Inspire 2, total daily energy expenditure (TDEE) and sleep timing were monitored over a complete cycle. Menstrual cycle phases were defined based on ovulation day, predicted using home luteinizing hormone tests. Participants completed daily electronic questionnaires rating MRSs using a modified menstrual distress questionnaire. Data were analyzed using a generalized linear mixed model with a gamma distribution and logarithmic link function, examining the relationship of TDEE and the midpoint of sleep time (MS time) with MRS severity. Results and discussion: The following observations were noted: first, MRS severity, except for behavioral change symptoms, significantly increased during the menstrual and luteal phases compared to the follicular phase. Second, delayed MS time was associated with reduced pain, concentration symptoms, water retention, and negative affect during the menstrual phase and reduced negative affect during the luteal phase. Finally, an increase in TDEE was associated with reduced concentration symptoms, autonomic reaction symptoms, and negative affect during the menstrual and luteal phases and reduced water retention only during the luteal phase. This study provides insights into the relationship between MRSs and TDEE/MS time, suggesting potential non-therapeutic approaches for symptom management, though further research is needed to substantiate these findings for practical applications. Keywords: generalized linear mixed model; menstrual cycle; menstrual cycle phase; menstruation-related symptoms; physical activity; sleep; wearable device.

mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED): rationale and study protocol for a pragmatic randomised controlled trial (2023)

BMC public health

Authors: Vetrovsky, Tomas; Kral, Norbert; Pfeiferova, Marketa; Kuhnova, Jitka; Novak, Jan; Wahlich, Charlotte; Jaklova, Andrea; Jurkova, Katerina; Janek, Michael; Omcirk, Dan; Capek, Vaclav; Maes, Iris; Steffl, Michal; Ussher, Michael; Tufano, James J.; Elavsky, Steriani; Van Dyck, Delfien; Cimler, Richard; Yates, Tom; Harris, Tess; Seifert, Bohumil

Abstract

Background: The growing number of patients with type 2 diabetes and prediabetes is a major public health concern. Physical activity is a cornerstone of diabetes management and may prevent its onset in prediabetes patients. Despite this, many patients with (pre)diabetes remain physically inactive. Primary care physicians are well-situated to deliver interventions to increase their patients' physical activity levels. However, effective and sustainable physical activity interventions for (pre)diabetes patients that can be translated into routine primary care are lacking. Methods: We describe the rationale and protocol for a 12-month pragmatic, multicentre, randomised, controlled trial assessing the effectiveness of an mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED). Twenty-one general practices will recruit 340 patients with (pre)diabetes during routine health check-ups. Patients allocated to the active control arm will receive a Fitbit activity tracker to self-monitor their daily steps and try to achieve the recommended step goal. Patients allocated to the intervention arm will additionally receive the mHealth intervention, including the delivery of several text messages per week, with some of them delivered just in time, based on data continuously collected by the Fitbit tracker. The trial consists of two phases, each lasting six months: the lead-in phase, when the mHealth intervention will be supported with human phone counselling, and the maintenance phase, when the intervention will be fully automated. The primary outcome, average ambulatory activity (steps/day) measured by a wrist-worn accelerometer, will be assessed at the end of the maintenance phase at 12 months. Discussion: The trial has several strengths, such as the choice of active control to isolate the net effect of the intervention beyond simple self-monitoring with an activity tracker, broad eligibility criteria allowing for the inclusion of patients without a smartphone, procedures to minimise selection bias, and involvement of a relatively large number of general practices. These design choices contribute to the trial's pragmatic character and ensure that the intervention, if effective, can be translated into routine primary care practice, allowing important public health benefits.

Minimally invasive versus open pancreatoduodenectomy for pancreatic and peri-ampullary neoplasm (DIPLOMA-2): study protocol for an international multicenter patient-blinded randomized controlled trial (2023)

Trials

Authors: de Graaf, Nine; Emmen, Anouk M. L. H.; Ramera, Marco; Björnsson, Bergthor; Boggi, Ugo; Bruna, Caro L.; Busch, Olivier R.; Daams, Freek; Ferrari, Giovanni; Festen, Sebastiaan; van Hilst, Jony; D'Hondt, Mathieu; Ielpo, Benedetto; Keck, Tobias; Khatkov, Igor E.; Koerkamp, Bas Groot; Lips, Daan J.; Luyer, Misha D. P.; Mieog, J. Sven D.; Morelli, Luca; Molenaar, I. Quintus; van Santvoort, Hjalmar C.; Sprangers, Mirjam A. G.; Ferrari, Clarissa; Berkhof, Johannes; Maisonneuve, Patrick; Abu Hilal, Mohammad; Besselink, Marc G.; European Consortium on Minimally Invasive Pancreatic Surgery (E-MIPS)

Abstract

Background: Minimally invasive pancreatoduodenectomy (MIPD) aims to reduce the negative impact of surgery as compared to open pancreatoduodenectomy (OPD) and is increasingly becoming part of clinical practice for selected patients worldwide. However, the safety of MIPD remains a topic of debate and the potential shorter time to functional recovery needs to be confirmed. To guide safe implementation of MIPD, large-scale international randomized trials comparing MIPD and OPD in experienced high-volume centers are needed. We hypothesize that MIPD is non-inferior in terms of overall complications, but superior regarding time to functional recovery, as compared to OPD. Methods/design: The DIPLOMA-2 trial is an international randomized controlled, patient-blinded, non-inferiority trial performed in 14 high-volume pancreatic centers in Europe with a minimum annual volume of 30 MIPD and 30 OPD. A total of 288 patients with an indication for elective pancreatoduodenectomy for pre-malignant and malignant disease, eligible for both open and minimally invasive approach, are randomly allocated for MIPD or OPD in a 2:1 ratio. Centers perform either laparoscopic or robot-assisted MIPD based on their surgical expertise. The primary outcome is the Comprehensive Complication Index (CCI®), measuring all complications graded according to the Clavien-Dindo classification up to 90 days after surgery. The sample size is calculated with the following assumptions: 2.5% one-sided significance level (α), 80% power (1-β), expected difference of the mean CCI® score of 0 points between MIPD and OPD, and a non-inferiority margin of 7.5 points. The main secondary outcome is time to functional recovery, which will be analyzed for superiority. Other secondary outcomes include post-operative 90-day Fitbit™ measured activity, operative outcomes (e.g., blood loss, operative time, conversion to open surgery, surgeon-reported outcomes), oncological findings in case of malignancy (e.g., R0-resection rate, time to adjuvant treatment, survival), postoperative outcomes (e.g., clinically relevant complications), healthcare resource utilization (length of stay, readmissions, intensive care stay), quality of life, and costs. Postoperative follow-up is up to 36 months. Discussion: The DIPLOMA-2 trial aims to establish the safety of MIPD as the new standard of care for this selected patient population undergoing pancreatoduodenectomy in high-volume centers, ultimately aiming for superior patient recovery. Trial registration: ISRCTN27483786. Registered on August 2, 2023.

Minute level smartphone derived exposure to greenness and consumer wearable derived physical activity in a cohort of US women (2023)

Environmental Research

Authors: Wilt, Grete E.; Roscoe, Charlotte J.; Hu, Cindy R.; Mehta, Unnati V.; Coull, Brent A.; Hart, Jaime E.; Gortmaker, Steven; Laden, Francine; James, Peter

Abstract

BACKGROUND: Inconsistent results have been found in the literature on associations of greenness, or vegetation quantity, and physical activity. However, few studies have assessed associations between mobility-based greenness and physical activity from mobile health data from smartphone and wearable devices with fine spatial and temporal resolution. METHODS: We assessed mobility-based greenness exposure and wearable accelerometer data from participants in the US-based prospective Nurses' Health Study 3 cohort Mobile Health (mHealth) Substudy (2018-2020). We recruited 500 female participants with instructions to wear devices over four 7-day sampling periods equally spaced throughout the year. After restriction criteria there were 337 participants (mean age 36 years) with n = 639,364 unique observations. Normalized Difference Vegetation Index (NDVI) data were derived from 30 m x 30 m Landsat-8 imagery and spatially joined to GPS points recorded every 10 min. Fitbit proprietary algorithms provided physical activity summarized as mean number of steps per minute, which we averaged during the 10-min period following a GPS-based greenness exposure assessment. We utilized Generalized Additive Mixed Models to examine associations (every 10 min) between greenness and physical activity adjusting for neighborhood and individual socioeconomic status, Census region, season, neighborhood walkability, daily mean temperature and precipitation. We assessed effect modification through stratification and interaction models and conducted sensitivity analyses. RESULTS: Mean 10-min step count averaged 7.0 steps (SD 14.9) and greenness (NDVI) averaged 0.3 (SD 0.2). Contrary to our hypotheses, higher greenness exposure was associated non-linearly with lower mean steps per minute after adjusting for confounders. We observed statistically significant effect modification by Census region and season. DISCUSSION: We utilized objective physical activity data at fine temporal and spatial scales to present novel estimates of the association between mobility-based greenness and step count. We found higher levels of greenness were inversely associated with steps per minute.

Moderate and increased physical activity is not detrimental to live birth rates among women with unexplained infertility and obesity (2023)

F\&S Reports

Authors: Vitek, Wendy S.; Sun, Fangbai; Cardozo, Eden; Hoeger, Kathleen M.; Hansen, Karl R.; Santoro, Nanette; Zhang, Heping; Legro, Richard S.

Abstract

OBJECTIVE: To determine if moderate physical activity is associated with live birth rates in women with unexplained infertility and obesity. DESIGN: Secondary analysis of the Improving Reproductive Fitness through Pretreatment with Lifestyle Modification in Obese Women with Unexplained Infertility trial. SETTING: US fertility centers, 2015-2019. PATIENTS: A total of 379 women participated in Improving Reproductive Fitness through Pretreatment with Lifestyle Modification in Obese Women with Unexplained Infertility trial, a lifestyle modification program with increased physical activity (phase I, 16 weeks) and up to three cycles of clomiphene citrate treatment and intrauterine insemination (phase II). INTERVENTIONS: Participants were instructed to add 500 steps/day weekly until a maximum of 10,000 steps/day was reached and maintained. Participants were stratified as active (top third, N = 125) and less active (lower third, N = 125) on the basis of the average number of steps per day recorded using a FitBit activity tracker. MAIN OUTCOME MEASURES: Live birth rate. RESULTS: Active participants were more physically active at the time of enrollment than less active participants (average baseline steps per day, 8,708 [7,079-10,000] vs. 4,695 [3,844-5,811]; P ≤ 0.001) and were more likely to reach 10,000 steps/day than less active participants (average steps per day, 10,526 [9,481-11,810] vs. 6,442 [4,644-7,747]; P ≤ 0.001), although both groups increased their average steps per day by a similar amount (1,818 vs.1,747; P = 0.57). There was no difference in live birth rates (24/125 [19.2\%] vs. 25/125 [20\%]; P = 0.87) between active and less active participants nor were there differences in clinical pregnancy rates (P = 0.45) or miscarriage rates (P = 0.49) between the two groups. CONCLUSIONS: Active participants were more likely to achieve the physical activity goal, although this was not associated with benefit or harm with respect to live birth. CLINICAL TRIAL REGISTRATION NUMBER: ClinicalTrials.gov (NCT02432209), first posted: May 4, 2015.

Motivational Message Framing Effects on Physical Activity Dynamics in a Digital Messaging Intervention: Secondary Analysis (2023)

JMIR formative research

Authors: Lee, Alexandra M.; Hojjatinia, Sahar; Courtney, Jimikaye B.; Brunke-Reese, Deborah; Hojjatinia, Sarah; Lagoa, Constantino M.; Conroy, David E.

Abstract

Background: Digital smartphone messaging can be used to promote physical activity to large populations with limited cost. It is not clear which psychological constructs should be targeted by digital messages to promote physical activity. This gap presents a challenge for developing optimal content for digital messaging interventions. Objective: The aim of this study is to compare affectively framed and social cognitively framed messages on subsequent changes in physical activity using dynamical modeling techniques. Methods: We conducted a secondary analysis of data collected from a digital messaging intervention in insufficiently active young adults (18-29 years) recruited between April 2019 and July 2020 who wore a Fitbit smartwatch for 6 months. Participants received 0 to 6 messages at random per day across the intervention period. Messages were drawn from 3 content libraries: affectively framed, social cognitively framed, or inspirational quotes. Person-specific dynamical models were identified, and model features of impulse response and cumulative step response were extracted for comparison. Two-way repeated-measures ANOVAs evaluated the main effects and interaction of message type and day type on model features. This early-phase work with novel dynamic features may have been underpowered to detect differences between message types so results were interpreted descriptively. Results: Messages (n=20,689) were paired with valid physical activity monitoring data from 45 participants for analysis. Received messages were distributed as 40% affective (8299/20,689 messages), 39% social-cognitive (8187/20,689 messages), and 20% inspirational quotes (4219/20,689 messages). There were no statistically significant main effects for message type when evaluating the steady state of step responses. Participants demonstrated heterogeneity in intervention response: some had their strongest responses to affectively framed messages, some had their strongest responses to social cognitively framed messages, and some had their strongest responses to the inspirational quote messages. Conclusions: No single type of digital message content universally promotes physical activity. Future work should evaluate the effects of multiple message types so that content can be continuously tuned based on person-specific responses to each message type.

Nonlinear, Multicomponent Physical Exercise with Heart Rate Variability-Guided Prescription in Women with Breast Cancer during Treatment: Feasibility and Preliminary Results (ATOPE Study) (2023)

Physical Therapy

Authors: González-Santos, Á.; Lopez-Garzon, M.; Gil-Gutiérrez, R.; Salinas-Asensio, M. M.; Postigo-Martin, P.; Cantarero-Villanueva, I.

Abstract

Objective: The purpose of this study was to examine the feasibility, safety, adherence, and preliminary efficacy of the ATOPE program during radiotherapy (RT) or chemotherapy (CT) for women with breast cancer. Methods: This single-blind, pretest-posttest feasibility study included 38 women with breast cancer at the beginning of their treatment. The ATOPE program consisted of 12 to 18 sessions of a multimodal physical exercise program, prescribed based on daily heart rate variability (HRV) and clinimetric assessments using the ATOPE+ mHealth system. Overall health was assessed with quality of life, autonomous balance, and body composition, whereas health-related fitness (HRF) was measured through functional capacity, physical activity levels, and upper and lower limb strength. Results: The rates of recruitment, retention, and adherence were 52.35%, 73.68%, and 84.37%, respectively, and the satisfaction rating was 9.2 out of a possible 10 points. The perceived health status change score was 3.83 points, scored on a - 5 to 5 point scale. No adverse effects were found. Compliance results showed that the ATOPE+ mHealth system was used on 73.38% of the days, and the Fitbit bracelet (Google, Mountain View, CA, USA) was used on 84.91% of the days. Women stayed physically active 55% of days. Regarding preliminary results, for overall health, the percentage of body fat in the RT group decreased by 1.93%, whereas it increased by 5.03% in the CT group. Lower limb strength increased in the RT group, specifically knee extensor isometric strength (6.07%), isokinetic knee flexors 180°/s (1.53%) and isokinetic knee extensors 300°/s (4.53%), in contrast with the reductions found in the CT group (11.07%, 18.67%, and 14.89%, respectively). Conclusions: The ATOPE program, through nonlinear prescription based on daily monitoring with the ATOPE+ mHealth system, is feasible and safe for application during breast cancer treatment. The results suggest that overall health can be maintained or even improved regarding most variables. Impact: This study focused on the feasibility, safety, and completion of a physical therapist-led program at early diagnosis for adults with breast cancer. The multimodal, supervised, tailored, nonlinear physical exercise program is feasible and safe, showed a good completion rate, and was able to prevent the quality-of-life deficits that are often triggered by systemic breast cancer treatment. This study highlights the importance of daily morning assessments using the ATOPE+ mHealth system in patients with breast cancer to prescribe nonlinear physical exercise.

Open-Source, Step-Counting Algorithm for Smartphone Data Collected in Clinical and Nonclinical Settings: Algorithm Development and Validation Study (2023)

JMIR cancer

Authors: Straczkiewicz, Marcin; Keating, Nancy L.; Thompson, Embree; Matulonis, Ursula A.; Campos, Susana M.; Wright, Alexi A.; Onnela, Jukka-Pekka

Abstract

Background: Step counts are increasingly used in public health and clinical research to assess well-being, lifestyle, and health status. However, estimating step counts using commercial activity trackers has several limitations, including a lack of reproducibility, generalizability, and scalability. Smartphones are a potentially promising alternative, but their step-counting algorithms require robust validation that accounts for temporal sensor body location, individual gait characteristics, and heterogeneous health states. Objective: Our goal was to evaluate an open-source, step-counting method for smartphones under various measurement conditions against step counts estimated from data collected simultaneously from different body locations ("cross-body" validation), manually ascertained ground truth ("visually assessed" validation), and step counts from a commercial activity tracker (Fitbit Charge 2) in patients with advanced cancer ("commercial wearable" validation). Methods: We used 8 independent data sets collected in controlled, semicontrolled, and free-living environments with different devices (primarily Android smartphones and wearable accelerometers) carried at typical body locations. A total of 5 data sets (n=103) were used for cross-body validation, 2 data sets (n=107) for visually assessed validation, and 1 data set (n=45) was used for commercial wearable validation. In each scenario, step counts were estimated using a previously published step-counting method for smartphones that uses raw subsecond-level accelerometer data. We calculated the mean bias and limits of agreement (LoA) between step count estimates and validation criteria using Bland-Altman analysis. Results: In the cross-body validation data sets, participants performed 751.7 (SD 581.2) steps, and the mean bias was -7.2 (LoA -47.6, 33.3) steps, or -0.5%. In the visually assessed validation data sets, the ground truth step count was 367.4 (SD 359.4) steps, while the mean bias was -0.4 (LoA -75.2, 74.3) steps, or 0.1%. In the commercial wearable validation data set, Fitbit devices indicated mean step counts of 1931.2 (SD 2338.4), while the calculated bias was equal to -67.1 (LoA -603.8, 469.7) steps, or a difference of 3.4%. Conclusions: This study demonstrates that our open-source, step-counting method for smartphone data provides reliable step counts across sensor locations, measurement scenarios, and populations, including healthy adults and patients with cancer. Keywords: accelerometer; cancer; open-source; smartphone; step count; validation; wearable.

Opportune warning of COVID-19 in a Mexican health care worker cohort: Discrete beta distribution entropy of smartwatch physiological records (2023)

Biomedical Signal Processing and Control

Authors: Aguado-García, Alejandro; Arroyo-Valerio, América; Escobedo, Galileo; Bueno-Hernández, Nallely; Olguín-Rodríguez, P. V.; Müller, Markus F.; Carrillo-Ruiz, José Damián; Martínez-Mekler, Gustavo

Abstract

We present a statistical study of heart rate, step cadence, and sleep stage registers of health care workers in the Hospital General de México "Dr. Eduardo Liceaga" (HGM), monitored continuously and non-invasively during the COVID-19 contingency from May to October 2020, using the Fitbit Charge 3® Smartwatch device. The HGM-COVID cohort consisted of 115 participants assigned to areas of COVID-19 exposure. We introduce a novel biomarker for an opportune signal for the likelihood of SARS-CoV-2 infection based on the Shannon Entropy of the Discrete Generalized Beta Distribution fit of rank ordered smartwatch registers. Our statistical test indicated infection for 94% of patients confirmed by positive polymer chain reaction (PCR+) test, 47% before the test, and 47% in coincidence. These results required innovative data preprocessing for the definition of a new biomarker index. The statistical method parameters are data-driven, confidence estimates were calibrated based on sensitivity tests using appropriately derived surrogate data as a benchmark. Our surrogate tests can also provide a benchmark for comparing results from other anomaly detection methods (ADMs). Biomarker comparison of the negative Immunoglobulin G Antibody (IgG-) subgroup with the PCR+ subgroup showed a statistically significant difference (p < 0.01, effect size = 1.44). The distribution of the uninfected population had a lower median and less dispersion than the PCR+ population. A retrospective study of our results confirmed that the biomarker index provides an early warning of the likelihood of COVID-19, even several days before the onset of symptoms or the PCR+ test request. The method can be calibrated for the analysis of different SARS-CoV-2 strains, the effect of vaccination, and previous infections. Furthermore, our biomarker screening could be implemented to provide general health profiles for other population sectors based on physiological signals from smartwatch wearable devices.

Pain self-management plus activity tracking and nurse-led support in adults with chronic low back pain: feasibility and acceptability of the problem-solving pain to enhance living well (PROPEL) intervention (2023)

BMC nursing

Authors: Xu, Wanli; Zhang, Yiming; Wang, Zequan; Dorsey, Susan G.; Starkweather, Angela; Kim, Kyounghae

Abstract

Background: Chronic low back pain can lead to individual suffering, high medical expenditures, and impaired social well-being. Although the role of physical activity in pain management is well established, the underlying mechanisms of biological and clinical outcomes are unknown. This study aimed to assess the feasibility and acceptability of a pain self-management intervention, Problem-Solving Pain to Enhance Living Well, which employs wearable activity tracking technology and nurse consultations for people with chronic low back pain. Methods: This one-arm longitudinal study recruited 40 adults aged 18-60 years with chronic low back pain. Over 12 weeks, participants watched 10 short video modules, wore activity trackers, and participated in nurse consultations every 2 weeks. At baseline and the 12-week follow-up, they completed study questionnaires, quantitative sensory testing, and blood sample collection. Results: Forty participants were recruited, and their mean age was 29.8. Thirty-two participants completed the survey questionnaire, quantitative sensory testing, Fitbit activity tracker, and bi-weekly nurse consultation, and 25 completed the evaluation of biological markers. The overall satisfaction with the Problem-Solving Pain to Enhance Living Well video modules, nurse consultations, and Fitbit in pain management was rated as excellent. No adverse events were reported. Between the baseline and 12-week follow-up, there was a significant decrease in pain intensity and interference and an increase in the warm detection threshold at the pain site. Conclusions: Despite concerns about the participant burden due to multidimensional assessment and intensive education, the feasibility of the Problem-Solving Pain to Enhance Living Well intervention was favorable. Technology-based self-management interventions can offer personalized strategies by integrating pain phenotypes, genetic markers, and physical activity types affecting pain conditions. Trial registration: This pilot study was registered with ClinicalTrials.gov [NCT03637998, August 20, 2018]. The first participant was enrolled on September 21, 2018.

Patient Engagement and Provider Effectiveness of a Novel Sleep Telehealth Platform and Remote Monitoring Assessment in the US Military: Pilot Study Providing Evidence-Based Sleep Treatment Recommendations (2023)

JMIR formative research

Authors: Wickwire, Emerson M.; Collen, Jacob; Capaldi, Vincent F.; Williams, Scott G.; Assefa, Samson Z.; Adornetti, Julianna P.; Huang, Kathleen; Venezia, Janet M.; Jones, Rachell L.; Johnston, Christine W.; Thomas, Connie; Thomas, Mary Ann; Mounts, Charles; Drake, Christopher L.; Businelle, Michael S.; Grandner, Michael A.; Manber, Rachel; Albrecht, Jennifer S.

Abstract

Background: Sleep problems are common and costly in the US military. Yet, within the military health system, there is a gross shortage of trained specialist providers to address sleep problems. As a result, demand for sleep medicine care far exceeds the available supply. Telehealth including telemedicine, mobile health, and wearables represents promising approaches to increase access to high-quality and cost-effective care. Objective: The purpose of this study was to evaluate patient engagement and provider perceived effectiveness of a novel sleep telehealth platform and remote monitoring assessment in the US military. The platform includes a desktop web portal, native mobile app, and integrated wearable sensors (ie, a commercial off-the-shelf sleep tracker [Fitbit]). The goal of the remote monitoring assessment was to provide evidence-based sleep treatment recommendations to patients and providers. Methods: Patients with sleep problems were recruited from the Internal Medicine clinic at Walter Reed National Military Medical Center. Patients completed intensive remote monitoring assessments over 10 days (including a baseline intake questionnaire, daily sleep diaries, and 2 daily symptom surveys), and wore a Fitbit sleep tracker. Following the remote monitoring period, patients received assessment results and personalized sleep education in the mobile app. In parallel, providers received a provisional patient assessment report in an editable electronic document format. Patient engagement was assessed via behavioral adherence metrics that were determined a priori. Patients also completed a brief survey regarding ease of completion. Provider effectiveness was assessed via an anonymous survey. Results: In total, 35 patients with sleep problems participated in the study. There were no dropouts. Results indicated a high level of engagement with the sleep telehealth platform, with all participants having completed the baseline remote assessment, reviewed their personalized sleep assessment report, and completed the satisfaction survey. Patients completed 95.1% of sleep diaries and 95.3% of symptom surveys over 10 days. Patients reported high levels of satisfaction with most aspects of the remote monitoring assessment. In total, 24 primary care providers also participated and completed the anonymous survey. The results indicate high levels of perceived effectiveness and identified important potential benefits from adopting a sleep telehealth approach throughout the US military health care system. Conclusions: Military patients with sleep problems and military primary care providers demonstrated high levels of engagement and satisfaction with a novel sleep telehealth platform and remote monitoring assessment. Sleep telehealth approaches represent a potential pathway to increase access to evidence-based sleep medicine care in the US military. Further evaluation is warranted. Keywords: application; behavioral; care; effective care; effectiveness; insomnia; monitoring; obstructive sleep apnea; patient engagement; remote monitoring; sleep; sleep disorders; telehealth; wearables.

Piloting HealthScore: Feasibility and acceptability of a clinically integrated health coaching program for people living with cancer (2023)

Cancer Medicine

Authors: Wood, William A.; Bailey, Carly; Castrogivanni, Brianna; Mehedint, Diana; Bryant, Ashley Leak; Lavin, Kyle; Tan, Xianming; Richardson, Jaime; Qian, Yiqing; Tan, Kelly R.; Kent, Erin E.

Abstract

BACKGROUND: Cancer supportive care interventions often have limited generalizability, goal misalignment, and high costs. We developed and piloted a health coaching intervention, UNC HealthScore, in patients undergoing cancer treatment (ClinicalTrials.gov identifier NCT04923997). We present feasibility, acceptability, and preliminary outcome data. METHODS: HealthScore is a six-month, theory-based, multicomponent intervention delivered through participant-driven coaching sessions. For the pilot study, participants were provided a Fitbit, responded to weekly symptom and physical function digital surveys, and met with a health coach weekly to develop and monitor goals. Coaching notes were discussed in weekly interdisciplinary team meetings and provided back to the treating oncology team. Symptom alerts were monitored and triaged through a study resource nurse to relevant supportive care services. Feasibility was determined based on intervention enrollment and completion. Acceptability was based on satisfaction with coaching and Fitbit-wearing and was informed by semistructured exit interviews. Outcomes evaluated for signs of improvement included several PROMIS (Patient-Reported Outcomes Measurement Information System) measures, including the primary intervention target, physical function. RESULTS: From May 2020 to March 2022, 50 participants completed the single-arm pilot. Feasibility was high: 66\% enrolled and 71\% completed the full intervention. Participants reported an average of 4.8 and 4.7 (out of 5) on the acceptability of coaching calls and using the Fitbit, respectively. Physical function scores rose 3.1 points (SE = 1.1) from baseline to 3 months, and 4.3 (SE = 1.0) from baseline to 6 months, above established minimal clinically important difference (MCID). Improvements above MCID were also evident in anxiety and depression, and smaller improvements were demonstrated for emotional support, social isolation, cognitive function, symptom burden, and self-efficacy. DISCUSSION: HealthScore shows feasibility, acceptability, and promising preliminary outcomes. Randomized studies are underway to determine the efficacy of preserving physical function in patients with advanced cancer.

Promoting participation in physical activity through Snacktivity: A qualitative mixed methods study (2023)

PloS One

Authors: Krouwel, Matthew; Greenfield, Sheila M.; Chalkley, Anna; Sanders, James P.; Parretti, Helen M.; Gokal, Kajal; Jolly, Kate; Skrybant, Magdalena; Biddle, Stuart J. H.; Greaves, Colin; Maddison, Ralph; Mutrie, Nanette; Ives, Natalie; Esliger, Dale W.; Sherar, Lauren; Edwardson, Charlotte L.; Yates, Tom; Frew, Emma; Tearne, Sarah; Daley, Amanda J.

Abstract

BACKGROUND: Public health guidance acknowledges the benefits of physical activity of any duration. We have proposed a whole-day approach to promoting physical activity called Snacktivity™, which encourages frequent 2-5 minute 'activity snacks' of moderate-to-vigorous intensity. METHODS: Using repeated semi-structured interviews and a think aloud protocol, this study aimed to understand participants' experiences of integrating Snacktivity™ into daily life, to provide insights to refine the delivery of Snacktivity™ interventions. Physically inactive adults recruited via primary care and a community health service engaged with an intervention to encourage Snacktivity™ over three weeks, which included using a Fitbit and linked mobile phone app (SnackApp). Participants took part in semi-structured interviews on two occasions during the intervention, with a sub-group participating in a think aloud study. Three study data sets were generated and independently explored using inductive thematic analysis, with findings combined into a single set of themes. RESULTS: Eleven adults participated in the interview study who were interviewed twice (total interviews completed n = 21, 1 participant declined the second interview), of whom six completed the think aloud study (total voice recordings n = 103). Three main themes emerged from the combined data; lived experience of participating in Snacktivity™, motivation for Snacktivity™ and experiences with the Snacktivity™ technology. Participants undertook a variety of activity snacks, utilising their environment, which they believed improved their psychological wellbeing. Participants were enthusiastic about Snacktivity™, with some stating that activity snacks were more accessible than traditional exercise, but perceived they were often prevented from doing so in the presence of others. Participants were mostly enthusiastic about using the Snacktivity™ technology. CONCLUSION: Participants were able to incorporate Snacktivity™ into their lives, particularly at home, and found this approach acceptable. Participants felt they experienced health benefits from Snacktivity™ although barriers to participation were reported. This study offers insights for translating guidance into practice and supporting people to become more physically active.

Protocol for randomized personalized trial for stress management compared to standard of care (2023)

Frontiers in Psychology

Authors: Goodwin, Ashley M.; Miller, Danielle; D'Angelo, Stefani; Perrin, Alexandra; Wiener, Ruby; Greene, Brittney; Romain, Anne-Marie N.; Arader, Lindsay; Chandereng, Thevaa; Kuen Cheung, Ying; Davidson, Karina W.; Butler, Mark

Abstract

Stress is a significant public health burden in the United States, with most Americans reporting unhealthy levels of stress. Stress management techniques include various evidence-based treatments shown to be effective but with heterogeneous treatment responses, indicating a lack of uniform benefits for all individuals. Designed to assess a participant's response to a specific intervention, personalized (N-of-1) trials provide guidance for which treatment (s) work (s) best for the individual. Prior studies examining the effects of mindfulness meditation, yoga, and walking for stress reduction found all three interventions to be associated with significant reductions in self-reported measures of stress. Delivering these treatments using a personalized trial approach has the potential to assist clinicians in identifying the best stress management techniques for individuals with persistently high stress while fostering treatment decisions that consider their personal condition/barriers. This trial will evaluate a personalized approach compared to standard of care for three interventions (guided mindfulness meditation; guided yoga; and guided brisk walking) to manage perceived stress. Participants will respond to daily surveys and wear a Fitbit device for 18 weeks. After a 2-week baseline period, participants in the personalized trial groups will receive 12 weeks of interventions in randomized order, while participants in the standard-of-care group will have access to all interventions for self-directed stress management. After intervention, all participants will undergo 2 weeks of observation, followed by two additional weeks of the stress management intervention of their choosing while continuing outcome measurement. At study completion, all participants will be sent a satisfaction survey. The primary analysis will compare perceived stress levels between the personalized and standard of care arms. The results of this trial will provide further support for the use of personalized designs for managing stress. Clinical Trial Registration: clinicaltrials.gov, NCT05408832. Protocol version: 9/14/2022, 21-0968-MRB. Keywords: N-of-1; mindfulness; personalized trials; physical activity; stress management techniques; yoga.

Real-time Assessment of the Bidirectional Relationship Between Affective States and Glucose: Protocol for a 14-Day Observational Study (2023)

JMIR research protocols

Authors: Rethorst, Chad D.; Githinji, Phrashiah; Seguin-Fowler, Rebecca A.; MacMillan Uribe, Alexandra L.; Szeszulski, Jacob; Liao, Yue

Abstract

Background: Glucose variability increases cardiometabolic disease risk. While many factors can influence glucose levels, postprandial glucose response is the primary driver of glucose variability. Furthermore, affect may directly and indirectly impact glucose variability through its effect on eating behavior. Continuous glucose monitors (CGMs) facilitate the real-time evaluation of blood glucose, and ecological momentary assessment (EMA) can be used to assess affect in real time. Together, data collected from these sources provide the opportunity to further understand the role of affect in glucose levels. Objective: This paper presents the protocol for a study that aims to (1) evaluate the feasibility and acceptability of using CGMs along with EMA in nondiabetic populations and (2) examine the bidirectional relationship between affect and glucose in nondiabetic adults with overweight or obesity using a CGM and EMA. Methods: Eligibility criteria for the study include participants (1) aged 18 to 65 years old, (2) with a BMI of ≥25 kg/m2, (3) who are able to read and write in English, and (4) who own a smartphone. Individuals will be excluded if they (1) have type 1 or 2 diabetes or have any other condition that requires glucose monitoring, (2) are pregnant, (3) use any medications that have the potential to alter blood glucose levels or interfere with the glucose sensing process, or (4) have a diagnosed gastrointestinal condition or eating disorder. In a 14-day observational study, participants will wear a FreeStyle Libre Pro CGM sensor (Abbott) and will receive mobile phone-based EMA prompts 6 times per day (randomly within six 2-hour windows between 8 AM and 8 PM) to assess positive and negative affect. Participants will also wear a Fitbit Inspire 2 (Fitbit) to continuously monitor physical activity and sleep, which will be included as covariates in the analysis. Multilevel linear regression models will be used to evaluate the acute relationship between glucose level and affect. Results: Recruitment started in October 2022 and is expected to be completed in March 2023. We will aim to recruit 100 participants. As of December 12, 2022, a total of 39 participants have been enrolled. Conclusions: The results of this study will further elucidate the role of affect in glucose variability. By identifying affective states that may lead to glucose excursions, our findings could inform just-in-time behavioral interventions by indicating opportunities for intervention delivery.

Selection of and Response to Physical Activity-Based Social Comparisons in a Digital Environment: Series of Daily Assessment Studies (2023)

JMIR human factors

Authors: Arigo, Danielle; Gray, Robert C.; Dallal, Diane H.; Villareale, Jennifer; Zhu, Jichen

Abstract

BACKGROUND: Innovative approaches are needed to understand barriers to and facilitators of physical activity among insufficiently active adults. Although social comparison processes (ie, self-evaluations relative to others) are often used to motivate physical activity in digital environments, user preferences and responses to comparison information are poorly understood. OBJECTIVE: We used an iterative approach to better understand users' selection of comparison targets, how they interacted with their selected targets, and how they responded to these targets. METHODS: Across 3 studies, different samples of insufficiently active college students used the Fitbit system (Fitbit LLC) to track their steps per day as well as a separate, adaptive web platform each day for 7 to 9 days (N=112). The adaptive platform was designed with different layouts for each study; each allowed participants to select their preferred comparison target from various sets of options, view the desired amount of information about their selected target, and rate their physical activity motivation before and after viewing information about their selected target. Targets were presented as achieving physical activity at various levels below and above their own, which were accessed via the Fitbit system each day. We examined the types of comparison target selections, time spent viewing and number of elements viewed for each type of target, and day-level associations between comparison selections and physical activity outcomes (motivation and behavior). RESULTS: Study 1 (n=5) demonstrated that the new web platform could be used as intended and that participants' interactions with the platform (ie, the type of target selected, the time spent viewing the selected target's profile, and the number of profile elements viewed) varied across the days. Studies 2 (n=53) and 3 (n=54) replicated these findings; in both studies, age was positively associated with time spent viewing the selected target's profile and the number of profile elements viewed. Across all studies, upward targets (who had more steps per day than the participant) were selected more often than downward targets (who had fewer steps per day than the participant), although only a subset of either type of target selection was associated with benefits for physical activity motivation or behavior. CONCLUSIONS: Capturing physical activity-based social comparison preferences is feasible in an adaptive digital environment, and day-to-day differences in preferences for social comparison targets are associated with day-to-day changes in physical activity motivation and behavior. Findings show that participants only sometimes focus on the comparison opportunities that support their physical activity motivation or behavior, which helps explain previous, equivocal findings regarding the benefits of physical activity-based comparisons. Additional investigation of day-level determinants of comparison selections and responses is needed to fully understand how best to harness comparison processes in digital tools to promote physical activity.

Social epidemiology of Fitbit daily steps in early adolescence (2023)

Pediatric Research

Authors: Nagata, Jason M.; Alsamman, Sana; Smith, Natalia; Yu, Jiayue; Ganson, Kyle T.; Dooley, Erin E.; Wing, David; Baker, Fiona C.; Pettee Gabriel, Kelley

Abstract

Background: Sociodemographic disparities in adolescent physical activity have been documented but mostly rely on self-reported data. Our objective was to examine differences in device-based step metrics, including daily step count (steps d-1), by sociodemographic factors among a diverse sample of 10-to-14-year-old adolescents in the US. Methods: We analyzed prospective cohort data from Year 2 (2018-2020) of the Adolescent Brain Cognitive Development (ABCD) Study (N = 6460). Mixed-effects models were conducted to estimate associations of sociodemographic factors (sex, sexual orientation, race/ethnicity, household income, parental education, and parental marital status) with repeated measures of steps d-1 over the course of 21 days. Results: Participants (49.6% female, 39.0% racial/ethnic minority) accumulated an average of 9095.8 steps d-1. In mixed-effects models, 1543.6 more steps d-1 were recorded for male versus female sex, Black versus White race (328.8 more steps d-1), heterosexual versus sexual minority sexual orientation (676.4 more steps d-1), >$200,000 versus <$25,000 household income (1003.3 more steps d-1), and having married/partnered parents versus unmarried/unpartnered parents (326.3 more steps d-1). We found effect modification by household income for Black adolescents and by sex for Asian adolescents. Conclusions: Given sociodemographic differences in adolescent steps d-1, physical activity guidelines should focus on key populations and adopt strategies optimized for adolescents from diverse backgrounds. Impact: Sociodemographic disparities in physical activity have been documented but mostly rely on self-reported data, which can be limited by reporting and prevarication bias. In this demographically diverse sample of 10-14-year-old early adolescents in the U.S., we found notable and nuanced sociodemographic disparities in Fitbit steps per day. More daily steps were recorded for male versus female sex, Black versus White race, heterosexual versus sexual minority, >$100,000 versus <$25,000 household income, and having married/partnered versus unmarried/unpartnered parents. We found effect modification by household income for Black adolescents and by sex for Asian adolescents.

Testing the Effects of App-Based Motivational Messages on Physical Activity and Resting Heart Rate Through Smartphone App Compliance in Patients With Vulnerable Coronary Artery Plaques: Protocol for a Microrandomized Trial (2023)

JMIR Research Protocols

Authors: Mitra, Sayan; Kroeger, Cynthia M.; Xu, Jing; Avery, Leah; Masedunskas, Andrius; Cassidy, Sophie; Wang, Tian; Hunyor, Imre; Wilcox, Ian; Huang, Robin; Chakraborty, Bibhas; Fontana, Luigi

Abstract

Background: Achieving the weekly physical activity recommendations of at least 150-300 minutes of moderate-intensity or 75-150 minutes of vigorous-intensity aerobic exercise is important for reducing cardiometabolic risk, but evidence shows that most people struggle to meet these goals, particularly in the mid to long term. Objective: The Messages Improving Resting Heart Health (MIRTH) study aims to determine if (1) sending daily motivational messages through a research app is effective in improving motivation and in promoting adherence to physical activity recommendations in men and women with coronary heart disease randomized to a 12-month intensive lifestyle intervention, and (2) the time of the day when the message is delivered impacts compliance with exercise training. Methods: We will conduct a single-center, microrandomized trial. Participants will be randomized daily to either receive or not receive motivational messages over two 90-day periods at the beginning (phase 1: months 4-6) and at the end (phase 2: months 10-12) of the Lifestyle Vulnerable Plaque Study. Wrist-worn devices (Fitbit Inspire 2) and Bluetooth pairing with smartphones will be used to passively collect data for proximal (ie, physical activity duration, steps walked, and heart rate within 180 minutes of receiving messages) and distal (ie, change values for resting heart rate and total steps walked within and across both phases 1 and 2 of the trial) outcomes. Participants will be recruited from a large academic cardiology office practice (Central Sydney Cardiology) and the Royal Prince Alfred Hospital Departments of Cardiology and Radiology. All clinical investigations will be undertaken at the Charles Perkins Centre Royal Prince Alfred clinic. Individuals aged 18-80 years (n=58) with stable coronary heart disease who have low attenuation plaques based on a coronary computed tomography angiography within the past 3 months and have been randomized to an intensive lifestyle intervention program will be included in MIRTH. Results: The Lifestyle Vulnerable Plaque Study was funded in 2020 and started enrolling participants in February 2022. Recruitment for MIRTH commenced in November 2022. As of September 2023, 2 participants were enrolled in the MIRTH study and provided baseline data. Conclusions: This MIRTH microrandomized trial will represent the single most detailed and integrated analysis of the effects of a comprehensive lifestyle intervention delivered through a customized mobile health app on smart devices on time-based motivational messaging for patients with coronary heart disease. This study will also help inform future studies optimizing for just-in-time adaptive interventions. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN12622000731796; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=382861. International registered report identifier (irrid): DERR1-10.2196/46082. Keywords: adherence; coronary artery disease; coronary heart disease; digital health; health behavior; heart rate; messages; mhealth; microrandomized trial; mobile app; physical activity; smartphone; telehealth; user motivation.

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The Added Value of Remote Technology in Cardiac Rehabilitation on Physical Function, Anthropometrics, and Quality of Life: Cluster Randomized Controlled Trial (2023)

Journal of Medical Internet Research

Authors: Lahtio, Heli; Heinonen, Ari; Paajanen, Teemu; Sjögren, Tuulikki

Abstract

Background: Cardiovascular diseases (CVDs) cause most deaths globally and can reduce quality of life (QoL) of rehabilitees with cardiac disease. The risk factors of CVDs are physical inactivity and increased BMI. With physical activity, it is possible to prevent CVDs, improve QoL, and help maintain a healthy body mass. Current literature shows the possibilities of digitalization and advanced technology in supporting independent self-rehabilitation. However, the interpretation of the results is complicated owing to the studies' high heterogeneity. In addition, the added value of this technology has not been studied well, especially in cardiac rehabilitation. Objective: We aimed to examine the effectiveness of added remote technology in cardiac rehabilitation on physical function, anthropometrics, and QoL in rehabilitees with CVD compared with conventional rehabilitation. Methods: Rehabilitees were cluster randomized into 3 remote technology intervention groups (n=29) and 3 reference groups (n=30). The reference group received conventional cardiac rehabilitation, and the remote technology intervention group received conventional cardiac rehabilitation with added remote technology, namely, the Movendos mCoach app and Fitbit charge accelerometer. The 12 months of rehabilitation consisted of three 5-day in-rehabilitation periods in the rehabilitation center. Between these periods were two 6-month self-rehabilitation periods. Outcome measurements included the 6-minute walk test, body mass, BMI, waist circumference, and World Health Organization QoL-BREF questionnaire at baseline and at 6 and 12 months. Between-group differences were assessed using 2-tailed t tests and Mann-Whitney U test. Within-group differences were analyzed using a paired samples t test or Wilcoxon signed-rank test. Results: Overall, 59 rehabilitees aged 41 to 66 years (mean age 60, SD 6 years; n=48, 81% men) were included in the study. Decrement in waist circumference (6 months: 1.6 cm; P=.04; 12 months: 3 cm; P<.001) and increment in self-assessed QoL were greater (environmental factors: 0.5; P=.02) in the remote technology intervention group than the reference group. Both groups achieved statistically significant improvements in the 6-minute walk test in both time frames (P=.01-.03). Additionally, the remote technology intervention group achieved statistically significant changes in the environmental domain at 0-6 months (P=.03) and waist circumference at both time frames (P=.01), and reference group achieve statistically significant changes in waist circumference at 0-6 months (P=.02). Conclusions: Remote cardiac rehabilitation added value to conventional cardiac rehabilitation in terms of waist circumference and QoL. The results were clinically small, but the findings suggest that adding remote technology to cardiac rehabilitation may increase beneficial health outcomes. There was some level of systematic error during rehabilitation intervention, and the sample size was relatively small. Therefore, care must be taken when generalizing the study results beyond the target population. To confirm assumptions of the added value of remote technology in rehabilitation interventions, more studies involving different rehabilitees with cardiac disease are required.

The Feasibility of Implementing Remote Measurement Technologies in Psychological Treatment for Depression: Mixed Methods Study on Engagement (2023)

JMIR mental health

Authors: de Angel, Valeria; Adeleye, Fadekemi; Zhang, Yuezhou; Cummins, Nicholas; Munir, Sara; Lewis, Serena; Laporta Puyal, Estela; Matcham, Faith; Sun, Shaoxiong; Folarin, Amos A.; Ranjan, Yatharth; Conde, Pauline; Rashid, Zulqarnain; Dobson, Richard; Hotopf, Matthew

Abstract

BACKGROUND: Remote measurement technologies (RMTs) such as smartphones and wearables can help improve treatment for depression by providing objective, continuous, and ecologically valid insights into mood and behavior. Engagement with RMTs is varied and highly context dependent; however, few studies have investigated their feasibility in the context of treatment. OBJECTIVE: A mixed methods design was used to evaluate engagement with active and passive data collection via RMT in people with depression undergoing psychotherapy. We evaluated the effects of treatment on 2 different types of engagement: study attrition (engagement with study protocol) and patterns of missing data (engagement with digital devices), which we termed data availability. Qualitative interviews were conducted to help interpret the differences in engagement. METHODS: A total of 66 people undergoing psychological therapy for depression were followed up for 7 months. Active data were gathered from weekly questionnaires and speech and cognitive tasks, and passive data were gathered from smartphone sensors and a Fitbit (Fitbit Inc) wearable device. RESULTS: The overall retention rate was 60\%. Higher-intensity treatment (χ21=4.6; P=.03) and higher baseline anxiety (t56.28=-2.80, 2-tailed; P=.007) were associated with attrition, but depression severity was not (t50.4=-0.18; P=.86). A trend toward significance was found for the association between longer treatments and increased attrition (U=339.5; P=.05). Data availability was higher for active data than for passive data initially but declined at a sharper rate (90\%-30\% drop in 7 months). As for passive data, wearable data availability fell from a maximum of 80\% to 45\% at 7 months but showed higher overall data availability than smartphone-based data, which remained stable at the range of 20\%-40\% throughout. Missing data were more prevalent among GPS location data, followed by among Bluetooth data, then among accelerometry data. As for active data, speech and cognitive tasks had lower completion rates than clinical questionnaires. The participants in treatment provided less Fitbit data but more active data than those on the waiting list. CONCLUSIONS: Different data streams showed varied patterns of missing data, despite being gathered from the same device. Longer and more complex treatments and clinical characteristics such as higher baseline anxiety may reduce long-term engagement with RMTs, and different devices may show opposite patterns of missingness during treatment. This has implications for the scalability and uptake of RMTs in health care settings, the generalizability and accuracy of the data collected by these methods, feature construction, and the appropriateness of RMT use in the long term.

The Role of Daily Steps in the Treatment of Major Depressive Disorder: Secondary Analysis of a Randomized Controlled Trial of a 6-Month Internet-Based, Mindfulness-Based Cognitive Behavioral Therapy Intervention for Youth (2023)

Interactive Journal of Medical Research

Authors: Dang, Kevin; Ritvo, Paul; Katz, Joel; Gratzer, David; Knyahnytska, Yuliya; Ortiz, Abigail; Walters, Clarice; Attia, Mohamed; Gonzalez-Torres, Christina; Lustig, Andrew; Daskalakis, Zafiris

Abstract

BACKGROUND: Current evidence supports physical activity (PA) as an adjunctive treatment for major depressive disorder (MDD). Few studies, however, have examined the relationship between objectively measured PA and MDD treatment outcomes using prospective data. OBJECTIVE: This study is a secondary analysis of data from a 24-week internet-based, mindfulness-based cognitive behavioral therapy program for MDD. The purpose of this analysis was twofold: (1) to examine average daily step counts in relation to MDD symptom improvement, and whether pain moderated this relationship; and (2) to examine whether changes in step activity (ie, step trajectories) during treatment were associated with baseline symptoms and symptom improvement. METHODS: Patients from the Centre for Addiction and Mental Health were part of a randomized controlled trial evaluating the effects of internet-based, mindfulness-based cognitive behavioral therapy for young adults (aged 18-30 years old) with MDD. Data from 20 participants who had completed the intervention were analyzed. PA, in the form of objectively measured steps, was measured using the Fitbit-HR Charge 2 (Fitbit Inc), and self-reported depression severity was measured with the Beck Depression Inventory-II (BDI-II). Linear regression analysis was used to test PA's relationship with depression improvement and the moderating effect of pain severity and pain interference. Growth curve and multivariable regression models were used to test longitudinal associations. RESULTS: Participants walked an average of 8269 steps per day, and each additional +1000-step difference between participants was significantly associated with a 2.66-point greater improvement (reduction) in BDI-II, controlling for anxiety, pain interference, and adherence to Fitbit monitoring (P=.02). Pain severity appeared to moderate (reduce) the positive effect of average daily steps on BDI-II improvement (P=.03). Higher baseline depression and anxiety symptoms predicted less positive step trajectories throughout treatment (Ps≤.001), and more positive step trajectories early in the trial predicted greater MDD improvement at the end of the trial (Ps{\textless}.04). However, step trajectories across the full duration of the trial did not significantly predict MDD improvement (Ps=.40). CONCLUSIONS: This study used objective measurements to demonstrate positive associations between PA and depression improvement in the context of cognitive behavioral treatment. Pain appeared to moderate this relationship, and baseline symptoms of anxiety and depression predicted PA trajectories. The findings inform future interventions for major depression. Future research with larger samples should consider additional moderators of PA-related treatment success and the extent to which outcomes are related to PA change in multimodal interventions. TRIAL REGISTRATION: Clinical Trials.gov NCT03406052; https://www.clinicaltrials.gov/ct2/show/NCT03406052. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/11591.

Using Consumer Wearable Devices to Profile Postoperative Complications After Pediatric Appendectomy (2023)

The Journal of Surgical Research

Authors: Pitt, J. Benjamin; Zeineddin, Suhail; Carter, Michela; Figueroa, Angie; Park, Erica; Kwon, Soyang; Ghomrawi, Hassan; Abdullah, Fizan

Abstract

INTRODUCTION: Markers of postoperative recovery in pediatric patients are difficult for parents to evaluate after hospital discharge, who use subjective proxies to assess recovery and the onset of complications. Consumer-grade wearable devices (e.g., Fitbit) generate objective recovery data in near real time and thus may provide an opportunity to remotely monitor postoperative patients and identify complications beyond the initial hospitalization. The aim of this study was to use daily step counts from a Fitbit to compare recovery in patients with complications to those without complications after undergoing appendectomy for complicated appendicitis. METHODS: Children ages 3-17 years old undergoing laparoscopic appendectomy for complicated appendicitis were recruited. Patients wore a Fitbit device for 21 d after operation. After collection, patient data were included in the analysis if minimum wear-time criteria were achieved. Postoperative complications were identified through chart review, and step count trajectories for patients recovering with and without complications were compared. Additionally, to account for the patients experiencing a complication on different postoperative days, median daily step count for pre- and post-complication were analyzed. RESULTS: Eighty-six patients with complicated appendicitis were enrolled in the study, and fourteen children developed a postoperative complication. Three patients were excluded because they did not meet the minimum wear time requirements. Complications were divided into abscesses (n = 7, 64\%), surgical site infections (n = 2, 18\%), and other, which included small bowel obstruction and Clostridioides difficile infection (n = 2, 18\%). Patients presented with a complication on mean postoperative day 8, while deviation from the normative recovery trajectory was evident 4 d prior. When compared to children with normative recovery, the patients with surgical complications experienced a slower increase in step count postoperatively, but the recovery trajectory was specific to each complication type. When corrected for day of presentation with complication, step count remained low prior to the discovery of the complication and increased after treatment resembling the normative recovery trajectory. CONCLUSIONS: This study profiled variations from the normative recovery trajectory in patients with complication after appendectomy for complicated appendicitis, with distinct trajectory patterns by complication type. Our findings have potentially profound clinical implications for monitoring pediatric patients postoperatively, particularly in the outpatient setting, thus providing objective data for potentially earlier identification of complications after hospital discharge.

Using mobile health to encourage physical activity in individuals with intellectual disability: a pilot mixed methods feasibility study (2023)

Frontiers in Rehabilitation Sciences

Authors: Michalsen, Henriette; Henriksen, André; Pettersen, Gunn; Hartvigsen, Gunnar; Wangberg, Silje; Thrane, Gyrd; Jahnsen, Reidun; Anke, Audny

Abstract

BACKGROUND: Many individuals with intellectual disability (ID) have a sedentary lifestyle. Few interventions aimed at increasing their level of physical activity (PA) have shown lasting effects. AIM: To assess the feasibility and acceptability of a pilot intervention study using innovative mobile health (mHealth) support systems to encourage PA in individuals with ID. METHODS: Nine individuals with ID and a low level of PA, aged 16-36 years, were included in the present convergent triangulation mixed method design. Two mHealth support systems (apps) were developed and tested. PA was measured with a Fitbit smartwatch, accelerometer, the International Physical Activity Questionnaire-Short Form (IPAQ-S), and Goal attainment scaling. Data were collected through online pre-, mid- (4 weeks), and post-intervention (12 weeks) questionnaires and activity trackers. Semi-structured qualitative interviews with participants and/or a family or staff member were held after the 12-week follow-up. Data were analyzed using conventional nonparametric statistics and thematic analyses. RESULTS: The response rate and retention to the trial were 16\% and 100\%, respectively. Data quality was high, except for missing data from Fitbit activity trackers of approximately 30\% from the 4- and 12-week follow-up stages. The feasibility challenges with activity trackers include rashes, size, non-acceptance, and loss of motivation. Participants and family members/staff reported interest in the study theme and were pleased with the data collection method. All but one participant achieved their PA goals. Most participants reported being satisfied with the apps as they were enjoyable or provided a reminder for performing physical and other activities. Social support for PA among family members also increased. However, app support from staff and family members was needed, and apps were not used regularly. Two of nine participants (22\%) had increased their PA measured as steps per day with Fitbit at the 12-week follow-up. CONCLUSIONS: The acceptability and feasibility of using tailored mobile applications in natural settings to increase PA among adults with ID are promising. This study aligns with previous studies in showing the challenges to increasing PA, which requires the inclusion of family members, staff, and stakeholders. The intervention requires modifications before a randomized controlled trial can be conducted.

Validation of an open-source smartphone step counting algorithm in clinical and non-clinical settings (2023)

medRxiv: The Preprint Server for Health Sciences

Authors: Straczkiewicz, Marcin; Keating, Nancy L.; Thompson, Embree; Matulonis, Ursula A.; Campos, Susana M.; Wright, Alexi A.; Onnela, Jukka-Pekka

Abstract

Background: Step counts are increasingly used in public health and clinical research to assess wellbeing, lifestyle, and health status. However, estimating step counts using commercial activity trackers has several limitations, including a lack of reproducibility, generalizability, and scalability. Smartphones are a potentially promising alternative, but their step-counting algorithms require robust validation that accounts for temporal sensor body location, individual gait characteristics, and heterogeneous health states. Objective: Our goal was to evaluate an open-source step-counting method for smartphones under various measurement conditions against step counts estimated from data collected simultaneously from different body locations ("internal" validation), manually ascertained ground truth ("manual" validation), and step counts from a commercial activity tracker (Fitbit Charge 2) in patients with advanced cancer ("wearable" validation). Methods: We used eight independent datasets collected in controlled, semi-controlled, and free-living environments with different devices (primarily Android smartphones and wearable accelerometers) carried at typical body locations. Five datasets (N=103) were used for internal validation, two datasets (N=107) for manual validation, and one dataset (N=45) used for wearable validation. In each scenario, step counts were estimated using a previously published step-counting method for smartphones that uses raw sub-second level accelerometer data. We calculated mean bias and limits of agreement (LoA) between step count estimates and validation criteria using Bland-Altman analysis. Results: In the internal validation datasets, participants performed 751.7±581.2 (mean±SD) steps, and the mean bias was -7.2 steps (LoA -47.6, 33.3) or -0.5%. In the manual validation datasets, the ground truth step count was 367.4±359.4 steps while the mean bias was -0.4 steps (LoA -75.2, 74.3) or 0.1 %. In the wearable validation dataset, Fitbit devices indicated mean step counts of 1931.2±2338.4, while the calculated bias was equal to -67.1 steps (LoA -603.8, 469.7) or a difference of 0.3 %. Conclusions: This study demonstrates that our open-source step counting method for smartphone data provides reliable step counts across sensor locations, measurement scenarios, and populations, including healthy adults and patients with cancer.

Validity of activity wristbands for estimating daily physical activity in primary schoolchildren under free-living conditions: School-Fit study (2023)

Frontiers in Public Health

Authors: Mayorga-Vega, Daniel; Casado-Robles, Carolina; Guijarro-Romero, Santiago; Viciana, Jesús

Abstract

INTRODUCTION: The use of activity wristbands to monitor and promote schoolchildren's physical activity (PA) is increasingly widespread. However, their validity has not been sufficiently studied, especially among primary schoolchildren. Consequently, the main purpose was to examine the validity of the daily steps and moderate-to-vigorous PA (MVPA) scores estimated by the activity wristbands Fitbit Ace 2, Garmin Vivofit Jr 2, and the Xiaomi Mi Band 5 in primary schoolchildren under free-living conditions. MATERIALS AND METHODS: An initial sample of 67 schoolchildren (final sample = 62; 50\% females), aged 9-12 years old (mean = 10.4 ± 1.0 years), participated in the present study. Each participant wore three activity wristbands (Fitbit Ace 2, Garmin Vivofit Jr 2, and Xiaomi Mi Band 5) on his/her non-dominant wrist and a research-grade accelerometer (ActiGraph wGT3X-BT) on his/her hip as the reference standard (number of steps and time in MVPA) during the waking time of one day. RESULTS: Results showed that the validity of the daily step scores estimated by the Garmin Vivofit Jr 2 and Xiaomi Mi Band 5 were good and acceptable (e.g., MAPE = 9.6/11.3\%, and lower 95\% IC of ICC = 0.87/0.73), respectively, as well as correctly classified schoolchildren as meeting or not meeting the daily 10,000/12,000-step-based recommendations, obtaining excellent/good and good/acceptable results (e.g., Garmin Vivofit Jr 2, k = 0.75/0.62; Xiaomi Mi Band 5, k = 0.73/0.53), respectively. However, the Fitbit Ace 2 did not show an acceptable validity (e.g., daily steps: MAPE = 21.1\%, and lower 95\% IC of ICC = 0.00; step-based recommendations: k = 0.48/0.36). None of the three activity wristbands showed an adequate validity for estimating daily MVPA (e.g., MAPE = 36.6-90.3\%, and lower 95\% IC of ICC = 0.00-0.41) and the validity for the MVPA-based recommendation tended to be considerably lower (e.g., k = -0.03-0.54). CONCLUSIONS: The activity wristband Garmin Vivofit Jr 2 obtained the best validity for monitoring primary schoolchildren's daily steps, offering a feasible alternative to the research-grade accelerometers. Furthermore, this activity wristband could be used during PA promotion programs to provide accurate feedback to primary schoolchildren to ensure their accomplishment with the PA recommendations.

Wearable Sensor and Mobile App-Based mHealth Approach for Investigating Substance Use and Related Factors in Daily Life: Protocol for an Ecological Momentary Assessment Study (2023)

JMIR research protocols

Authors: Takano, Ayumi; Ono, Koki; Nozawa, Kyosuke; Sato, Makito; Onuki, Masaki; Sese, Jun; Yumoto, Yosuke; Matsushita, Sachio; Matsumoto, Toshihiko

Abstract

Background: Digital health technologies using mobile apps and wearable devices are a promising approach to the investigation of substance use in the real world and for the analysis of predictive factors or harms from substance use. Moreover, consecutive repeated data collection enables the development of predictive algorithms for substance use by machine learning methods. Objective: We developed a new self-monitoring mobile app to record daily substance use, triggers, and cravings. Additionally, a wearable activity tracker (Fitbit) was used to collect objective biological and behavioral data before, during, and after substance use. This study aims to describe a model using machine learning methods to determine substance use. Methods: This study is an ongoing observational study using a Fitbit and a self-monitoring app. Participants of this study were people with health risks due to alcohol or methamphetamine use. They were required to record their daily substance use and related factors on the self-monitoring app and to always wear a Fitbit for 8 weeks, which collected the following data: (1) heart rate per minute, (2) sleep duration per day, (3) sleep stages per day, (4) the number of steps per day, and (5) the amount of physical activity per day. Fitbit data will first be visualized for data analysis to confirm typical Fitbit data patterns for individual users. Next, machine learning and statistical analysis methods will be performed to create a detection model for substance use based on the combined Fitbit and self-monitoring data. The model will be tested based on 5-fold cross-validation, and further preprocessing and machine learning methods will be conducted based on the preliminary results. The usability and feasibility of this approach will also be evaluated. Results: Enrollment for the trial began in September 2020, and the data collection finished in April 2021. In total, 13 people with methamphetamine use disorder and 36 with alcohol problems participated in this study. The severity of methamphetamine or alcohol use disorder assessed by the Drug Abuse Screening Test-10 or the Alcohol Use Disorders Identification Test-10 was moderate to severe. The anticipated results of this study include understanding the physiological and behavioral data before, during, and after alcohol or methamphetamine use and identifying individual patterns of behavior. Conclusions: Real-time data on daily life among people with substance use problems were collected in this study. This new approach to data collection might be helpful because of its high confidentiality and convenience. The findings of this study will provide data to support the development of interventions to reduce alcohol and methamphetamine use and associated negative consequences.

Wellness in Nursing Education to Promote Resilience and Reduce Burnout: Protocol for a Holistic Multidimensional Wellness Intervention and Longitudinal Research Study Design in Nursing Education (2023)

JMIR research protocols

Authors: Strout, Kelley; Schwartz-Mette, Rebecca; McNamara, Jade; Parsons, Kayla; Walsh, Dyan; Bonnet, Jen; O'Brien, Liam M.; Robinson, Kathryn; Sibley, Sean; Smith, Annie; Sapp, Maile; Sprague, Lydia; Sabegh, Nima Sajedi; Robinson, Kaitlin; Henderson, Amanda

Abstract

BACKGROUND: The United States faces a nursing shortage driven by a burnout epidemic among nurses and nursing students. Nursing students are an integral population to fuel the nursing workforce at high risk of burnout and increased rates of perceived stress. OBJECTIVE: The aim of this paper is to describe WellNurse, a holistic, interdisciplinary, multidimensional longitudinal research study that examines evidence-based interventions intended to reduce burnout and increase resilience among graduate and undergraduate nursing students. METHODS: Graduate and undergraduate nursing students matriculated at a large public university in the northeastern United States are eligible to enroll in this ongoing, longitudinal cohort study beginning in March 2021. Participants complete a battery of health measurements twice each semester during the fourth week and the week before final examinations. The measures include the Perceived Stress Scale, the Satisfaction with Life Scale, the Oldenburg Burnout Inventory, the Brief Resilience Scale, and the Pittsburgh Sleep Quality Index. Participants are eligible to enroll in a variety of interventions, including mindfulness-based stress reduction, mindful eating, fitness training, and massage therapy. Those who enroll in specific, targeted interventions complete additional measures designed to target the aim of the intervention. All participants receive a free Fitbit device. Additional environmental changes are being implemented to further promote a culture that supports academic well-being, including recruiting a diverse student population through evidence-based holistic admissions, inclusive teaching design, targeted resilience and stress reduction workshops, and cultural shifts within classrooms and curricula. The study design protocol is registered at Open Science Framework (DOI 10.17605/OSF.IO/NCBPE). RESULTS: The project was funded on January 1, 2022. Data collection started in March 2022. A total of 267 participants have been recruited. Results will be published after each semester starting in December 2023. WellNurse evaluation follows the Rapid Cycle Quality Improvement framework to continuously monitor ongoing project processes, activity outcomes, and progress toward reducing burnout and increasing resilience. Rapid Cycle Quality Improvement promotes the ability to alter WellNurse interventions, examine multiple interventions, and test their effectiveness among the nursing education population to identify the most effective interventions. CONCLUSIONS: Academic nursing organizations must address student burnout risk and increase resilience to produce a future workforce that provides high-quality patient care to a diverse population. Findings from WellNurse will support evidence-based implementations for public baccalaureate and master's nursing programs in the United States. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49020.

Working-from-home persistently influences sleep and physical activity 2 years after the Covid-19 pandemic onset: a longitudinal sleep tracker and electronic diary-based study (2023)

Frontiers in Psychology

Authors: Massar, Stijn A. A.; Ong, Ju Lynn; Lau, TeYang; Ng, Ben K. L.; Chan, Lit Fai; Koek, Daphne; Cheong, Karen; Chee, Michael W. L.

Abstract

Objective Working from home (WFH) has become common place since the Covid-19 pandemic. Early studies observed population-level shifts in sleep patterns (later and longer sleep) and physical activity (reduced PA), during home confinement. Other studies found these changes to depend on the proportion of days that individuals WFH (vs. work from office; WFO). Here, we examined the effects of WFH on sleep and activity patterns in the transition to normality during the later stages of the Covid-19 pandemic (Aug 2021–Jan 2022). Methods Two-hundred and twenty-five working adults enrolled in a public health study were followed for 22 weeks. Sleep and activity data were collected with a consumer fitness tracker (Fitbit Versa 2). Over three 2-week periods (Phase 1/week 1–2: August 16–29, 2021; Phase 2/week 11–12: October 25–November 7, 2021; Phase 3/week 21–22: January 3–16, 2022), participants provided daily Fitbit sleep and activity records. Additionally, they completed daily phone-based ecological momentary assessment (EMA), providing ratings of sleep quality, wellbeing (mood, stress, motivation), and information on daily work arrangements (WFH, WFO, no work). Work arrangement data were used to examine the effects of WFH vs. WFO on sleep, activity, and wellbeing. Results The proportion of WFH vs. WFO days fluctuated over the three measurement periods, mirroring evolving Covid restrictions. Across all three measurement periods WFH days were robustly associated with later bedtimes (+14.7 min), later wake times (+42.3 min), and longer Total Sleep Time (+20.2 min), compared to WFO days. Sleep efficiency was not affected. WFH was further associated with lower daily step count than WFO (−2,471 steps/day). WFH was associated with higher wellbeing ratings compared to WFO for those participants who had no children. However, for participants with children, these differences were not present. Conclusion Pandemic-initiated changes in sleep and physical activity were sustained during the later stage of the pandemic. These changes could have longer term effects, and conscious effort is encouraged to harness the benefits (i.e., longer sleep), and mitigate the pitfalls (i.e., less physical activity). These findings are relevant for public health as hybrid WHF is likely to persist in a post-pandemic world.

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A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study (2022)

The international journal of behavioral nutrition and physical activity

Authors: Mora-Gonzalez, Jose; Gould, Zachary R.; Moore, Christopher C.; Aguiar, Elroy J.; Ducharme, Scott W.; Schuna, John M.; Barreira, Tiago V.; Staudenmayer, John; McAvoy, Cayla R.; Boikova, Mariya; Miller, Taavy A.; Tudor-Locke, Catrine

Abstract

Background: Standardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies. Purpose: To expand a previously published child/youth catalog of validity indices to include adults (21-40, 41-60 and 61-85 years of age) assessed across a range of treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]) and device wear locations (ankle, thigh, waist, and wrist). Methods: Two hundred fifty-eight adults (52.5 ± 18.7 years, 49.6% female) participated in this laboratory-based study and performed a series of 5-min treadmill bouts while wearing multiple devices; 21 devices in total were evaluated over the course of this multi-year cross-sectional study (2015-2019). The criterion measure was directly observed steps. Computed validity indices included accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV). Results: Over the range of normal speeds, 15 devices (Actical, waist-worn ActiGraph GT9X, activPAL, Apple Watch Series 1, Fitbit Ionic, Fitbit One, Fitbit Zip, Garmin vivoactive 3, Garmin vivofit 3, waist-worn GENEActiv, NL-1000, PiezoRx, Samsung Gear Fit2, Samsung Gear Fit2 Pro, and StepWatch) performed at < 5% MAPE. The wrist-worn ActiGraph GT9X displayed the worst accuracy across normal speeds (MAPE = 52%). On average, accuracy was compromised across slow walking speeds for all wearable technologies (MAPE = 40%) while all performed best across normal speeds (MAPE = 7%). When analyzing the data by wear locations, the ankle and thigh demonstrated the best accuracy (both MAPE = 1%), followed by the waist (3%) and the wrist (15%) across normal speeds. There were significant effects of speed, wear location, and age group on accuracy and bias (both p < 0.001) and precision (p ≤ 0.045). Conclusions: Standardized validation indices cataloged by speed, wear location, and age group across the adult lifespan facilitate selecting, evaluating, or comparing performance of step counting wearable technologies. Speed, wear location, and age displayed a significant effect on accuracy, bias, and precision. Overall, reduced performance was associated with very slow walking speeds (0.8 to 3.2 km/h). Ankle- and thigh-located devices logged the highest accuracy, while those located at the wrist reported the worst accuracy.

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A Digital Health Program Targeting Physical Activity Among Adolescents With Overweight or Obesity: Open Trial (2022)

JMIR pediatrics and parenting

Authors: Cummings, Caroline; Crochiere, Rebecca; Lansing, Amy Hughes; Patel, Riya; Stanger, Catherine

Abstract

Background: Prior studies suggest that mobile health physical activity programs that provide only weekly or daily text-based health coaching evidence limit the efficacy in improving physical activity in adolescents with overweight or obesity. It is possible that incentives, combined with health coaching and daily feedback on goal success, may increase program efficacy; however, such programs have not yet been tested with adolescents with overweight and obesity. Objective: This study aims to examine the feasibility and acceptability of a 12-week, incentive-based, mobile health physical activity program with text-based health coaching, goal setting, and self-monitoring for adolescents with overweight or obesity. Program adherence and changes in tracked physical activity (ie, steps and active minutes while wearing a Fitbit [Google LLC]), body mass, and body fat are assessed. Methods: A total of 28 adolescents aged 13 to 18 years with a BMI ≥90th percentile participated in the program. Of the 28 participants, 2 (7%) were lost to follow-up; thus, data from 26 (93%) participants were used in analyses. Results: Participant-reported acceptability was high, with all mean ratings of text-based coaching, Fitbit use, and the overall program being >5 on a 7-point scale. In addition, 85% (23/26) of participants reported that they would like to continue to wear the Fitbit. Program adherence was also high, as participants wore the Fitbit on 91.1% (SD 12.6%) of days on average and met their weekly goals for an average of 7 (SD 3.5) of 11 possible weeks. There were no demographic (ie, sex, age, and baseline body mass) differences in the percentage of days participants wore their Fitbit. Across the 12-week study, there were significant improvements in tracked daily active minutes (P=.006) and steps (P<.001) and significant pre- to posttest improvements in body fat percentage (P=.04). Conclusions: The pilot program improved adolescent physical activity and physical health. A larger factorial design trial with adaptive daily goals may clarify the role of each program component in driving physical activity.

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A distance-based, randomized controlled trial for reducing sedentary behavior among prostate cancer survivors: a study protocol (2022)

BMC public health

Authors: Trinh, Linda; Sabiston, Catherine M.; Alibhai, Shabbir M. H.; Jones, Jennifer M.; Arbour-Nicitopoulos, Kelly P.; Mina, Daniel Santa; Campbell, Kristin; Faulkner, Guy E.

Abstract

Background: Prostate cancer survivors (PCS) experience long-term side effects beyond treatment such as fatigue, depression and anxiety. Quality and engaging supportive care programs are needed to reduce these chronic and debilitating effects. Independent of physical activity (PA), high volumes of sedentary behavior (SB) are associated with chronic disease-related risk factors and poorer cancer-specific quality of life (QoL). Simultaneously increasing PA and decreasing SB may be an effective health promotion strategy. Given that PCS may face several barriers to engaging in supervised programs, there is a need to develop and assess the efficacy of interventions that employ distance-based approaches for behavior change. The primary aim of this study is to determine the effects of a 12-week intervention (Fitbit + behavioral counselling) vs. Fitbit-only control group in reducing SB among PCS. Secondary outcomes include light-intensity PA, QoL, motivational outcomes, and patient satisfaction. Methods: This two-armed, randomized controlled trial will recruit inactive PCS (stage I-IV) across Canada who self-report engaging in >8 hours/day of SB. Participants will be randomized to the intervention (n=60; Fitbit and behavioral support) or active control group (n=60; Fitbit-only). The intervention consists of the use of a Fitbit and a series of six behavioral support sessions (two group, four individual) to aid PCS in gradually replacing SB with light-intensity PA by increasing their daily step counts to 3,000 steps above their baseline values. The Fitbit-only control condition will receive a Fitbit and public health PA resources. The primary outcome is change in SB measured objectively using activPAL inclinometers. All secondary outcomes will be measured via self-report, except for PA which will be measuring using Fitbits. Data will be collected at baseline, post-intervention, and at 6-month post-intervention. Discussion: Reducing SB and increasing light-intensity PA plays an important, yet often undervalued role in the health and well-being of PCS. This study will create a unique distance-based platform that can be used by clinical and community-based organizations as a low-cost, supportive care tool to improve health outcomes for PCS.

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A Facebook-Delivered Weight Loss Intervention Using Open Enrollment: Randomized Pilot Feasibility Trial (2022)

JMIR Formative Research

Authors: Pagoto, Sherry L.; Schroeder, Matthew W.; Xu, Ran; Waring, Molly E.; Groshon, Laurie; Goetz, Jared M.; Idiong, Christie; Troy, Haley; DiVito, Joseph; Bannor, Richard

Abstract

Background Behavioral weight loss programs typically enroll 12-40 people into groups that then suffer from declining engagement over time. Web-based patient communities, on the other hand, typically offer no limits on capacity and membership is fluid. This model may be useful for boosting engagement in behavioral weight loss interventions, which could lead to better outcomes. Objective In this study, we aimed to examine the feasibility and acceptability of continuously enrolling participants into a Facebook-delivered weight loss intervention for the first 8 of 16 weeks relative to the same intervention where no new participants were enrolled after randomization. Methods We conducted a randomized pilot trial to compare a Facebook weight loss group that used open enrollment with a group that used closed enrollment on feasibility and acceptability in adults with BMI 27-45 kg/m2. The feasibility outcomes included retention, engagement, and diet tracking adherence. We described the percentage loss of ≥5% weight in both groups as an exploratory outcome. We also explored the relationship between total volume of activity in the group and weight loss. The participants provided feedback via web-based surveys and focus groups. Results Randomized participants (68/80, 85% women) were on average, aged 40.2 (SD 11.2) years with a mean BMI of 34.4 (SD 4.98) kg/m2. We enrolled an additional 54 participants (50/54, 93% female) in the open enrollment condition between weeks 1 and 8, resulting in a total group size of 94. Retention was 88% and 98% under the open and closed conditions, respectively. Randomized participants across conditions did not differ in engagement (P=.72), or diet tracking adherence (P=.42). Participant feedback in both conditions revealed that sense of community was what they liked most about the program and not enough individualized feedback was what they liked the least. Weight loss of ≥5% was achieved by 30% (12/40) of the participants randomized to the open enrollment condition and 18% (7/40) of the participants in the closed enrollment condition. Exploratory analyses revealed that the open condition (median 385, IQR 228-536.5) had a greater volume of engagement than the closed condition (median 215, IQR 145.5-292; P=.007). Furthermore, an increase of 100 in the total volume of engagement in the Facebook group each week was associated with an additional 0.1% weekly weight loss among the randomized participants (P=.02), which was independent of time, individual participant engagement, and sociodemographic characteristics. Conclusions Open enrollment was as feasible and acceptable as closed enrollment. A greater volume of engagement in the Facebook group was associated with weight loss, suggesting that larger groups that produce more engagement overall may be beneficial. Future research should examine the efficacy of the open enrollment approach for weight loss in a fully powered randomized trial.

A method for intelligent allocation of diagnostic testing by leveraging data from commercial wearable devices: a case study on COVID-19 (2022)

NPJ digital medicine

Authors: Shandhi, Md Mobashir Hasan; Cho, Peter J.; Roghanizad, Ali R.; Singh, Karnika; Wang, Will; Enache, Oana M.; Stern, Amanda; Sbahi, Rami; Tatar, Bilge; Fiscus, Sean; Khoo, Qi Xuan; Kuo, Yvonne; Lu, Xiao; Hsieh, Joseph; Kalodzitsa, Alena; Bahmani, Amir; Alavi, Arash; Ray, Utsab; Snyder, Michael P.; Ginsburg, Geoffrey S.; Pasquale, Dana K.; Woods, Christopher W.; Shaw, Ryan J.; Dunn, Jessilyn P.

Abstract

Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. However, diagnostic test shortages are prevalent globally and continue to occur in the US with the onset of new COVID-19 variants and emerging diseases like monkeypox, demonstrating an unprecedented need for improving our current methods for mass surveillance testing. By targeting surveillance testing toward individuals who are most likely to be infected and, thus, increasing the testing positivity rate (i.e., percent positive in the surveillance group), fewer tests are needed to capture the same number of positive cases. Here, we developed an Intelligent Testing Allocation (ITA) method by leveraging data from the CovIdentify study (6765 participants) and the MyPHD study (8580 participants), including smartwatch data from 1265 individuals of whom 126 tested positive for COVID-19. Our rigorous model and parameter search uncovered the optimal time periods and aggregate metrics for monitoring continuous digital biomarkers to increase the positivity rate of COVID-19 diagnostic testing. We found that resting heart rate (RHR) features distinguished between COVID-19-positive and -negative cases earlier in the course of the infection than steps features, as early as 10 and 5 days prior to the diagnostic test, respectively. We also found that including steps features increased the area under the receiver operating characteristic curve (AUC-ROC) by 7–11% when compared with RHR features alone, while including RHR features improved the AUC of the ITA model's precision-recall curve (AUC-PR) by 38–50% when compared with steps features alone. The best AUC-ROC (0.73 ± 0.14 and 0.77 on the cross-validated training set and independent test set, respectively) and AUC-PR (0.55 ± 0.21 and 0.24) were achieved by using data from a single device type (Fitbit) with high-resolution (minute-level) data. Finally, we show that ITA generates up to a 6.5-fold increase in the positivity rate in the cross-validated training set and up to a 4.5-fold increase in the positivity rate in the independent test set, including both symptomatic and asymptomatic (up to 27%) individuals. Our findings suggest that, if deployed on a large scale and without needing self-reported symptoms, the ITA method could improve the allocation of diagnostic testing resources and reduce the burden of test shortages.

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A multiple technology-based physical activity intervention for Latina adolescents in the USA: randomized controlled trial study protocol for Chicas Fuertes (2022)

Trials

Authors: Larsen, Britta; Greenstadt, Emily; Olesen, Brittany; Osuna, Lilliana; Godino, Job; Marcus, Bess; Dunsiger, Shira; Meyer, Dawn; Zive, Michelle

Abstract

Background: Latina adolescents in the USA report some of the lowest rates of physical activity of any demographic subgroup; this is paralleled by a markedly higher lifetime risk of obesity, type 2 diabetes, and other conditions related to inactivity. Despite this, to date, no fully powered clinical trials have tested physical activity interventions specifically for this population. High use of mobile technologies (including text messages, smartphone apps, and social media) suggests this could be an appropriate intervention channel, while also having potential for broad reach. This paper describes the protocol for Chicas Fuertes, a fully powered randomized trial of a mobile technology-based physical activity intervention for Latina adolescents. Methods: We plan to recruit 200 Latina teens (age 13-18) in San Diego, CA, currently engaging in ≤ 150 min/week of moderate-to-vigorous physical activity (MVPA) to be assigned 1:1 to the intervention or control groups. Those randomly assigned to the intervention group receive a one-on-one goal setting session followed by 6 months of mobile technology-based intervention, including a personalized website, Fitbit activity tracker and app, individually tailored text messages based on Fitbit data, and daily intervention content on Instagram. Those randomized to the control group receive only a Fitbit activity tracker. The main outcome is change in weekly minutes of MVPA from baseline to 6 months, measured both objectively (ActiGraph accelerometers and Fitbit Inspire HR) and subjectively (7-Day Physical Activity Recall Interview). Additional outcomes are maintenance of activity change at 12 months and changes in psychosocial constructs, including social support and self-efficacy, engagement with mobile technology channels, and costs of intervention delivery. We are also examining the potential mediators and moderators of the intervention. The efficacy of the intervention is analyzed using a mixed effects regression model, adjusting for any potential confounders not balanced by randomization. All analyses of accelerometer measured MVPA are also adjusted for wear time.

A Positive Emotion-Focused Intervention to Increase Physical Activity After Bariatric Surgery: Protocol for a Pilot Randomized Controlled Trial (2022)

JMIR research protocols

Authors: Feig, Emily H.; Harnedy, Lauren E.; Thorndike, Anne N.; Psaros, Christina; Healy, Brian C.; Huffman, Jeff C.

Abstract

BACKGROUND: Physical activity levels after bariatric surgery are usually low, despite the significant protective health benefits of physical activity in this population. Positive psychological well-being is associated with improved adherence to health behaviors, but bariatric surgery patients often have negative associations with physical activity that prevent sustained engagement. OBJECTIVE: The Gaining Optimism After weight Loss Surgery (GOALS) pilot randomized controlled trial is aimed at testing a novel intervention to increase physical activity after bariatric surgery, which incorporates positive psychological skill-building with motivational interviewing and goal-setting. METHODS: The GOALS trial is a 2-arm, 24-week pilot randomized controlled trial that aims to enroll 58 adults who report less than 200 minutes per week of moderate to vigorous physical activity and a desire to become more active 6-12 months after bariatric surgery. GOALS is testing the feasibility, acceptability, and preliminary efficacy of a positive psychology-motivational interviewing telephone intervention targeting to increase physical activity and associated positive affect. Intervention components include positive psychology, goal-setting, self-monitoring via provided Fitbits, and motivational interviewing to overcome barriers and increase motivation. The intervention is compared to a physical activity education control that includes mailings with psychoeducation around physical activity and provision of a Fitbit. The primary outcomes of the pilot trial are feasibility and acceptability, measured as session completion rates and participant ratings of ease and helpfulness of each session. The main secondary outcome is change in accelerometer-measured moderate to vigorous physical activity post intervention and at 24-week follow-up. Additional outcomes include changes in attitudes related to physical activity, psychological well-being, and physical health measures. RESULTS: This multiphase project was funded in 2020 and institutional review board approval was obtained for the proposed trial in 2021. Recruitment for the randomized controlled trial began in July 2022. Upon completion of the pilot trial, we will examine the feasibility, acceptability, and preliminary efficacy of the intervention. CONCLUSIONS: Although bariatric surgery is the most effective treatment available for severe obesity, weight regain occurs, often in the context of low psychological well-being. Many individuals would benefit from learning strategies to increase positive psychological well-being after bariatric surgery, which could help them maintain lifestyle changes. Positive psychology is a novel approach to improve adherence by increasing positive associations with health behaviors including physical activity. The GOALS pilot trial will determine whether this type of intervention is feasible and acceptable to this population and will provide a foundation for a future full-scale randomized controlled efficacy trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT04868032; https://clinicaltrials.gov/ct2/show/NCT04868032. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/39856.

A qualitative study to explore the acceptability and usefulness of personalized biofeedback to motivate physical activity in cancer survivors (2022)

Digital Health

Authors: Brannon, Grace E.; Ray, Madison; Cho, Patrick; Baum, Miranda; Beg, Muhammad Shaalan; Bevers, Therese; Schembre, Susan M.; Basen-Engquist, Karen; Liao, Yue

Abstract

Objective: Many cancer survivors do not meet recommended levels of exercise, despite the benefits physical activity offers. This study aimed to understand experiences of insufficiently active overweight/obese breast or colorectal cancer survivors, in efforts to (1) examine regular physical activity barriers, and (2) determine perceptions and acceptability of a remotely delivered physical activity intervention utilizing wearable sensors and personalized feedback messages. Methods: In-person and virtual small group interviews were conducted engaging overweight/obese cancer survivors (n = 16, 94\% female, 94\% breast cancer survivors) in discussions resulting in 314 pages of transcribed data analyzed by multiple coders. Results: All participants expressed needing to increase physical activity, identifying lack of motivation centering on survivorship experiences and symptom management as the most salient barrier. They indicated familiarity with activity trackers (i.e., Fitbit) and expressed interest in biosensors (i.e., continuous glucose monitors [CGMs]) as CGMs show biological metrics in real-time. Participants reported (1) personalized feedback messages can improve motivation and accountability; (2) CGM acceptability is high given survivors' medical history; and (3) glucose data is a relevant health indicator and they appreciated integrated messages (between Fitbit and CGM) in demonstrating how behaviors immediately affect one's body. Conclusions: This study supports the use of wearable biosensors and m-health interventions to promote physical activity in cancer survivors. Glucose-based biofeedback provides relevant and motivating information for cancer survivors regarding their daily activity levels by demonstrating the immediate effects of physical activity. Integrating biofeedback into physical activity interventions could be an effective behavioral change strategy to promote a healthy lifestyle in cancer survivors.

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A Randomized Clinical Trial Demonstrating Feasibility and Preliminary Efficacy of a Videoconference-Delivered Physical Activity Lifestyle Intervention Among Adolescents With a Congenital Heart Defect (2022)

Annals of behavioral medicine : a publication of the Society of Behavioral Medicine

Authors: Jackson, Jamie L.; Fox, Kristen R.; Rausch, Joseph R.; Swenski, Taylor N.; Neville, Steven P.; Marousis, Noelle C.; Korth, Christina X.; Cua, Clifford L.; Garg, Vidu; Vannatta, Kathryn

Abstract

Background: Individuals with congenital heart defects are at increased risk for developing further cardiovascular complications, which can be mitigated by increasing physical activity. Given that positive health behaviors begin declining during older adolescence, it is vital to promote lifestyle changes in this population. Purpose: The current study aims to (a) determine the feasibility/acceptability of the Congenital Heart Disease Physical Activity Lifestyle (CHD-PAL) intervention among adolescents (ages 15-18) with moderate and complex congenital heart defects, and (b) estimate the preliminary efficacy of CHD-PAL for increasing time spent in moderate-to-vigorous physical activity (MVPA) and cardiorespiratory fitness and decreasing sedentary behavior. Methods: Eligible participants were randomized into either CHD-PAL (eight 30-min videoconferencing sessions over 20 weeks with an interventionist + Fitbit + exercise prescription) or a comparator (Fitbit + exercise prescription). Results: Sixty adolescents were randomized (76% recruitment rate; 94% of participants were retained from baseline to follow-up). Most adolescents (73%) and their parents/guardians (76%) reported that the trial was enjoyable. While there was no effect of arm on change in MVPA, sedentary behavior, or cardiorespiratory fitness for the entire sample, among those who engaged in <21 min of MVPA on average at baseline, adolescents in the CHD-PAL intervention had an increase of 16 min/day of MVPA more than comparators (d = 0.90). Conclusions: The CHD-PAL intervention warrants examination in a larger trial to establish efficacy among those adolescents with a congenital heart defect who engage in <21 min of MVPA/day and should include follow-up assessments to examine effect durability.

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A randomized controlled trial of the effect of supervised exercise on functional outcomes in older African American and non-Hispanic White breast cancer survivors: Are there racial differences in the effects of exercise on functional outcomes? (2022)

Cancer

Authors: Owusu, Cynthia; Margevicius, Seunghee; Nock, Nora L.; Austin, Kristina; Bennet, Elizabeth; Ld, Rd; Cerne, Stephen; Acs-Cet, Acsm; Paul Hergenroeder; Halle; Moore, C. F.; Petkac, Jean; Schluchter; Mark; Schmitz, Kathryn H.; Monica; Hooper, Webb; Wimbley; Leonard; Ma, Ba /; Berger, Nathan A.

Abstract

BACKGROUND: The objective of this study was to test the hypothesis that exercise would be more effective than a support group plus Fitbit (SG+Fitbit) program in improving functional outcomes in older breast cancer survivors (BCSs) and that race would moderate the exercise effect on outcomes. METHODS: Older African American (AA) and non-Hispanic White (NHW) BCSs were purposively recruited and enrolled into the 52-week randomized controlled trial. The interventions included 20 weeks of supervised moderate-intensity aero-bic and resistance training followed by 32 weeks of unsupervised exercise called IMPROVE (n = 108) and a 20-week SG+Fitbit program followed by 32 weeks of unsupervised activity (n = 105). Study outcomes were assessed at 20 and 52 weeks. The primary outcome was the change in Short Physical Performance Battery (SPPB) scores 20 weeks from the baseline between arms. Secondary outcomes included change in the 6-Minute Walk Test (6MWT) in meters 20 weeks from the baseline between arms. General linear regression and multivariable logistic regression analyses were used. RESULTS: The mean age was 71.9 years (SD, 5.9 years), and 44% were AA. SPPB scores did not differ between arms (adjusted difference in mean change, 0.13; 95% CI,-0.28 to 0.55; P = .53). However, the exercise arm (vs the SG+Fitbit arm) improved on the 6MWT (21.6 m; 95% CI, 2.5-40.6 m; P = .03). Race moderated the exercise effect on the 6MWT (adjusted interaction effect, 43.3 m; 95% CI, 6.3-80.2 m; P = .02); this implied that the change in the adjusted mean for the 6MWT at 20 weeks from the baseline was 43.3 m higher in AA exercise participants versus NHW exercise participants. CONCLUSIONS: Combined aerobic and resistance exercise appears to improve physical performance in older BCSs, and the exercise effect might be moderated by race, with AAs appearing to derive larger benefits in comparison with NHWs. Larger studies are warranted to confirm the study findings. Cancer 2022;0:1-19.

A randomized, double-blind, placebo-controlled trial investigating the effects of an Ocimum tenuiflorum (Holy Basil) extract (HolixerTM) on stress, mood, and sleep in adults experiencing stress (2022)

Frontiers in Nutrition

Authors: Lopresti, Adrian L.; Smith, Stephen J.; Metse, Alexandra P.; Drummond, Peter D.

Abstract

Background: In Ayurveda, Ocimum tenuiflorum (Holy Basil) is referred to as "the elixir of life" and is believed to promote longevity and general wellbeing. Although limited, there are clinical trials to suggest Ocimum tenuiflorum has anti-stress effects. Purpose: Examine the effects of a standardized Ocimum tenuiflorum extract (HolixerTM) on subjective and objective measures of stress and sleep quality in adults experiencing stress. Study design: Two-arm, parallel-group, 8-week, randomized, double-blind, placebo-controlled trial. Australian and New Zealand Clinical Trials Registry trial registration number ACTRN12621000609853. Methods: One hundred volunteers aged 18-65 years received either 125 mg of Ocimum tenuiflorum twice daily or a placebo. Outcome measures included the Perceived Stress Scale (PSS) (primary outcome measure), Profile of Mood States, Athens Insomnia Scale (AIS), Restorative Sleep Questionnaire, and the Patient-Reported Outcomes Measurement Information System-29. Sleep quality was also assessed using a wrist-worn sleep tracker (Fitbit), and stress changes were examined by measuring between-group differences in hair cortisol and stress responses after exposure to an experiment stress procedure known as the Maastricht Acute Stress Test (MAST). Results: Compared to the placebo, Ocimum tenuiflorum supplementation was associated with greater improvements in PSS (p = 0.003) and AIS (p = 0.025) scores; and at week 8, concentrations in hair cortisol were also lower (p = 0.025). Moreover, Ocimum tenuiflorum supplementation was associated with a buffered stress responses after exposure to the MAST as demonstrated by significantly lower concentrations in salivary cortisol (p = 0.001), salivary amylase (p = 0.001), systolic (p = 0.010) and diastolic (p = 0.025) blood pressure, and subjective stress ratings (p < 0.001). Ocimum tenuiflorum supplementation was well-tolerated with no reports of major adverse effects. Conclusion: The results from this trial suggest that 8 weeks of supplementation with an Ocimum tenuiflorum extract (HolixerTM) may reduce objective and subjective measures of stress, and improve subjective measures of sleep quality. However, further research using gold-standard objective sleep measures will be required to substantiate the sleep-related findings.

A Remote Health Coaching, Text-Based Walking Program in Ethnic Minority Primary Care Patients With Overweight and Obesity: Feasibility and Acceptability Pilot Study (2022)

JMIR formative research

Authors: Smart, Mary H.; Nabulsi, Nadia A.; Gerber, Ben S.; Gupta, Itika; Di Eugenio, Barbara; Ziebart, Brian; Sharp, Lisa K.

Abstract

Background: Over half of US adults have at least one chronic disease, including obesity. Although physical activity is an important component of chronic disease self-management, few reach the recommended physical activity goals. Individuals who identify as racial and ethnic minorities are disproportionally affected by chronic diseases and physical inactivity. Interventions using consumer-based wearable devices have shown promise for increasing physical activity among patients with chronic diseases; however, populations with the most to gain, such as minorities, have been poorly represented to date. Objective: This study aims to assess the feasibility, acceptability, and preliminary outcomes of an 8-week text-based coaching and Fitbit program aimed at increasing the number of steps in a predominantly overweight ethnic minority population. Methods: Overweight patients (BMI >25 kg/m2) were recruited from an internal medicine clinic located in an inner-city academic medical center. Fitbit devices were provided. Using 2-way SMS text messaging, health coaches (HCs) guided patients to establish weekly step goals that were specific, measurable, attainable, realistic, and time-bound. SMS text messaging and Fitbit activities were managed using a custom-designed app. Program feasibility was assessed via the recruitment rate, retention rate (the proportion of eligible participants completing the 8-week program), and patient engagement (based on the number of weekly text message goals set with the HC across the 8-week period). Acceptability was assessed using a qualitative, summative evaluation. Exploratory statistical analysis included evaluating the average weekly steps in week 1 compared with week 8 using a paired t test (2-tailed) and modeling daily steps over time using a linear mixed model. Results: Of the 33 patients initially screened; 30 (91%) patients were enrolled in the study. At baseline, the average BMI was 39.3 (SD 9.3) kg/m2, with 70% (23/33) of participants presenting as obese. A total of 30% (9/30) of participants self-rated their health as either fair or poor, and 73% (22/30) of participants set up ≥6 weekly goals across the 8-week program. In total, 93% (28/30) of participants completed a qualitative summative evaluation, and 10 themes emerged from the evaluation: patient motivation, convenient SMS text messaging experience, social support, supportive accountability, technology support, self-determined goals, achievable goals, feedback from Fitbit, challenges, and habit formation. There was no significant group change in the average weekly steps for week 1 compared with week 8 (mean difference 7.26, SD 6209.3; P=.99). However, 17% (5/30) of participants showed a significant increase in their daily steps. Conclusions: Overall, the results demonstrate the feasibility and acceptability of a remotely delivered walking study that included an HC; SMS text messaging; a wearable device (Fitbit); and specific, measurable, attainable, realistic, and time-bound goals within an ethnic minority patient population. Results support further development and testing in larger samples to explore efficacy.

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A Remotely Delivered Progressive Walking Intervention for Adults With Persistent Symptoms of a Mild Traumatic Brain Injury: Feasibility and Exploration of Its Impact (2022)

Frontiers in Rehabilitation Sciences

Authors: Alarie, Christophe; Gagnon, Isabelle; de Guise, Elaine; McKerral, Michelle; Kersalé, Marietta; Hoog, Béatrice van Het; Swaine, Bonnie

Abstract

Introduction: Persistent post-concussion symptoms following a mild traumatic brain injury (mTBI) can impact function and participation of adults. Physical activity is recommended to reduce symptoms and foster return to normal activities. Adults with a mTBI may have personal factors or experience accessibility issues restricting physical activity. Walking is a physical activity accessible to most that could be delivered remotely. Objectives: Determine the feasibility, safety, and acceptability of a remotely delivered progressive walking intervention designed for adults with persistent mTBI symptoms and explore its effects on health-related outcomes. Methodology: This feasibility study using a single-group pre-post mixed methods convergent parallel design was conducted remotely. Adults aged 18-65 years with a mTBI reporting persistent symptoms for ≥3 months were recruited. The 8-week remote progressive walking intervention aimed to increase the weekly number of steps walked by 40\% based on a 1-week baseline measured by a Fitbit Inspire 2 activity monitor. Feasibility measures were about the intervention, its remote delivery, safety, and acceptability. Health-related outcomes were post-concussion symptoms, kinesiophobia, mood, sleep, fatigue, and quality of life. Semi-structured exit interviews were recorded and transcribed verbatim. Quantitative and qualitative data were analyzed separately, and results merged, compared, and contrasted. Descriptive statistics and paired samples t-tests were used. The qualitative analyses followed an iterative content analysis approach using reflexivity and triangulation of sources. Results: Twenty adults (16 women) aged 42.5 ± 11.51 years with persisting symptoms for 9.25 ± 6.43 months participated, adhered to 94.38\% of sessions, completed the intervention, and found it to be feasible, safe and acceptable. Participants increased weekly total number of steps walked (change = 14,886 ± 18,283; t = 3.55, p = 0.002). Severity of post-concussion symptoms (change = -6.42 ± 10.69; t = -2.62, p = 0.018), kinesiophobia (change = -5 ± 6.86; t = 3.18, p = 0.005), anxiety (change = -1.53 ± 3.01; t = -2.21, p = 0.04), and fatigue (change = -10.21 ± 10.20; t = -4.37, p {\textless} 0.001) were reduced, whilst quality of life improved (change = 10.58 ± 13.35; t = 3.46, p = 0.003). Participants' perceptions corroborate most quantitative results; they felt improved self-efficacy about physical activity and provided five key recommendations. Discussion: This study demonstrates the feasibility, safety, and acceptability of the remote 8-week progressive walking intervention, a promising approach to reduce persisting symptoms, improve physical activity level health-related outcomes and quality of life of adults with persistent post-concussion symptoms following a mTBI.

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A Smartphone Physical Activity App for Patients in Alcohol Treatment: Single-Arm Feasibility Trial (2022)

JMIR Formative Research

Authors: Abrantes, Ana M.; Meshesha, Lidia Z.; Blevins, Claire E.; Battle, Cynthia L.; Lindsay, Clifford; Marsh, Eliza; Feltus, Sage; Buman, Matthew; Agu, Emmanuel; Stein, Michael

Abstract

Background: Alcohol use disorder (AUD) is a significant public health concern worldwide. Alcohol consumption is a leading cause of death in the United States and has a significant negative impact on individuals and society. Relapse following treatment is common, and adjunct intervention approaches to improve alcohol outcomes during early recovery continue to be critical. Interventions focused on increasing physical activity (PA) may improve AUD treatment outcomes. Given the ubiquity of smartphones and activity trackers, integrating this technology into a mobile app may be a feasible, acceptable, and scalable approach for increasing PA in individuals with AUD. Objective: This study aims to test the Fit\&Sober app developed for patients with AUD. The goals of the app were to facilitate self-monitoring of PA engagement and daily mood and alcohol cravings, increase awareness of immediate benefits of PA on mood and cravings, encourage setting and adjusting PA goals, provide resources and increase knowledge for increasing PA, and serve as a resource for alcohol relapse prevention strategies. Methods: To preliminarily test the Fit\&Sober app, we conducted an open pilot trial of patients with AUD in early recovery (N=22; 13/22, 59\% women; mean age 43.6, SD 11.6 years). At the time of hospital admission, participants drank 72\% of the days in the last 3 months, averaging 9 drinks per drinking day. The extent to which the Fit\&Sober app was feasible and acceptable among patients with AUD during early recovery was examined. Changes in alcohol consumption, PA, anxiety, depression, alcohol craving, and quality of life were also examined after 12 weeks of app use. Results: Participants reported high levels of satisfaction with the Fit\&Sober app. App metadata suggested that participants were still using the app approximately 2.5 days per week by the end of the intervention. Pre-post analyses revealed small-to-moderate effects on increase in PA, from a mean of 5784 (SD 2511) steps per day at baseline to 7236 (SD 3130) steps per day at 12 weeks (Cohen d=0.35). Moderate-to-large effects were observed for increases in percentage of abstinent days (Cohen d=2.17) and quality of life (Cohen d=0.58) as well as decreases in anxiety (Cohen d=−0.71) and depression symptoms (Cohen d=−0.58). Conclusions: The Fit\&Sober app is an acceptable and feasible approach for increasing PA in patients with AUD during early recovery. A future randomized controlled trial is necessary to determine the efficacy of the Fit\&Sober app for long-term maintenance of PA, ancillary mental health, and alcohol outcomes. If the efficacy of the Fit\&Sober app could be established, patients with AUD would have a valuable adjunct to traditional alcohol treatment that can be delivered in any setting and at any time, thereby improving the overall health and well-being of this population. Trial Registration: ClinicalTrials.gov NCT02958280; https://www.clinicaltrials.gov/ct2/show/NCT02958280

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A Smartwatch Step-Counting App for Older Adults: Development and Evaluation Study (2022)

JMIR aging

Authors: Boateng, George; Petersen, Curtis L.; Kotz, David; Fortuna, Karen L.; Masutani, Rebecca; Batsis, John A.

Abstract

Background: Older adults who engage in physical activity can reduce their risk of mobility impairment and disability. Short amounts of walking can improve quality of life, physical function, and cardiovascular health. Various programs have been implemented to encourage older adults to engage in physical activity, but sustaining their motivation continues to be a challenge. Ubiquitous devices, such as mobile phones and smartwatches, coupled with machine-learning algorithms, can potentially encourage older adults to be more physically active. Current algorithms that are deployed in consumer devices (eg, Fitbit) are proprietary, often are not tailored to the movements of older adults, and have been shown to be inaccurate in clinical settings. Step-counting algorithms have been developed for smartwatches, but only using data from younger adults and, often, were only validated in controlled laboratory settings. Objective: We sought to develop and validate a smartwatch step-counting app for older adults and evaluate the algorithm in free-living settings over a long period of time. Methods: We developed and evaluated a step-counting app for older adults on an open-source wrist-worn device (Amulet). The app includes algorithms to infer the level of physical activity and to count steps. We validated the step-counting algorithm in the lab (counting steps from a video recording, n=20) and in free-living conditions-one 2-day field study (n=6) and two 12-week field studies (using the Fitbit as ground truth, n=16). During app system development, we evaluated 4 walking patterns: normal, fast, up and down a staircase, and intermittent speed. For the field studies, we evaluated 5 different cut-off values for the algorithm, using correlation and error rate as the evaluation metrics. Results: The step-counting algorithm performed well. In the lab study, for normal walking (R2=0.5), there was a stronger correlation between the Amulet steps and the video-validated steps; for all activities, the Amulet's count was on average 3.2 (2.1%) steps lower (SD 25.9) than the video-validated count. For the 2-day field study, the best parameter settings led to an association between Amulet and Fitbit (R2=0.989) and 3.1% (SD 25.1) steps lower than Fitbit, respectively. For the 12-week field study, the best parameter setting led to an R2 value of 0.669. Conclusions: Our findings demonstrate the importance of an iterative process in algorithm development before field-based deployment. This work highlights various challenges and insights involved in developing and validating monitoring systems in real-world settings. Nonetheless, our step-counting app for older adults had good performance relative to the ground truth (a commercial Fitbit step counter). Our app could potentially be used to help improve physical activity among older adults.

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Accuracy and Acceptability of Wrist-Wearable Activity-Tracking Devices: Systematic Review of the Literature (2022)

Journal of medical Internet research

Authors: Germini, Federico; Noronha, Noella; Borg Debono, Victoria; Abraham Philip, Binu; Pete, Drashti; Navarro, Tamara; Keepanasseril, Arun; Parpia, Sameer; de Wit, Kerstin; Iorio, Alfonso

Abstract

Background: Numerous wrist-wearable devices to measure physical activity are currently available, but there is a need to unify the evidence on how they compare in terms of acceptability and accuracy. Objective: The aim of this study is to perform a systematic review of the literature to assess the accuracy and acceptability (willingness to use the device for the task it is designed to support) of wrist-wearable activity trackers. Methods: We searched MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, and SPORTDiscus for studies measuring physical activity in the general population using wrist-wearable activity trackers. We screened articles for inclusion and, for the included studies, reported data on the studies' setting and population, outcome measured, and risk of bias. Results: A total of 65 articles were included in our review. Accuracy was assessed for 14 different outcomes, which can be classified in the following categories: count of specific activities (including step counts), time spent being active, intensity of physical activity (including energy expenditure), heart rate, distance, and speed. Substantial clinical heterogeneity did not allow us to perform a meta-analysis of the results. The outcomes assessed most frequently were step counts, heart rate, and energy expenditure. For step counts, the Fitbit Charge (or the Fitbit Charge HR) had a mean absolute percentage error (MAPE) <25% across 20 studies. For heart rate, the Apple Watch had a MAPE <10% in 2 studies. For energy expenditure, the MAPE was >30% for all the brands, showing poor accuracy across devices. Acceptability was most frequently measured through data availability and wearing time. Data availability was ≥75% for the Fitbit Charge HR, Fitbit Flex 2, and Garmin Vivofit. The wearing time was 89% for both the GENEActiv and Nike FuelBand. Conclusions: The Fitbit Charge and Fitbit Charge HR were consistently shown to have a good accuracy for step counts and the Apple Watch for measuring heart rate. None of the tested devices proved to be accurate in measuring energy expenditure. Efforts should be made to reduce the heterogeneity among studies.

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Accuracy and Precision of Energy Expenditure, Heart Rate, and Steps Measured by Combined-Sensing Fitbits Against Reference Measures: Systematic Review and Meta-analysis (2022)

JMIR mHealth and uHealth

Authors: Chevance, Guillaume; Golaszewski, Natalie M.; Tipton, Elizabeth; Hekler, Eric B.; Buman, Matthew; Welk, Gregory; Patrick, Kevin; Godino, Job G.

Abstract

Background: Although it is widely recognized that physical activity is an important determinant of health, assessing this complex behavior is a considerable challenge. Objective: The purpose of this systematic review and meta-analysis is to examine, quantify, and report the current state of evidence for the validity of energy expenditure, heart rate, and steps measured by recent combined-sensing Fitbits. Methods: We conducted a systematic review and Bland-Altman meta-analysis of validation studies of combined-sensing Fitbits against reference measures of energy expenditure, heart rate, and steps. Results: A total of 52 studies were included in the systematic review. Among the 52 studies, 41 (79%) were included in the meta-analysis, representing 203 individual comparisons between Fitbit devices and a criterion measure (ie, n=117, 57.6% for heart rate; n=49, 24.1% for energy expenditure; and n=37, 18.2% for steps). Overall, most authors of the included studies concluded that recent Fitbit models underestimate heart rate, energy expenditure, and steps compared with criterion measures. These independent conclusions aligned with the results of the pooled meta-analyses showing an average underestimation of -2.99 beats per minute (k comparison=74), -2.77 kcal per minute (k comparison=29), and -3.11 steps per minute (k comparison=19), respectively, of the Fitbit compared with the criterion measure (results obtained after removing the high risk of bias studies; population limit of agreements for heart rate, energy expenditure, and steps: -23.99 to 18.01, -12.75 to 7.41, and -13.07 to 6.86, respectively). Conclusions: Fitbit devices are likely to underestimate heart rate, energy expenditure, and steps. The estimation of these measurements varied by the quality of the study, age of the participants, type of activities, and the model of Fitbit. The qualitative conclusions of most studies aligned with the results of the meta-analysis. Although the expected level of accuracy might vary from one context to another, this underestimation can be acceptable, on average, for steps and heart rate. However, the measurement of energy expenditure may be inaccurate for some research purposes.

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Activity monitoring and patient-reported outcome measures in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome patients (2022)

PloS One

Authors: Rekeland, Ingrid G.; Sørland, Kari; Bruland, Ove; Risa, Kristin; Alme, Kine; Dahl, Olav; Tronstad, Karl J.; Mella, Olav; Fluge, Øystein

Abstract

INTRODUCTION: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a disease with no validated specific and sensitive biomarker, and no standard approved treatment. In this observational study with no intervention, participants used a Fitbit activity tracker. The aims were to explore natural symptom variation, feasibility of continuous activity monitoring, and to compare activity data with patient reported outcome measures (PROMs). MATERIALS AND METHODS: In this pilot study, 27 patients with mild to severe ME/CFS, of mean age 42.3 years, used the Fitbit Charge 3 continuously for six months. Patients wore a SenseWear activity bracelet for 7 days at baseline, at 3 and 6 months. At baseline and follow-up they completed the Short Form 36 Health Survey (SF-36) and the DePaul Symptom Questionnaire-Short Form (DSQ-SF). RESULTS: The mean number of steps per day decreased with increasing ME/CFS severity; mild 5566, moderate 4991 and severe 1998. The day-by-day variation was mean 47\% (range 25\%-79\%). Mean steps per day increased from the first to the second three-month period, 4341 vs 4781 steps, p = 0.022. The maximum differences in outcome measures between 4-week periods (highest vs lowest), were more evident in a group of eight patients with milder disease (baseline SF-36 PF {\textgreater} 50 or DSQ-SF {\textless} 55) as compared to 19 patients with higher symptom burden (SF-36 PF {\textless} 50 and DSQ-SF {\textgreater} 55), for SF-36 PF raw scores: 16.9 vs 3.4 points, and for steps per day: 958 versus 479 steps. The correlations between steps per day and self-reported SF-36 Physical function, SF-36 Social function, and DSQ-SF were significant. Fitbit recorded significantly higher number of steps than SenseWear. Resting heart rates were stable during six months. CONCLUSION: Continuous activity registration with Fitbit Charge 3 trackers is feasible and useful in studies with ME/CFS patients to monitor steps and resting heart rate, in addition to self-reported outcome measures. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov: NCT04195815.

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Adverse Effects of Sit and Stand Workstations on the Health Outcomes of Assembly Line Workers: A Cross-sectional Study (2022)

Journal of Preventive Medicine and Hygiene

Authors: Moshref Javadi, Amir-Milad; Choobineh, Alireza; Razeghi, Mohsen; Ghaem, Haleh; Daneshmandi, Hadi

Abstract

INTRODUCTION: Sitting and standing workstations can affect individual's health outcomes differently. This study aimed to assess the effects of sit and stand workstations on energy expenditure and blood parameters, including glucose and triglyceride, musculoskeletal symptoms/pain and discomfort, fatigue, and productivity among workers of assembly line of a belt factory. METHODS: This cross-sectional study was conducted on 47 male assembly line workers (24 workers in sitting workstation and 23 workers in standing workstation) with at least one year of working experience. Data were gathered via demographic/occupational characteristics, Fitbit system, medical records, the Persian version of the Nordic Musculoskeletal Questionnaire (P-NMQ), the Persian version of the Numeric Rating Scale (P-NRS), the Persian version of the Swedish Occupational Fatigue (P-SOFI), and Persian version of the Health and Work Questionnaire (P-HWQ). RESULTS: The results showed that there were no statistically significant between the demographic/occupational details of the participants in sitting and standing groups, except work experience. The findings of the present study revealed that the energy expenditure, and blood glucose/triglyceride there are not statistically differences between sitting and standing groups. In addition, the prevalence of musculoskeletal symptoms in the neck, lower back, knees, and ankles/feet in standing group was significantly higher than the sitting group. The means of severity of discomfort/pain in all body regions were significantly higher in standing group compared to other group. Generally, occupational fatigue was higher among the standing group compared to sitting group. About productivity, the 'concentration/focus' and 'impatience/irritability' subscales in sitting group were higher than the standing group. Contrariwise, other subscales of the productivity, including 'productivity', 'supervisor relations', 'non-work satisfaction', 'work satisfaction' in the standing group were higher than the sitting group. CONCLUSIONS: To reduce the adverse effects of sitting and standing workstations on individual's health outcomes, planning to use sit-stand workstations is recommended.

Associations of COVID-19 lockdown restrictions with longer-term activity levels of working adults with type 2 diabetes (2022)

JMIR diabetes

Authors: Brakenridge, Christian; Salim, Agus; Healy, Genevieve Nissa; Grigg, Ruth; Carver, Alison; Rickards, Kym; Owen, Neville; Dunstan, David

Abstract

Background: Lockdown restrictions reduce COVID-19 community transmission; however, they may pose challenges for non-communicable disease management. A 112-day hard lockdown in Victoria, Australia (commencing March 23, 2020), coincided with an intervention trial of reducing and breaking up sitting time in desk workers with type 2 diabetes who were using a provided consumer grade activity tracker (Fitbit). Objective: To compare continuously recorded activity levels preceding and during COVID-19 lockdown restrictions among working adults with type 2 diabetes participating in a sitting less and moving more intervention. Methods: Eleven participants (8/11 male; mean [SD] age 52.8 [5.0] years) in Melbourne, Australia had Fitbit activity tracked before (mean [SD]: 122.7 [47.9] days) and during (99.7 [62.5] days) city-wide COVID-19 lockdown restrictions. Regression models compared device (Fitbit Inspire HR)-derived activity (steps; METs [metabolic equivalents], mean time in sedentary, lightly, fairly, and very active minutes, and usual bout durations) during restrictions, to pre-restriction. Changes in activity were statistically significant when estimates (Δ%) did not intercept zero. Results: Overall, there was a decrease in mean: steps (-1,584 steps/day; Δ% : 9%; 95%CI: -11, -7); METs (-83 METs/day; Δ% : -5%; 95%CI: -6, -5); and, lightly active (Δ% : -4%; 95%CI: -8, -1), fairly active (Δ% : -8%; 95%CI: -21, -15), and very active (Δ% : -8%; 95%CI: -11, -5) intensity minutes per day, and increases in mean sedentary minutes per day (+51 mins/day; Δ% : +3%; 95%CI: 1, 6). Only very active (+5.1 mins) and sedentary (+4.3 mins) bout durations changed significantly. Conclusions: In a convenience sample of adults with type 2 diabetes, COVID-19 lockdown restrictions were associated with decreases in overall activity levels and increases in very active and sedentary bout durations. A Fitbit monitor provided meaningful continuous long-term data in this context.

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Commercial Devices Provide Estimates of Energy Balance with Varying Degrees of Validity in Free-Living Adults (2022)

The Journal of nutrition

Authors: Shook, Robin P.; Yeh, Hung Wen; Welk, Gregory J.; Davis, Ann M.; Ries, Daniel

Abstract

Background: The challenges of accurate estimation of energy intake (EI) are well-documented, with self-reported values 12%-20% below expected values. New approaches rely on gold-standard assessments of the other components of energy balance, energy expenditure (EE) and energy storage (ES), to estimate EI. Objectives: The purpose of this study was to evaluate the validity, repeatability, and measurement error of consumer devices when estimating energy balance in a free-living population. Methods: Twenty-four healthy adults (14 women, 10 men; mean ± SD age: 30.7 ± 8.2 y) completed two 14-d assessment periods, including assessments of EE and ES using gold-standard [doubly labeled water (DLW) and DXA] and commercial devices [Fitbit Alta HR activity monitor (Alta) and Fitbit Aria wireless body composition scale (Aria)], and of EI by dietician-administered recalls. Accuracy and validity were assessed using Spearman correlation, interclass correlation, mean absolute percentage error, and equivalency testing. We also applied linear measurement error modeling including error in gold-standard devices and within-subject repeated-measures design to calibrate consumer devices and quantify error. Results: There was moderate to strong agreement for EE between the Fitbit Alta and DLW at each time point (rs = 0.82 and 0.66 for Times 1 and 2, respectively). There was weak agreement for ES between the Fitbit Aria and DXA (rs = 0.15 and 0.49 for Times 1 and 2, respectively). Correlations between methods to assess EI ranged from weak to strong, with agreement between the DXA/DLW-calculated EI and dietary recalls being the highest (rs = 0.63 for Time 1 and 0.73 for Time 2). Only EE from the Fitbit Alta at Time 1 was equivalent to the DLW value using equivalency testing. Conclusions: Commercial devices provide estimates of energy balance in free-living adults with varying degrees of validity compared to gold-standard techniques. EE estimates were the most robust overall, whereas ES estimates were generally poor.

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Comparing a Fitbit Wearable to an Electrocardiogram Gold Standard as a Measure of Heart Rate Under Psychological Stress: A Validation Study (2022)

JMIR formative research

Authors: Gagnon, Joel; Khau, Michelle; Lavoie-Hudon, Léandre; Vachon, François; Drapeau, Vicky; Tremblay, Sébastien

Abstract

BACKGROUND: Wearable devices collect physiological and behavioral data that have the potential to identify individuals at risk of declining mental health and well-being. Past research has mainly focused on assessing the accuracy and the agreement of heart rate (HR) measurement of wearables under different physical exercise conditions. However, the capacity of wearables to sense physiological changes, assessed by increasing HR, caused by a stressful event has not been thoroughly studied. OBJECTIVE: This study followed 3 objectives: (1) to test the ability of a wearable device (Fitbit Versa 2) to sense an increase in HR upon induction of psychological stress in the laboratory; (2) to assess the accuracy of the wearable device to capture short-term HR variations caused by psychological stress compared to a gold-standard electrocardiogram (ECG) measure (Biopac); and (3) to quantify the degree of agreement between the wearable device and the gold-standard ECG measure across different experimental conditions. METHODS: Participants underwent the Trier Social Stress Test protocol, which consists of an oral phase, an arithmetic stress phase, an anticipation phase, and 2 relaxation phases (at the beginning and the end). During the stress protocol, the participants wore a Fitbit Versa 2 and were also connected to a Biopac. A mixed-effect modeling approach was used (1) to assess the effect of experimental conditions on HR, (2) to estimate several metrics of accuracy, and (3) to assess the agreement: the Bland-Altman limits of agreement (LoA), the concordance correlation coefficient, the coverage probability, the total deviation index, and the coefficient of an individual agreement. Mean absolute error and mean absolute percent error were calculated as accuracy indices. RESULTS: A total of 34 university students were recruited for this study (64\% of participants were female with a mean age of 26.8 years, SD 8.3). Overall, the results showed significant HR variations across experimental phases. Post hoc tests revealed significant pairwise differences for all phases. Accuracy analyses revealed acceptable accuracy according to the analyzed metrics of accuracy for the Fitbit Versa 2 to capture the short-term variations in psychological stress levels. However, poor indices of agreement between the Fitbit Versa 2 and the Biopac were found. CONCLUSIONS: Overall, the results support the use of the Fitbit Versa 2 to capture short-term stress variations. The Fitbit device showed acceptable levels of accuracy but poor agreement with an ECG gold standard. Greater inaccuracy and smaller agreement were found for stressful experimental conditions that induced a higher HR. Fitbit devices can be used in research to measure HR variations caused by stress, although they cannot replace an ECG instrument when precision is of utmost importance.

Concurrent and prospective associations between fitbit wearable-derived RDoC arousal and regulatory constructs and adolescent internalizing symptoms (2022)

Journal of child psychology and psychiatry, and allied disciplines

Authors: Nelson, Benjamin W.; Flannery, Jessica E.; Flournoy, John; Duell, Natasha; Prinstein, Mitchell J.; Telzer, Eva

Abstract

Background: Adolescence is characterized by alterations in biobehavioral functioning, during which individuals are at heightened risk for onset of psychopathology, particularly internalizing disorders. Researchers have proposed using digital technologies to index daily biobehavioral functioning, yet there is a dearth of research examining how wearable metrics are associated with mental health. Methods: We preregistered analyses using the Adolescent Brain Cognitive Development Study dataset using wearable data collection in 5,686 adolescents (123,862 person-days or 2,972,688 person-hours) to determine whether wearable indices of resting heart rate (RHR), step count, and sleep duration and variability in these measures were cross-sectionally associated with internalizing symptomatology. All models were also run controlling for age, sex, body mass index, socioeconomic status, and race. We then performed prospective analyses on a subset of this sample (n = 143) across 25 months that had Fitbit data available at baseline and follow-up in order to explore directionality of effects. Results: Cross-sectional analyses revealed a small, yet significant, effect size (R2 =.053) that higher RHR, lower step count and step count variability, and greater variability in sleep duration were associated with greater internalizing symptoms. Cross-lagged panel model analysis revealed that there were no prospective associations between wearable variables and internalizing symptoms (partial R2 =.026), but greater internalizing symptoms and higher RHR predicted lower step count 25 months later (partial R2 =.010), while higher RHR also predicted lower step count variability 25 months later (partial R2 =.008). Conclusions: Findings indicate that wearable indices concurrently associate with internalizing symptoms during early adolescence, while a larger sample size is likely required to accurately assess prospective or directional effects between wearable indices and mental health. Future research should capitalize on the temporal resolution provided by wearable devices to determine the intensive longitudinal relations between biobehavioral risk factors and acute changes in mental health.

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Consistency With and Disengagement From Self-monitoring of Weight, Dietary Intake, and Physical Activity in a Technology-Based Weight Loss Program: Exploratory Study (2022)

JMIR formative research

Authors: Carpenter, Chelsea A.; Eastman, Abraham; Ross, Kathryn M.

Abstract

Background: Digital self-monitoring tools offer promise to improve adherence to self-monitoring of weight and weight-related behaviors; however, less is known regarding the patterns of participant consistency and disengagement with these tools. Objective: This study characterizes the consistency of use and time to disengagement with digital self-monitoring tools during a 6-month weight loss intervention and investigates whether the provision of phone-based intervention improved self-monitoring adherence. Methods: Participants were 54 adults with overweight or obesity (mean age 49.6 years, SD 12.4 years; mean BMI 32.6 kg/m2, SD 3.2 kg/m2) enrolled in a pilot trial assessing the impact of self-monitoring technology (Fitbit Zip, Aria scale, and smartphone app), with and without additional interventionist contact, on weight loss. All participants received weight loss education and were asked to self-monitor weight, dietary intake, and physical activity daily throughout the 6-month program. Consistency was defined as the number of weeks that participants adhered to self-monitoring recommendations (7 out of 7 days). Disengagement was defined as the first of 2 consecutive weeks that the 7-day self-monitoring adherence goal was not met. Wilcoxon signed-rank tests were used to examine differences in consistency and disengagement by behavioral targets. t tests (2-tailed) and Cox proportional hazards models were used to examine whether providing additional interventionist contact would lead to significant improvements in consistency and time to disengagement from self-monitoring tools, respectively. Linear regressions were used to examine associations between consistency, time to disengagement, and weight loss. Results: Participants consistently self-monitored physical activity for more weeks (mean 17.4 weeks, SD 8.5 weeks) than weight (mean 11.1 weeks, SD 8.5 weeks) or dietary intake (mean 10.8 weeks, SD 8.7 weeks; P<.05). Similarly, participants had a significantly longer time to disengagement from self-monitoring of physical activity (median 19.5 weeks) than weight (4 weeks) or dietary intake (10 weeks; P<.001). Participants randomized to receive additional interventionist contact had significantly greater consistency and longer time to disengagement for self-monitoring of dietary intake compared with participants who did not (P=.006); however, there were no statistically significant differences between groups for self-monitoring of weight or physical activity (P=.24 and P=.25, respectively). Greater consistency and longer time to disengagement were associated with greater weight loss for self-monitoring of weight and dietary intake (P<.001 and P=.004, respectively) but not for physical activity (P=.57). Conclusions: Results demonstrated that self-monitoring adherence differed by behavioral target, with greater consistency and longer time to disengagement associated with lower-burden tools (ie, self-monitoring of physical activity). Consistent with supportive accountability theory, additional interventionist contact improved consistency and lengthened time to disengagement from self-monitoring of dietary intake. Given the observed associations between consistency, disengagement, and weight loss outcomes, it is important to identify additional methods of increasing consistency and engagement with digital self-monitoring tools.

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Continuous Monitoring of Vital Signs With Wearable Sensors During Daily Life Activities: Validation Study (2022)

JMIR formative research

Authors: Haveman, Marjolein E.; van Rossum, Mathilde C.; Vaseur, Roswita M. E.; van der Riet, Claire; Schuurmann, Richte C. L.; Hermens, Hermie J.; de Vries, Jean Paul P. M.; Tabak, Monique

Abstract

Background: Continuous telemonitoring of vital signs in a clinical or home setting may lead to improved knowledge of patients' baseline vital signs and earlier detection of patient deterioration, and it may also facilitate the migration of care toward home. Little is known about the performance of available wearable sensors, especially during daily life activities, although accurate technology is critical for clinical decision-making. Objective: The aim of this study is to assess the data availability, accuracy, and concurrent validity of vital sign data measured with wearable sensors in volunteers during various daily life activities in a simulated free-living environment. Methods: Volunteers were equipped with 4 wearable sensors (Everion placed on the left and right arms, VitalPatch, and Fitbit Charge 3) and 2 reference devices (Oxycon Mobile and iButton) to obtain continuous measurements of heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2), and temperature. Participants performed standardized activities, including resting, walking, metronome breathing, chores, stationary cycling, and recovery afterward. Data availability was measured as the percentage of missing data. Accuracy was evaluated by the median absolute percentage error (MAPE) and concurrent validity using the Bland-Altman plot with mean difference and 95% limits of agreement (LoA). Results: A total of 20 volunteers (median age 64 years, range 20-74 years) were included. Data availability was high for all vital signs measured by VitalPatch and for HR and temperature measured by Everion. Data availability for HR was the lowest for Fitbit (4807/13,680, 35.14% missing data points). For SpO2 measured by Everion, median percentages of missing data of up to 100% were noted. The overall accuracy of HR was high for all wearable sensors, except during walking. For RR, an overall MAPE of 8.6% was noted for VitalPatch and that of 18.9% for Everion, with a higher MAPE noted during physical activity (up to 27.1%) for both sensors. The accuracy of temperature was high for VitalPatch (MAPE up to 1.7%), and it decreased for Everion (MAPE from 6.3% to 9%). Bland-Altman analyses showed small mean differences of VitalPatch for HR (0.1 beats/min [bpm]), RR (−0.1 breaths/min), and temperature (0.5 °C). Everion and Fitbit underestimated HR up to 5.3 (LoA of −39.0 to 28.3) bpm and 11.4 (LoA of −53.8 to 30.9) bpm, respectively. Everion had a small mean difference with large LoA (−10.8 to 10.4 breaths/min) for RR, underestimated SpO2 (>1%), and overestimated temperature up to 2.9 °C. Conclusions: Data availability, accuracy, and concurrent validity of the studied wearable sensors varied and differed according to activity. In this study, the accuracy of all sensors decreased with physical activity. Of the tested sensors, VitalPatch was found to be the most accurate and valid for vital signs monitoring.

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Detailed Versus Simplified Dietary Self-monitoring in a Digital Weight Loss Intervention Among Racial and Ethnic Minority Adults: Fully Remote, Randomized Pilot Study (2022)

JMIR formative research

Authors: Patel, Michele L.; Cleare, Angel E.; Smith, Carly M.; Rosas, Lisa Goldman; King, Abby C.

Abstract

BACKGROUND: Detailed self-monitoring (or tracking) of dietary intake is a popular and effective weight loss approach that can be delivered via digital tools, although engagement declines over time. Simplifying the experience of self-monitoring diet may counteract this decline in engagement. Testing these strategies among racial and ethnic minority groups is important as these groups are often disproportionately affected by obesity yet underrepresented in behavioral obesity treatment. OBJECTIVE: In this 2-arm pilot study, we aimed to evaluate the feasibility and acceptability of a digital weight loss intervention with either detailed or simplified dietary self-monitoring. METHODS: We recruited racial and ethnic minority adults aged ≥21 years with a BMI of 25 kg/m2 to 45 kg/m2 and living in the United States. The Pacific time zone was selected for a fully remote study. Participants received a 3-month stand-alone digital weight loss intervention and were randomized 1:1 to either the detailed arm that was instructed to self-monitor all foods and drinks consumed each day using the Fitbit mobile app or to the simplified arm that was instructed to self-monitor only red zone foods (foods that are highly caloric and of limited nutritional value) each day via a web-based checklist. All participants were instructed to self-monitor both steps and body weight daily. Each week, participants were emailed behavioral lessons, action plans, and personalized feedback. In total, 12 a priori benchmarks were set to establish feasibility, including outcomes related to reach, retention, and self-monitoring engagement (assessed objectively via digital tools). Acceptability was assessed using a questionnaire. Weight change was assessed using scales shipped to the participants' homes and reported descriptively. RESULTS: The eligibility screen was completed by 248 individuals, of whom 38 (15.3\%) were randomized, 18 to detailed and 20 to simplified. At baseline, participants had a mean age of 47.4 (SD 14.0) years and BMI of 31.2 (SD 4.8) kg/m2. More than half (22/38, 58\%) were identified as Hispanic of any race. The study retention rate was 92\% (35/38) at 3 months. The detailed arm met 9 of 12 feasibility benchmarks, while the simplified arm met all 12. Self-monitoring engagement was moderate to high (self-monitoring diet: median of 49\% of days for detailed, 97\% for simplified; self-monitoring steps: 99\% for detailed, 100\% for simplified; self-monitoring weight: 67\% for detailed, 80\% for simplified). Participants in both arms reported high satisfaction, with 89\% indicating that they would recommend the intervention. Weight change was -3.4 (95\% CI -4.6 to -2.2) kg for detailed and -3.3 (95\% CI -4.4 to -2.2) kg for simplified. CONCLUSIONS: A digital weight loss intervention that incorporated either detailed or simplified dietary self-monitoring was feasible, with high retention and engagement, and acceptable to racial and ethnic minority adults. TRIAL REGISTRATION: ASPREDICTED \#66674; https://aspredicted.org/ka478.pdf.

Detection of Atrial Fibrillation in a Large Population Using Wearable Devices: The Fitbit Heart Study (2022)

Circulation

Authors: Lubitz, Steven A.; Faranesh, Anthony Z.; Selvaggi, Caitlin; Atlas, Steven J.; McManus, David D.; Singer, Daniel E.; Pagoto, Sherry; McConnell, Michael V.; Pantelopoulos, Alexandros; Foulkes, Andrea S.

Abstract

BACKGROUND: Morbidity from undiagnosed atrial fibrillation (AF) may be preventable with early detection. Many consumer wearables contain optical photoplethysmography (PPG) sensors to measure pulse rate. PPG-based software algorithms that detect irregular heart rhythms may identify undiagnosed AF in large populations using wearables, but minimizing false-positive detections is essential. METHODS: We performed a prospective remote clinical trial to examine a novel PPG-based algorithm for detecting undiagnosed AF from a range of wrist-worn devices. Adults aged ≥22 years in the United States without AF, using compatible wearable Fitbit devices and Android or iOS smartphones, were included. PPG data were analyzed using a novel algorithm that examines overlapping 5-minute pulse windows (tachograms). Eligible participants with an irregular heart rhythm detection (IHRD), defined as 11 consecutive irregular tachograms, were invited to schedule a telehealth visit and were mailed a 1-week ambulatory ECG patch monitor. The primary outcome was the positive predictive value of the first IHRD during ECG patch monitoring for concurrent AF. RESULTS: A total of 455 699 participants enrolled (median age 47 years, 71\% female, 73\% White) between May 6 and October 1, 2020. IHRDs occurred for 4728 (1\%) participants, and 2070 (4\%) participants aged ≥65 years during a median of 122 (interquartile range, 110-134) days were at risk for an IHRD. Among 1057 participants with an IHRD notification and subsequent analyzable ECG patch monitor, AF was present in 340 (32.2\%). Of the 225 participants with another IHRD during ECG patch monitoring, 221 had concurrent AF on the ECG and 4 did not, resulting in an IHRD positive predictive value of 98.2\% (95\% CI, 95.5\%-99.5\%). For participants aged ≥65 years, the IHRD positive predictive value was 97.0\% (95\% CI, 91.4\%-99.4\%). CONCLUSIONS: A novel PPG software algorithm for wearable Fitbit devices exhibited a high positive predictive value for concurrent AF and identified participants likely to have AF on subsequent ECG patch monitoring. Wearable devices may facilitate identifying individuals with undiagnosed AF. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT04380415.

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Digital phenotyping by wearable-driven artificial intelligence in older adults and people with Parkinson's disease: Protocol of the mixed method, cyclic ActiveAgeing study (2022)

PloS One

Authors: Torrado, Juan C.; Husebo, Bettina S.; Allore, Heather G.; Erdal, Ane; Fæø, Stein E.; Reithe, Haakon; Førsund, Elise; Tzoulis, Charalampos; Patrascu, Monica

Abstract

BACKGROUND: Active ageing is described as the process of optimizing health, empowerment, and security to enhance the quality of life in the rapidly growing population of older adults. Meanwhile, multimorbidity and neurological disorders, such as Parkinson's disease (PD), lead to global public health and resource limitations. We introduce a novel user-centered paradigm of ageing based on wearable-driven artificial intelligence (AI) that may harness the autonomy and independence that accompany functional limitation or disability, and possibly elevate life expectancy in older adults and people with PD. METHODS: ActiveAgeing is a 4-year, multicentre, mixed method, cyclic study that combines digital phenotyping via commercial devices (Empatica E4, Fitbit Sense, and Oura Ring) with traditional evaluation (clinical assessment scales, in-depth interviews, and clinical consultations) and includes four types of participants: (1) people with PD and (2) their informal caregiver; (3) healthy older adults from the Helgetun living environment in Norway, and (4) people on the Helgetun waiting list. For the first study, each group will be represented by N = 15 participants to test the data acquisition and to determine the sample size for the second study. To suggest lifestyle changes, modules for human expert-based advice, machine-generated advice, and self-generated advice from accessible data visualization will be designed. Quantitative analysis of physiological data will rely on digital signal processing (DSP) and AI techniques. The clinical assessment scales are the Unified Parkinson's Disease Rating Scale (UPDRS), Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale (GDS), Geriatric Anxiety Inventory (GAI), Apathy Evaluation Scale (AES), and the REM Sleep Behaviour Disorder Screening Questionnaire (RBDSQ). A qualitative inquiry will be carried out with individual and focus group interviews and analysed using a hermeneutic approach including narrative and thematic analysis techniques. DISCUSSION: We hypothesise that digital phenotyping is feasible to explore the ageing process from clinical and lifestyle perspectives including older adults and people with PD. Data is used for clinical decision-making by symptom tracking, predicting symptom evolution, and discovering new outcome measures for clinical trials.

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Evaluation of the Immediate Effects of Web-Based Intervention Modules for Goals, Planning, and Coping Planning on Physical Activity: Secondary Analysis of a Randomized Controlled Trial on Weight Loss Maintenance (2022)

Journal of medical Internet research

Authors: Mattila, Elina; Horgan, Graham; Palmeira, Antonio L.; O'Driscoll, Ruairi; Stubbs, R. James; Heitmann, Berit L.; Marques, Marta M.

Abstract

Background: The use of digital interventions can be accurately monitored via log files. However, monitoring engagement with intervention goals or enactment of the actual behaviors targeted by the intervention is more difficult and is usually evaluated based on pre-post measurements in a controlled trial. Objective: The objective of this paper is to evaluate if engaging with 2 digital intervention modules focusing on (1) physical activity goals and action plans and (2) coping with barriers has immediate effects on the actual physical activity behavior. Methods: The NoHoW Toolkit (TK), a digital intervention developed to support long-term weight loss maintenance, was evaluated in a 2 x 2 factorial randomized controlled trial. The TK contained various modules based on behavioral self-regulation and motivation theories, as well as contextual emotion regulation approaches, and involved continuous tracking of weight and physical activity through connected commercial devices (Fitbit Aria and Charge 2). Of the 4 trial arms, 2 had access to 2 modules directly targeting physical activity: a module for goal setting and action planning (Goal) and a module for identifying barriers and coping planning (Barriers). Module visits and completion were determined based on TK log files and time spent in the module web page. Seven physical activity metrics (steps; activity; energy expenditure; fairly active, very active and total active minutes; and distance) were compared before and after visiting and completing the modules to examine whether the modules had immediate or sustained effects on physical activity. Immediate effect was determined based on 7-day windows before and after the visit, and sustained effects were evaluated for 1 to 8 weeks after module completion. Results: Out of the 811 participants, 498 (61.4%) visited the Goal module and 406 (50.1%) visited the Barriers module. The Barriers module had an immediate effect on very active and total active minutes (very active minutes: before median 24.2, IQR 10.4-43.0 vs after median 24.9, IQR 10.0-46.3; P=.047; total active minutes: before median 45.1, IQR 22.9-74.9 vs after median 46.9, IQR 22.4-78.4; P=.03). The differences were larger when only completed Barriers modules were considered. The Barriers module completion was also associated with sustained effects in fairly active and total active minutes for most of the 8 weeks following module completion and for 3 weeks in very active minutes. Conclusions: The Barriers module had small, significant, immediate, and sustained effects on active minutes measured by a wrist-worn activity tracker. Future interventions should pay attention to assessing barriers and planning coping mechanisms to overcome them.

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Factors related to daily step counts of stroke patients during hospitalization in a convalescent rehabilitation ward (2022)

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association

Authors: Yamada, Ryuichiro; Shimizu, Shinobu; Suzuki, Yuta; Nakachi, Yuki; Takemura, Nami; Taira, Katsuya; Yamazato, Tomoya; Shimabukuro, Michiru; Tsunoda, Satoshi; Shimose, Ryota; Ogura, Misao; Higa, Jun; Nakanishi, Takayuki; Matsunaga, Atsuhiko

Abstract

Objectives: Clarifying the factors related to decreased physical activity in post-stroke patients is essential for effective disease management. This study aimed to examine the factors influencing the amount of daily steps taken by post-stroke patients in a convalescent rehabilitation ward during activities other than rehabilitation (non-rehabilitation steps). Materials and methods: Eighty-nine post-stroke patients (60.8±14.4 years; 55 men) were enrolled. The inclusion criteria were walking independently within the ward and having a walking speed of ≥24 m/min. Data on patient clinical characteristics including age, sex, body mass index, stroke type, hemiparetic side, and time from stroke onset were collected. Stroke impairment and motor and cognitive functional disabilities were assessed using the Stroke Impairment Assessment Set and the Functional Independence Measure, respectively. The non-rehabilitation steps were calculated by subtracting the steps during the rehabilitation activities from the total steps using Fitbit Flex2. Results: The average number of non-rehabilitation steps was 4,523±2,339 steps/day. The hierarchical multiple regression analysis revealed that sex, motor disability, and the interaction term of stroke impairment with cognitive disability were significantly related to non-rehabilitation steps. Simple slope analysis demonstrated that the stroke impairment slope was steeper at lower levels than at higher levels of cognitive disability for non-rehabilitation steps. Conclusions: In addition to independent effects of sex and motor disability, this study found that stroke impairment and cognitive disability were interactively related to non-rehabilitation steps in post-stroke patients in a convalescent rehabilitation ward. These findings may provide useful information for managing physical activity in post-stroke patients after hospital discharge.

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Feasibility and Acceptability of a Physical Activity Tracker and Text Messages to Promote Physical Activity During Chemotherapy for Colorectal Cancer: Pilot Randomized Controlled Trial (Smart Pace II) (2022)

JMIR cancer

Authors: Van Blarigan, Erin L.; Dhruva, Anand; Atreya, Chloe E.; Kenfield, Stacey A.; Chan, June M.; Milloy, Alexandra; Kim, Iris; Steiding, Paige; Laffan, Angela; Zhang, Li; Piawah, Sorbarikor; Fukuoka, Yoshimi; Miaskowski, Christine; Hecht, Frederick M.; Kim, Mi-Ok; Venook, Alan P.; Van Loon, Katherine

Abstract

Background: We conducted a pilot 2-arm randomized controlled trial to assess the feasibility of a digital health intervention to increase moderate-to-vigorous physical activity in patients with colorectal cancer (CRC) during chemotherapy. Objective: This study aimed to determine whether a digital health physical activity intervention is feasible and acceptable during chemotherapy for CRC. Methods: Potentially eligible patients with CRC expected to receive at least 12 weeks of chemotherapy were identified in person at the University of California, San Francisco, and on the web through advertising. Eligible patients were randomized 1:1 to a 12-week intervention (Fitbit Flex, automated SMS text messages) versus usual care. At 0 and 12 weeks, patients wore an Actigraph GT3X+ accelerometer for 7 days and completed surveys, body size measurements, and an optional 6-minute walk test. Participants could not be masked to their intervention arm, but people assessing the body size and 6-minute walk test outcomes were masked. The primary outcomes were adherence (eg, Fitbit wear and text response rate) and self-assessed acceptability of the intervention. The intervention would be considered feasible if we observed at least 80% complete follow-up and 70% adherence and satisfaction, a priori. Results: From 2018 to 2020, we screened 240 patients; 53.3% (128/240) of patients were ineligible and 26.7% (64/240) declined to participate. A total of 44 patients (44/240, 18%) were randomized to the intervention (n=22) or control (n=22) groups. Of these, 57% (25/44) were women; 68% (30/44) identified as White and 25% (11/44) identified as Asian American or Pacific Islander; and 77% (34/44) had a 4-year college degree. The median age at enrollment was 54 years (IQR 45-62 years). Follow-up at 12 weeks was 91% (40/44) complete. In the intervention arm, patients wore Fitbit devices on a median of 67 out of 84 (80%) study days and responded to a median of 17 out of 27 (63%) questions sent via SMS text message. Among 19 out of 22 (86%) intervention patients who completed the feedback survey, 89% (17/19) were satisfied with the Fitbit device; 63% (12/19) were satisfied with the SMS text messages; 68% (13/19) said the SMS text messages motivated them to exercise; 74% (14/19) said the frequency of SMS text messages (1-3 days) was ideal; and 79% (15/19) said that receiving SMS text messages in the morning and evening was ideal. Conclusions: This pilot study demonstrated that many people receiving chemotherapy for CRC are interested in participating in digital health physical activity interventions. Fitbit adherence was high; however, participants indicated a desire for more tailored SMS text message content. Studies with more socioeconomically diverse patients with CRC are required.

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Feasibility and Acceptability of a Preoperative Multimodal Mobile Health Assessment in Spine Surgery Candidates (2022)

Neurosurgery

Authors: Greenberg, Jacob K.; Frumkin, Madelyn R.; Javeed, Saad; Zhang, Justin K.; Dai, Ruixuan; Molina, Camilo A.; Pennicooke, Brenton H.; Agarwal, Nitin; Santiago, Paul; Goodwin, Matthew L.; Jain, Deeptee; Pallotta, Nicholas; Gupta, Munish C.; Buchowski, Jacob M.; Leuthardt, Eric C.; Ghogawala, Zoher; Kelly, Michael P.; Hall, Bruce L.; Piccirillo, Jay F.; Lu, Chenyang; Rodebaugh, Thomas L.; Ray, Wilson Z.

Abstract

BACKGROUND: Rapid growth in smartphone use has expanded opportunities to use mobile health (mHealth) technology to collect real-time patient-reported and objective biometric data. These data may have important implication for personalized treatments of degenerative spine disease. However, no large-scale study has examined the feasibility and acceptability of these methods in spine surgery patients. OBJECTIVE: To evaluate the feasibility and acceptability of a multimodal preoperative mHealth assessment in patients with degenerative spine disease. METHODS: Adults undergoing elective spine surgery were provided with Fitbit trackers and sent preoperative ecological momentary assessments (EMAs) assessing pain, disability, mood, and catastrophizing 5 times daily for 3 weeks. Objective adherence rates and a subjective acceptability survey were used to evaluate feasibility of these methods. RESULTS: The 77 included participants completed an average of 82 EMAs each, with an average completion rate of 86\%. Younger age and chronic pulmonary disease were significantly associated with lower EMA adherence. Seventy-two (93\%) participants completed Fitbit monitoring and wore the Fitbits for an average of 247 hours each. On average, participants wore the Fitbits for at least 12 hours per day for 15 days. Only worse mood scores were independently associated with lower Fitbit adherence. Most participants endorsed positive experiences with the study protocol, including 91\% who said they would be willing to complete EMAs to improve their preoperative surgical guidance. CONCLUSION: Spine fusion candidates successfully completed a preoperative multimodal mHealth assessment with high acceptability. The intensive longitudinal data collected may provide new insights that improve patient selection and treatment guidance.

Feasibility of Conducting Long-term Health and Behaviors Follow-up in Adolescents: Longitudinal Observational Study (2022)

JMIR formative research

Authors: Cucchiaro, Giovanni; Ahumada, Luis; Gray, Geoffrey; Fierstein, Jamie; Yates, Hannah; Householder, Kym; Frye, William; Rehman, Mohamed

Abstract

Background: Machine learning uses algorithms that improve automatically through experience. This statistical learning approach is a natural extension of traditional statistical methods and can offer potential advantages for certain problems. The feasibility of using machine learning techniques in health care is predicated on access to a sufficient volume of data in a problem space. Objective: This study aimed to assess the feasibility of data collection from an adolescent population before and after a posterior spine fusion operation. Methods: Both physical and psychosocial data were collected. Adolescents scheduled for a posterior spine fusion operation were approached when they were scheduled for the surgery. The study collected repeated measures of patient data, including at least 2 weeks prior to the operation and 6 months after the patients were discharged from the hospital. Patients were provided with a Fitbit Charge 4 (consumer-grade health tracker) and instructed to wear it as often as possible. A third-party web-based portal was used to collect and store the Fitbit data, and patients were trained on how to download and sync their personal device data on step counts, sleep time, and heart rate onto the web-based portal. Demographic and physiologic data recorded in the electronic medical record were retrieved from the hospital data warehouse. We evaluated changes in the patients' psychological profile over time using several validated questionnaires (ie, Pain Catastrophizing Scale, Patient Health Questionnaire, Generalized Anxiety Disorder Scale, and Pediatric Quality of Life Inventory). Questionnaires were administered to patients using Qualtrics software. Patients received the questionnaire prior to and during the hospitalization and again at 3 and 6 months postsurgery. We administered paper-based questionnaires for the self-report of daily pain scores and the use of analgesic medications. Results: There were several challenges to data collection from the study population. Only 38% (32/84) of the patients we approached met eligibility criteria, and 50% (16/32) of the enrolled patients dropped out during the follow-up period-on average 17.6 weeks into the study. Of those who completed the study, 69% (9/13) reliably wore the Fitbit and downloaded data into the web-based portal. These patients also had a high response rate to the psychosocial surveys. However, none of the patients who finished the study completed the paper-based pain diary. There were no difficulties accessing the demographic and clinical data stored in the hospital data warehouse. Conclusions: This study identifies several challenges to long-term medical follow-up in adolescents, including willingness to participate in these types of studies and compliance with the various data collection approaches. Several of these challenges-insufficient incentives and personal contact between researchers and patients-should be addressed in future studies.

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Feasibility, acceptability, and effectiveness of school-based dance movement psychotherapy for children with emotional and behavioral difficulties (2022)

Frontiers in psychology

Authors: Moula, Zoe; Powell, Joanne; Brocklehurst, Shirley; Karkou, Vicky

Abstract

Background: Schools have been increasingly employing dance movement psychotherapists to support children cope with daily worries and stress, express and understand their emotions, develop self-awareness and self-esteem. However, evidence on the impact of dance movement psychotherapy as a tool for prevention of mental health difficulties in childhood remains limited. Methods: Sixteen children (aged 7-9) with mild emotional and behavioral difficulties from two primary schools were randomly assigned to a Dance Movement Psychotherapy (DMP) intervention or to a waiting list, within a larger pilot cross-over randomized controlled study which aimed to (a) test whether all elements of study design can work together and run smoothly in a full-scale RCT; and (b) investigate the effectiveness of arts therapies in improving children's health related quality of life (HRQOL; EQ-5D-Y), wellbeing and life functioning (Child Outcome Rating Scale; CORS), emotional and behavioral difficulties (Strengths and Difficulties Questionnaire; SDQ), and duration of sleep (Fitbits). The therapeutic process was also evaluated through interviews with children, participant observations, the Children's Session Rating Scale (CSRS), and ratings of adherence to the therapeutic protocol. Results: The findings indicated that DMP led to improvements in children's life functioning, wellbeing, duration of sleep, emotional and behavioral difficulties, but not in quality of life. The improvements were maintained at the follow-up stages, up to 6 months post-intervention. Interviews with children also suggested positive outcomes, such as self-expression; emotional regulation; mastery and acceptance of emotions; improved self-confidence and self-esteem; reduced stress; and development of positive relationships. However, children would have preferred smaller groups and longer sessions. Conclusion: This study indicated that all outcome measures would be suitable for inclusion in a larger randomized controlled trial, though the EQ-5D-Y is not recommended as a stand-alone measure due to its lack of sensitivity and specificity for young participants. The adherence to the therapeutic protocol ratings differed between children and adults, highlighting the need to include children's voice in future research. Strategies are also proposed of how to conduct randomization of participants in ways that do not hinder the therapeutic process.

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Fitbit Use and Activity Levels From Intervention to 2 Years After: Secondary Analysis of a Randomized Controlled Trial (2022)

JMIR mHealth and uHealth

Authors: Hartman, Sheri J.; Chen, Ruohui; Tam, Rowena M.; Narayan, Hari K.; Natarajan, Loki; Liu, Lin

Abstract

Background: There has been a rapid increase in the use of commercially available activity trackers, such as Fitbit, in physical activity intervention research. However, little is known about the long-term sustained use of trackers and behavior change after short-term interventions. Objective: This study aims to use minute-level data collected from a Fitbit tracker for up to 2 years after the end of a randomized controlled trial to examine patterns of Fitbit use and activity over time. Methods: Participants in this secondary data analysis were 75 female breast cancer survivors who had been enrolled in a 12-week physical activity randomized controlled trial. Participants randomized to the exercise intervention (full intervention arm) received a Fitbit One, which was worn daily throughout the 12-week intervention, and then were followed for 2 years after the intervention. Participants randomized to the waitlist arm, after completing the randomized controlled trial, received a Fitbit One and a minimal version of the exercise intervention (light intervention arm), and then were followed for 2 years after the intervention. Average and daily adherence and MVPA were compared between the 2 groups in the interventional and postinterventional periods using both linear and generalized additive mixed effects models. Results: Adherence to wearing the Fitbit during the 12-week intervention period was significantly higher in the full intervention arm than in the light intervention arm (85% vs 60%; P<.001). Average adherence was significantly lower for both study arms during the follow-up period than in the intervention period; however, there were statistically different patterns of adherence during the follow-up period, with the light intervention arm having steeper declines than the full intervention arm over time (P<.001). Similar to the adherence results, mean minutes of Fitbit-measured MVPA was higher for the full intervention arm than for the light intervention arm during the 12-week intervention period (mean MVPA 27.89 minutes/day, SD 16.38 minutes/day vs 18.35 minutes/day, SD 12.64 minutes/day; P<.001). During the follow-up period, average MVPA was significantly lower than the 12-week intervention period for both the full intervention arm (21.74 minutes/day, SD 24.65 minutes/day; P=.002) and the light intervention arm (15.03 minutes/day, SD 13.27 minutes/day; P=.004). Although the mean MVPA in each arm was similar across the follow-up period (P=.33), the pattern of daily MVPA was significantly different between the 2 groups (P<.001). Conclusions: While adherence to wearing activity trackers and maintaining physical activities declined after completion of a 12-week exercise intervention, a more active interventional strategy resulted in greater wear time and activity levels during the intervention and more stable patterns of adherence and activity in the long term. An improved understanding of long-term maintenance patterns may inform improved exercise interventions that result in sustained increases in physical activity.

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Functional Connectivity, Physical Activity, and Neurocognitive Performances in Patients with Vascular Cognitive Impairment, No Dementia (2022)

Current Alzheimer research

Authors: Chang, Ya-Ting; Liu, Chun-Ting; Hsu, Shih-Wei; Lee, Chen-Chang; Huang, Pei-Ching

Abstract

Background: Vascular Cognitive Impairment, No Dementia (VCIND) is a key stage at which early intervention will delay or prevent dementia. The pathophysiology of VCIND posits that a lesion in a single location in the brain has the ability to disrupt brain networks, and the subsequent abnormal Functional Connectivity (FC) of brain networks leads to deficits in corresponding neurobehavioral domains. In this study, we tested the hypothesis that disrupted anterior cingulate cortex and striatal networks mediated the effects of Physical Activity (PA) on neurobehavioral function. Methods: In 27 patients with VCIND, FC within the brain networks and neurobehavioral dysfunction were assessed. The relationship between the cognitive scores, FC, and PA was studied. The Fitbit Charge 2 was used to measure step counts, distance, and calories burned. In patients with VCIND, a cross-sectional Spearman's correlation to analyze the relationship among patient-level measures of PA, cognitive function scores, and FC strength within the brain networks. Results: Average step counts and average distance were associated with Trail Making Test B (TM-B) time to completion (seconds) and Instrumental Activities of Daily Living (IADL) score (P <0.05). The average calories burned were associated with IADL score (P = 0.009). The FC within the brain networks anchored by left caudal Anterior Cingulate Cortex (ACC) seeds (x= -5, y= 0, z= 36) and (x= -5, y= -10, z= 47) were positively correlated with average step counts and average distance, were negatively correlated with TMB time to completion (seconds), and were positively correlated with IADL score (P < 0.05). The FC within the brain networks anchored by left subgenual ACC seed (x= -5, y= 25, z= -10) were negatively correlated with average step counts and average distance were positively correlated with TMB time to completion (seconds), and were negatively correlated with IADL score (P < 0.05). The FC within the striatal networks was positively correlated with average calories burned and IADL score (P < 0.05). Keywords: Actigraphy; brain network; cognition; executive function; functional connectivity; physical activity.

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Heart Rate Measurement Accuracy of Fitbit Charge 4 and Samsung Galaxy Watch Active2: Device Evaluation Study (2022)

JMIR formative research

Authors: Nissen, Michael; Slim, Syrine; Jager Katharina; Flaucher Madeleine; Huebner Hanna; Danzberger Nina; Fasching Peter A.; Beckmann Matthias W.; Gradl Stefan; Eskofier Bjoern M.

Abstract

Background: Fitness trackers and smart watches are frequently used to collect data in longitudinal medical studies. They allow continuous recording in real-life settings, potentially revealing previously uncaptured variabilities of biophysiological parameters and diseases. Adequate device accuracy is a prerequisite for meaningful research. Objective: This study aims to assess the heart rate recording accuracy in two previously unvalidated devices: Fitbit Charge 4 and Samsung Galaxy Watch Active2. Methods: Participants performed a study protocol comprising 5 resting and sedentary, 2 low-intensity, and 3 high-intensity exercise phases, lasting an average of 19 minutes 27 seconds. Participants wore two wearables simultaneously during all activities: Fitbit Charge 4 and Samsung Galaxy Watch Active2. Reference heart rate data were recorded using a medically certified Holter electrocardiogram. The data of the reference and evaluated devices were synchronized and compared at 1-second intervals. The mean, mean absolute error, mean absolute percentage error, Lin concordance correlation coefficient, Pearson correlation coefficient, and Bland-Altman plots were analyzed. Results: A total of 23 healthy adults (mean age 24.2, SD 4.6 years) participated in our study. Overall, and across all activities, the Fitbit Charge 4 slightly underestimated the heart rate, whereas the Samsung Galaxy Watch Active2 overestimated it (-1.66 beats per minute [bpm]/3.84 bpm). The Fitbit Charge 4 achieved a lower mean absolute error during resting and sedentary activities (seated rest: 7.8 vs 9.4; typing: 8.1 vs 11.6; laying down [left]: 7.2 vs 9.4; laying down [back]: 6.0 vs 8.6; and walking slowly: 6.8 vs 7.7 bpm), whereas the Samsung Galaxy Watch Active2 performed better during and after low- and high-intensity activities (standing up: 12.3 vs 9.0; walking fast: 6.1 vs 5.8; stairs: 8.8 vs 6.9; squats: 15.7 vs 6.1; resting: 9.6 vs 5.6 bpm). Conclusions: Device accuracy varied with activity. Overall, both devices achieved a mean absolute percentage error of just <10%. Thus, they were considered to produce valid results based on the limits established by previous work in the field. Neither device reached sufficient accuracy during seated rest or keyboard typing. Thus, both devices may be eligible for use in respective studies; however, researchers should consider their individual study requirements.

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Home-based cardiac rehabilitation using information and communication technology for heart failure patients with frailty (2022)

ESC heart failure

Authors: Nagatomi, Yuta; Ide, Tomomi; Higuchi, Tae; Nezu, Tomoyuki; Fujino, Takeo; Tohyama, Takeshi; Nagata, Takuya; Higo, Taiki; Hashimoto, Toru; Matsushima, Shouji; Shinohara, Keisuke; Yokoyama, Tomiko; Eguchi, Aika; Ogusu, Ayumi; Ikeda, Masataka; Ishikawa, Yusuke; Yamashita, Fumika; Kinugawa, Shintaro; Tsutsui, Hiroyuki

Abstract

Aims: Cardiac rehabilitation (CR) is an evidence-based, secondary preventive strategy that improves mortality and morbidity rates in patients with heart failure (HF). However, the implementation and continuation of CR remains unsatisfactory, particularly for outpatients with physical frailty. This study investigated the efficacy and safety of a comprehensive home-based cardiac rehabilitation (HBCR) programme that combines patient education, exercise guidance, and nutritional guidance using information and communication technology (ICT). Methods and results: This study was a single-centre, open-label, randomized, controlled trial. Between April 2020 and November 2020, 30 outpatients with chronic HF (New York Heart Association II-III) and physical frailty were enrolled. The control group (n = 15) continued with standard care, while the HBCR group (n = 15) also received comprehensive, individualized CR, including ICT-based exercise and nutrition guidance using ICT via a Fitbit® device for 3 months. The CR team communicated with each patient in HBCR group once a week via the application messaging tool and planned the training frequency and intensity of training individually for the next week according to each patient's symptoms and recorded pulse data during exercise. Dietitians conducted a nutritional assessment and then provided individual nutritional advice using the picture-posting function of the application. The primary outcome was the change in the 6 min walking distance (6MWD). The participants' mean age was 63.7 ± 10.1 years, 53% were male, and 87% had non-ischaemic heart disease. The observed change in the 6MWD was significantly greater in the HBCR group (52.1 ± 43.9 m vs. -4.3 ± 38.8 m; P < 0.001) at a 73% of adherence rate. There was no significant change in adverse events in either group. Conclusions: Our comprehensive HBCR programme using ICT for HF patients with physical frailty improved exercise tolerance and improved lower extremity muscle strength in our sample, suggesting management with individualized ICT-based programmes as a safe and effective approach. Considering the increasing number of HF patients with frailty worldwide, our approach provides an efficient method to keep patients engaged in physical activity in their daily life.

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Human-Centered Design of a Digital Health Tool to Promote Effective Self-care in Patients With Heart Failure: Mixed Methods Study (2022)

JMIR Formative Research

Authors: Johnston, William; Keogh, Alison; Dickson, Jane; Leslie, Stephen J.; Megyesi, Peter; Connolly, Rachelle; Burke, David; Caulfield, Brian

Abstract

Background Effective self-care is an important factor in the successful management of patients with heart failure (HF). Despite the importance of self-care, most patients with HF are not adequately taught the wide range of skills required to become proficient in self-care. Digital health technology (DHT) may provide a novel solution to support patients at home in effective self-care, with the view to enhancing the quality of life and ultimately improving patient outcomes. However, many of the solutions developed to date have failed to consider users’ perspectives at the point of design, resulting in poor effectiveness. Leveraging a human-centered design (HCD) approach to the development of DHTs may lead to the successful promotion of self-care behaviors in patients with HF. Objective This study aimed to outline the HCD, development, and evaluation process of a DHT designed to promote effective self-care in patients with HF. Methods A design thinking approach within the HCD framework was undertaken, as described in the International Organization for Standardization 9241-210:2019 regulations, using a 5-step process: empathize, ideate, design, develop, and test. Patients with HF were involved throughout the design and evaluation of the system. The designed system was grounded in behavior change theory using the Theoretical Domains Framework and included behavior change techniques. Mixed methods were used to evaluate the DHT during the testing phase. Results Steps 1 to 3 of the process resulted in a set of evidence- and user-informed design requirements that were carried forward into the iterative development of a version 1 system. A cross-platform (iOS and Android) mobile app integrated with Fitbit activity trackers and smart scales was developed. A 2-week user testing phase highlighted the ease of use of the system, with patients demonstrating excellent adherence. Qualitative analysis of semistructured interviews identified the early potential for the system to positively influence self-care. Specifically, users perceived that the system increased their confidence and motivation to engage in key self-care behaviors, provided them with skills and knowledge that made them more aware of the importance of self-care behaviors, and might facilitate timely help seeking. Conclusions The use of an HCD methodology in this research has resulted in the development of a DHT that may engage patients with HF and potentially affect their self-care behaviors. This comprehensive work lays the groundwork for further development and evaluation of this solution before its implementation in health care systems. A detailed description of the HCD process used in this research will help guide the development and evaluation of future DHTs across a range of disease use cases.

Intra-individual impact of the COVID-19 pandemic on mental health and sleep in young adults (2022)

PloS One

Authors: Knickerbocker, Kelly J.; Cox, Evelyn A.; Dhawka, Luvna; Woods, Kerri; Ingram, Krista K.

Abstract

The COVID-19 pandemic has posed unique academic, social, financial, and health-related challenges for young adults. While numerous studies have documented average increases in reported mental health issues in the general population, few have measured the magnitude of changes in mental health symptoms and sleep difficulties within individuals. Here, we measure the impact of the COVID-19 pandemic on mental health and sleep of university students pre- and mid-pandemic. Prior to the pandemic (Fall 2019), individuals (n = 23) were recruited to participate in an eight-day, comprehensive sleep study using Fitbit® actigraphy. Participants also completed detailed mental health and sleep surveys, including depression (BDI-II), anxiety (STAI), and sleep disturbance (PROMIS) surveys. One year later, these individuals repeated the study during the pandemic (Fall 2020); participants completed the original surveys and sleep study, in addition to a targeted survey on mental and sleep health due to the pandemic. Self-reported levels of anxiety, depression, and sleep disturbance, and sleep parameters, measured by actigraphy, were compared within the same individuals pre- and mid-pandemic. Self-report survey data revealed that three-quarters of participants experienced an increase in stress and anxiety due to the pandemic. In addition, intra-individual depression and anxiety symptoms increased to clinically significant levels within individuals from pre- to mid-pandemic. Over two-thirds of participants reported sleeping less, and more than half reported that their sleep health had worsened during the pandemic. Changes in sleep disturbance were positively associated with changes in depression and anxiety, reinforcing the robust relationship between poor sleep quality and mental health. Furthermore, individuals who reported greater sleep disturbance during the pandemic experienced lower relative proportions of both REM and deep sleep. The impact of the COVID-19 pandemic on university students is multi-faceted-mental health, sleep quality, and the amount of restorative sleep are negatively affected by the pandemic environment. These compounded effects exacerbate the health consequences of the pandemic and highlight a need for increased attention to the prevention and treatment of mental health disorders, particularly in vulnerable populations of young adults.

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Living labs for a mobile app-based health program: effectiveness of a 24-week walking intervention for cardiovascular disease risk reduction among female Korean-Chinese migrant workers: a randomized controlled trial (2022)

Archives of Public Health = Archives Belges De Sante Publique

Authors: Kim, Youlim; Lee, Hyeonkyeong; Chung, Misook Lee

Abstract

BACKGROUND: The risk of Cardiovascular disease (CVDs) among adult populations is influenced by environmental factors, and immigrant populations tend to be more vulnerable. This study examined the effectiveness of a 24-week walking program based on social-cognitive determinants through mobile app for CVD risk reduction among female Korean-Chinese middle-aged workers. METHODS: This study used a parallel randomized controlled trial. Participants were recruited by distributing posters and flyers and randomly assigned to either the standard treatment (ST, n = 22) or enhanced treatment group (ET, n = 28). Participants were provided with a mobile app linked to Fitbit Alta for 24 weeks and instructed to walk at least 30 minutes five times a week and moderate-intensity physical activity. The ET group had additional interventions that enhanced social-cognitive determinants such as self-efficacy, social support. All participants were guided to voluntary physical activity during the 12-week maintenance period. Data were analyzed by the Mann Whitney U-test and a generalized estimating equation. RESULTS: There were significant between-group differences regarding the number of steps (B = 1.295, P {\textless} .001) and moderate physical activity time (OR = 6.396, P = .030) at week 12. ET group had significant changes in high-density lipoprotein cholesterol (B = 10.522, P = .007), low-density lipoprotein cholesterol (B = -16.178, P = .024), total cholesterol (B = -20.325, P = .039), fasting blood sugar (B = - 8.138, P = -.046). In addition, there was a significant reduction of 10-year CVD risk for the ET group over 12 weeks compared to the ST group (B = -0.521, P{\textless}. 001). CONCLUSIONS: Long-term studies are needed to reduce the risk of cardiovascular disease in large-scale migrant workers and to confirm the direct and insdirect effects of social-cognitive determinants on health outcomes. TRIAL REGISTRATION: The trial was retrospectively registered in WHO ICTRP (KCT0006467) August 19th, 2021. ( https://trialsearch.who.int/Trial2.aspx?TrialID=KCT0006467.

Low- and High-Intensity Physical Activity Among People with HIV: Multilevel Modeling Analysis Using Sensor- and Survey-Based Predictors (2022)

JMIR mHealth and uHealth

Authors: Cook, Paul; Jankowski, Catherine; Erlandson, Kristine M.; Reeder, Blaine; Starr, Whitney; Makic, Mary Beth Flynn

Abstract

Background: High-intensity physical activity improves the health of people with HIV. Even when people have good intentions to engage in physical activity, they often find it difficult to maintain physical activity behavior in the long term. Two Minds Theory is a neurocognitive model that explains gaps between people's intentions and behaviors based on the operations of 2 independent mental systems. This model predicts that everyday experiences will affect physical activity and that factors outside people's awareness, such as sleep and stress, can have particularly strong effects on physical activity behaviors. Objective: We designed this study to test the effects of daily experiences on physical activity among people with HIV, including measures of people's conscious experiences using daily electronic surveys and measures of nonconscious influences using sensor devices. Methods: In this study, 55 people with HIV wore a Fitbit Alta for 30 days to monitor their physical activity, sleep, and heart rate variability (HRV) as a physiological indicator of stress. Participants also used their smartphones to complete daily electronic surveys for the same 30 days about fatigue, self-efficacy, mood, stress, coping, motivation, and barriers to self-care. Time-lagged, within-person, multilevel models were used to identify the best prospective predictors of physical activity, considering the daily survey responses of people with HIV and sensor data as predictors of their physical activity the following day. We also tested baseline surveys as predictors of physical activity for comparison with daily variables. Results: Different people had different average levels of physical activity; however, physical activity also varied substantially from day to day, and daily measures were more predictive than baseline surveys. This suggests a chance to intervene based on day-to-day variations in physical activity. High-intensity physical activity was more likely when people with HIV reported less subjective fatigue on the prior day (r=-0.48) but was unrelated to actual sleep based on objective sensor data. High-intensity physical activity was also predicted by higher HRV (r=0.56), indicating less stress, lower HIV-related stigma (r=-0.21), fewer barriers to self-care (r=-0.34), and less approach coping (r=-0.34). Similar variables predicted lower-level physical activity measured based on the number of steps per day of people with HIV. Conclusions: Some predictors of physical activity, such as HRV, were only apparent based on sensor data, whereas others, such as fatigue, could be measured via self-report. Findings about coping were unexpected; however, other findings were in line with the literature. This study extends our prior knowledge on physical activity by demonstrating a prospective effect of everyday experiences on physical activity behavior, which is in line with the predictions of Two Minds Theory. Clinicians can support the physical activity of people with HIV by helping their patients reduce their daily stress, fatigue, and barriers to self-care.

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Mediators of Effects on Physical Activity and Sedentary Time in an Activity Tracker and Behavior Change Intervention for Adolescents: Secondary Analysis of a Cluster Randomized Controlled Trial (2022)

JMIR mHealth and uHealth

Authors: Verswijveren, Simone Johanna Josefa Maria; Abbott, Gavin; Lai, Samuel K.; Salmon, Jo; Timperio, Anna; Brown, Helen; Macfarlane, Susie; Ridgers, Nicola D.

Abstract

BACKGROUND: Adolescence is a critical age where steep declines in physical activity and increases in sedentary time occur. Promoting physical activity should therefore be a priority for short- and long-term health benefits. Wearable activity trackers in combination with supportive resources have the potential to influence adolescents' physical activity levels and sedentary behavior. Examining the pathways through which such interventions work can inform which mediators to target in future studies. OBJECTIVE: The aim of this paper is to examine the impact of the Raising Awareness of Physical Activity (RAW-PA) intervention on potential mediators of behavior change after intervention, and whether these mediated the intervention effects on physical activity and sedentary time at 6-month follow-up. METHODS: RAW-PA was a 12-week intervention, grounded in social cognitive theory and behavioral choice theory, aimed at increasing physical activity among inactive adolescents through combining a wearable activity tracker with digital resources delivered via a private Facebook group (n=159 complete cases). The targeted potential mediators were identified from previous studies conducted in adolescents and included self-efficacy, peer support, family support, teacher support, self-regulation strategies, barriers, and enjoyment. Outcomes included sedentary time as well as light- and moderate-to-vigorous-intensity physical activity. A series of mixed linear models were used to estimate intervention effects on physical activity and sedentary behavior at follow-up and on potential mediators after intervention and to test whether there were indirect effects of the intervention on physical activity and sedentary behavior via mediators. RESULTS: Adolescents in the intervention group (n=75) engaged in higher sedentary time and lower light intensity at 6-month follow-up compared to the wait-list controls (n=84). There were no intervention effects for moderate-to-vigorous-intensity physical activity. The intervention group perceived more barriers to physical activity than the wait-list control group at 6-month follow-up (mean adjusted difference=1.77; 95\% CI 0.19-3.34; P=.03). However, indirect effects for each outcome were not statistically significant, indicating that perceived barriers to physical activity did not mediate intervention effects for physical activity or sedentary time. CONCLUSIONS: RAW-PA did not beneficially impact hypothesized mediators in these inactive adolescents, despite strategies being designed to target them. This suggests that the lack of overall intervention effects on physical activity and sedentary time observed in the RAW-PA study could be due to the limited impact of the intervention on the targeted mediators. Future studies should consider different strategies to target theoretically informed potential mediators and identify intervention strategies that effectively target key mediators to improve physical activity among inactive adolescents. Finally, intervention effects according to level of wearable tracker use or level of engagement with the intervention should be explored. This may provide important insights for designing successful wearable activity tracker interventions. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12616000899448; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370716\&isReview=true. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12889-016-3945-5.

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mHealth Support to Stimulate Physical Activity in Individuals With Intellectual Disability: Protocol for a Mixed Methods Pilot Study (2022)

JMIR research protocols

Authors: Michalsen, Henriette; Wangberg, Silje C.; Hartvigsen, Gunnar; Henriksen, André; Pettersen, Gunn; Jaccheri, Letizia; Jahnsen, Reidun Birgitta; Thrane, Gyrd; Arntzen, Cathrine; Anke, Audny

Abstract

BACKGROUND: Several studies have shown that individuals with intellectual disabilities (IDs) have low levels of physical activity (PA), and intervention studies on PA suggest inconsistent evidence. The use of technology as a means of motivation for PA has yet to be extensively explored and needs to be further investigated. OBJECTIVE: We aim to assess the feasibility and acceptability of procedures for an intervention arm in a future trial on mobile health (mHealth) to support PA for individuals with IDs. In addition, we aim to examine how the use of technology can influence motivation for PA among participants, their caregivers, and staff members. METHODS: A mixed methods pilot study of an intervention arm will be carried out in a planned randomized controlled trial (RCT). Ten participants with ID and their caregivers or a staff member will be included. Information will always be provided by a caregiver or a staff member, or participants with ID if possible. Assessments will be carried out at baseline, follow-up after 4 weeks, and 12 weeks, and include questionnaires on PA, social support, self-efficacy, and challenging behavior. PA will be measured with 2 different activity trackers (Fitbit and Axivity) for 1 week at all assessments. Feasibility will be assessed as recruitment and adherence rate, missing data, usability of the motivational mHealth tool, and estimates of effectiveness. Acceptability of study procedures, activity measures, and motivation for participation in PA will be additionally assessed with qualitative methods at the end of the intervention. RESULTS: Enrollment commenced in May 2021. Data collection was completed in March 2022. CONCLUSIONS: This pilot study will evaluate the feasibility and acceptability of study procedures of the intervention arm of a planned RCT to address feasibility issues, improve study procedures, and estimate effectiveness of the study measures. How the use of technology can influence motivation for PA will also be examined, which can help guide and improve future PA interventions involving the use of technology. TRIAL REGISTRATION: ClinicalTrials.gov NCT04929106; https://clinicaltrials.gov/ct2/show/NCT04929106. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37849.

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mHealth-Supported Gender- and Culturally Sensitive Weight Loss Intervention for Hispanic Men With Overweight and Obesity: Single-Arm Pilot Study (2022)

JMIR formative research

Authors: Garcia, David O.; Valdez, Luis A.; Aceves, Benjamin; Bell, Melanie L.; Rabe, Brooke A.; Villavicencio, Edgar A.; Marrero, David G.; Melton, Forest; Hooker, Steven P.

Abstract

BACKGROUND: Hispanic men have disproportionate rates of overweight and obesity compared with other racial and ethnic subpopulations. However, few weight loss interventions have been developed specifically for this high-risk group. Furthermore, the use of mobile health (mHealth) technologies to support lifestyle behavior changes in weight loss interventions for Hispanic men is largely untested. OBJECTIVE: This single-arm pilot study examined the feasibility and acceptability of integrating mHealth technology into a 12-week gender- and culturally sensitive weight loss intervention (GCSWLI) for Hispanic men with overweight and obesity. METHODS: A total of 18 Hispanic men (mean age 38, SD 10.9 years; mean BMI 34.3, SD 5.5 kg/m²; 10/18, 56\% Spanish monolingual) received a GCSWLI, including weekly in-person individual sessions, a daily calorie goal, and prescription of ≥225 minutes of moderate-intensity physical activity per week. mHealth technology support included tailored SMS text messaging, behavior self-monitoring support using Fitbit Charge 2, and weight tracking using a Fitbit Aria Wi-Fi Smart Scale. Changes in weight from baseline to 12 weeks were estimated using a paired 2-tailed t test. Descriptive analyses characterized the use of Fitbit and smart scales. Semistructured interviews were conducted immediately after intervention to assess the participants' weight loss experiences and perspectives on mHealth technologies. RESULTS: Of 18 participants, 16 (89\%) completed the 12-week assessments; the overall attrition rate was 11.1\%. The mean weight loss at week 12 was -4.7 kg (95\% CI 7.1 to -2.4 kg; P{\textless}.001). Participants wore the Fitbit 71.58\% (962/1344) of the intervention days and logged their body weight using the smart scale (410/1344, 30.51\% of the intervention days). Participants identified barriers to the use of the technology, such as lack of technological literacy and unreliable internet access for the smart scale. CONCLUSIONS: Although clinically significant weight loss was achieved by integrating mHealth technology into the GCSWLI, adherence to the prescribed use of technology was modest. Addressing barriers to the use of such technologies identified in our work may help to refine an mHealth intervention approach for Hispanic men. TRIAL REGISTRATION: ClinicalTrials.gov NCT02783521; https://clinicaltrials.gov/ct2/show/NCT02783521.

Moving from intention to behaviour: a randomised controlled trial protocol for an app-based physical activity intervention (i2be) (2022)

BMJ open

Authors: Kokai, Lili L.; O Ceallaigh, Diarmaid T.; Wijtzes, Anne I.; Roeters Van Lennep, Jeanine E.; Hagger, Martin S.; Cawley, John; Rohde, Kirsten I. M.; Van Kippersluis, Hans; Burdorf, Alex

Abstract

Introduction Efficacy tests of physical activity interventions indicate that many have limited or short-term efficacy, principally because they do not sufficiently build on theory-based processes that determine behaviour. The current study aims to address this limitation. Methods and analysis The efficacy of the 8-week intervention will be tested using a three-condition randomised controlled trial delivered through an app, in women with a prior hypertensive pregnancy disorder. The intervention is based on the integrated behaviour change model, which outlines the motivational, volitional and automatic processes that lead to physical activity. The mechanisms by which the behaviour change techniques lead to physical activity will be tested. Following stratification on baseline factors, participants will be randomly allocated in-app to one of three conditions (1:1:1). The information condition will receive information, replicating usual care. Additionally to what the information condition receives, the motivation condition will receive content targeting motivational processes. Additionally to what the motivation condition receives, the action condition will receive content targeting volitional and automatic processes. The primary outcome is weekly minutes of moderate-to-vigorous physical activity, as measured by an activity tracker (Fitbit Inspire 2). Secondary outcomes include weekly average of Fitbit-measured daily resting heart rate, and self-reported body mass index, waist-hip ratio, cardiorespiratory fitness and subjective well-being. Tertiary outcomes include self-reported variables representing motivational, volitional, and automatic processes. Outcome measures will be assessed at baseline, immediately post-intervention, and at 3 and 12 months post-intervention. Physical activity will also be investigated at intervention midpoint. Efficacy will be determined by available case analysis. A process evaluation will be performed based on programme fidelity and acceptability measures. Ethics and dissemination The Medical Ethics Committee of the Erasmus MC has approved this study (MEC-2020-0981). Results will be published in peer reviewed scientific journals and presented at scientific conferences. Trial registration number Netherlands trial register, NL9329.

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Objective and subjective measures of daily physical activity in persons with Multiple Sclerosis beginning a rehabilitation regime: A cross-sectional study (2022)

Multiple Sclerosis and Related Disorders

Authors: Torchio, Alessandro; Fusari, Giulia; Perini, Gloria; Crispiatico, Valeria; Grosso, Cristina; Cattaneo, Davide; Pagliari, Chiara; Jonsdottir, Johanna

Abstract

INTRODUCTION: Fatigue, and balance and gait disorders can impact on physical activity (PA) levels in persons with Multiple Sclerosis (pwMS). To date, several studies have examined PA in pwMS during daily life, but little is known about PA levels in pwMS during a rehabilitation period. The present study investigated PA levels (daily steps, light physical activity (LPA), and moderate-vigorous physical activity (MVPA)) in inpatient and outpatients with MS during their rehabilitation period and described the relationship between objectively measured PA and levels of disability, quality of life, fatigue, and self-efficacy. METHODS: In this exploratory cross-sectional study, we examined 40 pwMS during their inpatient or outpatient rehabilitation regime. Participants included in the study (N = 34) wore a Fitbit Versa tracker for one week recording daily steps, minutes of LPA, and minutes of MVPA (primary outcomes). They underwent a clinical assessment of physical activity levels (Godin Leisure-Time Exercise Questionnaire(GLTEQ)), fatigue (Fatigue Severity Scale(FSS)), walking ability (10 Meter Walk Test(10MWT), 2-Min Walk Test(2MWT), 12-item Multiple Sclerosis Walking scale(MSWS-12)), quality of life (12-Item Short Form Survey (SF-12)), and self-efficacy (Self-Efficacy in Multiple Sclerosis scale (SEMS)) (secondary outcomes). Multiple linear regressions (MLR) models were used to test whether the demographic difference between the two groups influenced the estimation of objective variables measured by Fitbit. Finally, correlations between objectively measured physical activity and subjective clinical scales were estimated with Spearman correlations. RESULTS: Our sample consisted of 21 females and 13 males with a mean (interquartile range) age of 52 (20) years and an Expanded Disability Status scale(EDSS) score of 6.0 (1.50) points; baseline characteristics of inpatients (N = 18) and outpatients (N = 16) differed statistically only in EDSS levels (p-value = 0.008) and use of assistive devices (p=0.007). The whole sample performed (mean±standard deviation) 3969±2190 steps per day, with no significant difference between inpatients (3318±1515) and outpatients (4660±2606). No statistical difference was found between the groups in LPA (p-value=0.064). A significant difference in MVPA (p-value {\textless} 0.001) was found between inpatients and outpatients, 1.52±3.98 and 14.69±11.56 min per day, respectively. Significant correlations were found between FSS and MVPA both in the whole sample (r(32)= -0.62, p {\textless} 0.001) and in the outpatients group (r(14) = -0.66, p = 0.005), and between 10MWT and daily steps (whole sample:(r(32) = 0.48, p = 0.005), outpatients:(r(14)= -0.51, p = 0.05)). CONCLUSIONS: PwMS in our study overall engaged in reduced and less intense levels of daily PA with respect to the guidelines with inpatients performing almost no vigorous activities. Considering the importance of PA in improving physical and mental well-being, clinicians and researchers should develope strategies to increase daily PA of PwMS during their rehabilitation programs and daily life.

Performance of Four Commercial Wearable Sleep-Tracking Devices Tested Under Unrestricted Conditions at Home in Healthy Young Adults (2022)

Nature and Science of Sleep

Authors: Chinoy, Evan D.; Cuellar, Joseph A.; Jameson, Jason T.; Markwald, Rachel R.

Abstract

PURPOSE: Commercial wearable sleep-tracking devices are growing in popularity and in recent studies have performed well against gold standard sleep measurement techniques. However, most studies were conducted in controlled laboratory conditions. We therefore aimed to test the performance of devices under naturalistic unrestricted home sleep conditions. PARTICIPANTS AND METHODS: Healthy young adults (n = 21; 12 women, 9 men; 29.0 ± 5.0 years, mean ± SD) slept at home under unrestricted conditions for 1 week using a set of commercial wearable sleep-tracking devices and completed daily sleep diaries. Devices included the Fatigue Science Readiband, Fitbit Inspire HR, Oura ring, and Polar Vantage V Titan. Participants also wore a research-grade actigraphy watch (Philips Respironics Actiwatch 2) for comparison. To assess performance, all devices were compared with a high performing mobile sleep electroencephalography headband device (Dreem 2). Analyses included epoch-by-epoch and sleep summary agreement comparisons. RESULTS: Devices accurately tracked sleep-wake summary metrics (ie, time in bed, total sleep time, sleep efficiency, sleep latency, wake after sleep onset) on most nights but performed best on nights with higher sleep efficiency. Epoch-by-epoch sensitivity (for sleep) and specificity (for wake), respectively, were as follows: Actiwatch (0.95, 0.35), Fatigue Science (0.94, 0.40), Fitbit (0.93, 0.45), Oura (0.94, 0.41), and Polar (0.96, 0.35). Sleep stage-tracking performance was mixed, with high variability. CONCLUSION: As in previous studies, all devices were better at detecting sleep than wake, and most devices compared favorably to actigraphy in wake detection. Devices performed best on nights with more consolidated sleep patterns. Unrestricted sleep TIB differences were accurately tracked on most nights. High variability in sleep stage-tracking performance suggests that these devices, in their current form, are still best utilized for tracking sleep-wake outcomes and not sleep stages. Most commercial wearables exhibited promising performance for tracking sleep-wake in real-world conditions, further supporting their consideration as an alternative to actigraphy.

Physical activity measurement in older adults: Wearables versus self-report (2022)

Frontiers in Digital Health

Authors: VandeBunte, Anna; Gontrum, Eva; Goldberger, Lauren; Fonseca, Corrina; Djukic, Nina; You, Michelle; Kramer, Joel H.; Casaletto, Kaitlin B.

Abstract

Physical activity (PA) is associated with preserved age-related body and brain health. However, PA quantification can vary. Commercial-grade wearable monitors are objective, low burden tools to capture PA but are less well validated in older adults. Self-report PA questionnaires are widely accepted and more frequently used but carry inherent limitations. We aimed to compare these commonly used PA measures against one another and examine their convergent validity with a host of relevant outcomes. We also examined the factors that drive differences in PA self-reporting styles in older adults. 179 older adults completed 30-day Fitbit Flex2™ monitoring and reported PA levels via two widely used PA questionnaires: PASE and CHAMPS-METs (metabolic expenditure calories burned). Participants also completed measures of cardiometabolic (hypertension diagnosis, resting heart rate, A1C levels), cognitive (memory, processing speed, executive functioning), and brain MRI (medial temporal lobe volume) outcomes. The discrepancy between objective Fitbit monitoring and self-reported PA was evaluated using a sample-based z difference score. There were only modest relationships across all PA metrics. Fitbit step count demonstrated a stronger association with the PASE, whereas Fitbit calories burned was more strongly associated with CHAMPS-MET. Fitbit outcomes had more consistent convergence with relevant outcomes of interest (e.g., cardiometabolic and brain health indices) when compared to subjective measures; however, considerable heterogeneity within these associations was observed. A higher degree of overreporting was associated with worse memory and executive performances, as well as hypertension diagnoses. We build on prior findings that wearable, digital health indicators of PA demonstrate greater construct validity than self-report in older adults. We further show important clinical features (e.g., poorer cognitive status) of older adults that could contribute to a higher level of overreporting on self-report measures. Characterization of what PA measures truly operationalize will help elucidate relationships between most relevant facets of PA and outcomes of interest.

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Pre S cription Digita L Th E rap E utic for P atients with I nsomnia ( SLEEP-I): a protocol for a pragmatic randomised controlled trial (2022)

BMJ open

Authors: Dreyer, Rachel P.; Berkowitz, Alyssa; Yaggi, Henry Klar; Schneeberg, Lynelle; Shah, Nilay D.; Emanuel, Lindsay; Kolla, Bhanuprakash; Jeffery, Molly Moore; Deeg, Mark; Ervin, Keondae; Thorndike, Frances; Ross, Joseph S.

Abstract

Introduction Cognitive behavioural therapy for insomnia (CBT-I) is effective at treating chronic insomnia, yet in-person CBT-I can often be challenging to access. Prior studies have used technology to bridge barriers but have been unable to extensively assess the impact of the digital therapeutic on real-world patient experience and multidimensional outcomes. Among patients with insomnia, our aim is to determine the impact of a prescription digital therapeutic (PDT) (PEAR-003b, FDA-authorised as Somryst; herein called PDT) that provides mobile-delivered CBT-I on patient-reported outcomes (PROs) and healthcare utilisation. Methods and analysis We are conducting a pragmatically designed, prospective, multicentre randomised controlled trial that leverages Hugo, a unique patient-centred health data-aggregating platform for data collection and patient follow-up from Hugo Health. A total of 100 participants with insomnia from two health centres will be enrolled onto the Hugo Health platform, provided with a linked Fitbit (Inspire 2) to track activity and then randomised 1:1 to receive (or not) the PDT for mobile-delivered CBT-I (Somryst). The primary outcome is a change in the insomnia severity index score from baseline to 9-week postrandomisation. Secondary outcomes include healthcare utilisation, health utility scores and clinical outcomes; change in sleep outcomes as measured with sleep diaries and a change in individual PROs including depressive symptoms, daytime sleepiness, health status, stress and anxiety. For those allocated to the PDT, we will also assess engagement with the PDT. Ethics and dissemination The Institutional Review Boards at Yale University and the Mayo Clinic have approved the trial protocol. This trial will provide important data to patients, clinicians and policymakers about the impact of the PDT device delivering CBT-I on PROs, clinical outcomes and healthcare utilisation. Findings will be disseminated to participants, presented at professional meetings and published in peer-reviewed journals. Trial registration number NCT04909229.

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Predictive Modeling of Mental Illness Onset Using Wearable Devices and Medical Examination Data: Machine Learning Approach (2022)

Frontiers in Digital Health

Authors: Saito, Tomoki; Suzuki, Hikaru; Kishi, Akifumi

Abstract

The prevention and treatment of mental illness is a serious social issue. Prediction and intervention, however, have been difficult because of lack of objective biomarkers for mental illness. The objective of this study was to use biometric data acquired from wearable devices as well as medical examination data to build a predictive model that can contribute to the prevention of the onset of mental illness. This was an observational study of 4,612 subjects from the health database of society-managed health insurance in Japan provided by JMDC Inc. The inputs to the predictive model were 3-months of continuous wearable data and medical examinations within and near that period; the output was the presence or absence of mental illness over the following month, as defined by insurance claims data. The features relating to the wearable data were sleep, activity, and resting heart rate, measured by a consumer-grade wearable device (specifically, Fitbit). The predictive model was built using the XGBoost algorithm and presented an area-under-the-receiver-operating-characteristic curve of 0.712 (SD = 0.02, a repeated stratified group 10-fold cross validation). The top-ranking feature importance measure was wearable data, and its importance was higher than the blood-test values from medical examinations. Detailed verification of the model showed that predictions were made based on disrupted sleep rhythms, mild physical activity duration, alcohol use, and medical examination data on disrupted eating habits as risk factors. In summary, the predictive model showed useful accuracy for grouping the risk of mental illness onset, suggesting the potential of predictive detection, and preventive intervention using wearable devices. Sleep abnormalities in particular were detected as wearable data 3 months prior to mental illness onset, and the possibility of early intervention targeting the stabilization of sleep as an effective measure for mental illness onset was shown.

Predictors of engagement with remote sensing technologies for symptom measurement in Major Depressive Disorder (2022)

Journal of Affective Disorders

Authors: Matcham, F.; Carr, E.; White, K. M.; Leightley, D.; Lamers, F.; Siddi, S.; Annas, P.; de Girolamo, G.; Haro, J. M.; Horsfall, M.; Ivan, A.; Lavelle, G.; Li, Q.; Lombardini, F.; Mohr, D. C.; Narayan, V. A.; Penninx, B. W. H. J.; Oetzmann, C.; Coromina, M.; Simblett, S. K.; Weyer, J.; Wykes, T.; Zorbas, S.; Brasen, J. C.; Myin-Germeys, I.; Conde, P.; Dobson, R. J. B.; Folarin, A. A.; Ranjan, Y.; Rashid, Z.; Cummins, N.; Dineley, J.; Vairavan, S.; Hotopf, M.

Abstract

Background Remote sensing for the measurement and management of long-term conditions such as Major Depressive Disorder (MDD) is becoming more prevalent. User-engagement is essential to yield any benefits. We tested three hypotheses examining associations between clinical characteristics, perceptions of remote sensing, and objective user engagement metrics. Methods The Remote Assessment of Disease and Relapse – Major Depressive Disorder (RADAR-MDD) study is a multicentre longitudinal observational cohort study in people with recurrent MDD. Participants wore a FitBit and completed app-based assessments every two weeks for a median of 18 months. Multivariable random effects regression models pooling data across timepoints were used to examine associations between variables. Results A total of 547 participants (87.8% of the total sample) were included in the current analysis. Higher levels of anxiety were associated with lower levels of perceived technology ease of use; increased functional disability was associated with small differences in perceptions of technology usefulness and usability. Participants who reported higher system ease of use, usefulness, and acceptability subsequently completed more app-based questionnaires and tended to wear their FitBit activity tracker for longer. All effect sizes were small and unlikely to be of practical significance. Limitations Symptoms of depression, anxiety, functional disability, and perceptions of system usability are measured at the same time. These therefore represent cross-sectional associations rather than predictions of future perceptions. Conclusions These findings suggest that perceived usability and actual use of remote measurement technologies in people with MDD are robust across differences in severity of depression, anxiety, and functional impairment.

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Prescribing Time in Nature for Human Health and Well-Being: Study Protocol for Tailored Park Prescriptions (2022)

Frontiers in Digital Health

Authors: Schultz, Courtney L.; Bocarro, Jason N.; Hipp, J. Aaron; Bennett, Gary J.; Floyd, Myron F.

Abstract

BACKGROUND: eHealth technologies offer an efficient method to integrate park prescriptions into clinical practice by primary health care (PHC) providers to help patients improve their health via tailored, nature-based health behavior interventions. This paper describes the protocol of the GoalRx Prescription Intervention (GPI) which was designed to leverage community resources to provide tailored park prescriptions for PHC patients. METHODS: The GPI study was designed as a 3-arm, multi-site observational study. We enrolled low-income, rural adults either at-risk of or living with hypertension or diabetes (n = 75) from Federally Qualified Health Centers (FQHC) in two counties in North Carolina, USA into the 3-month intervention. Eligible participants self-selected to receive (1) a tailored park prescription intervention; (2) a tailored home/indoor PA prescription intervention; or (3) a healthy eating prescription (with no PA prescription beyond standard PA counseling advice that is already routinely provided in PHC) as the comparison group. The GPI app paired patient health data from the electronic health record with stated patient preferences and triggered app-integrated SMS motivation and compliance messaging directly to the patient. Patients were assessed at baseline and at a 3-month follow-up upon the completion of the intervention. The primary outcome (mean difference in weekly physical activity from baseline (T0) to post-intervention (T1) as measured by the Fitbit Flex 2) was assessed at 3 months. Secondary outcomes included assessment of the relationship between the intervention and biological markers of health, including body mass index (BMI), systolic and diastolic blood pressure, HbA1c or available glucose test (if applicable), and a depression screen score using the Patient Health Questionnaire 9. Secondary outcomes also included the total number of SMS messages sent, number of SMS messages responded to, number of SMS messages ignored, and opt-out rate. DISCUSSION: The goal was to create a protocol utilizing eHealth technologies that addressed the specific needs of rural low-income communities and fit into the natural rhythms and processes of the selected FQHC clinics in North Carolina. This protocol offered a higher standard of health care by connecting patients to their PHC teams and increasing patient motivation to make longer-lasting health behavior changes.

PreScription DigitaL ThErapEutic for Patients with Insomnia (SLEEP-I): a protocol for a pragmatic randomised controlled trial (2022)

BMJ open

Authors: Dreyer, Rachel P.; Berkowitz, Alyssa; Yaggi, Henry Klar; Schneeberg, Lynelle; Shah, Nilay D.; Emanuel, Lindsay; Kolla, Bhanuprakash; Jeffery, Molly Moore; Deeg, Mark; Ervin, Keondae; Thorndike, Frances; Ross, Joseph S.

Abstract

INTRODUCTION: Cognitive behavioural therapy for insomnia (CBT-I) is effective at treating chronic insomnia, yet in-person CBT-I can often be challenging to access. Prior studies have used technology to bridge barriers but have been unable to extensively assess the impact of the digital therapeutic on real-world patient experience and multidimensional outcomes. Among patients with insomnia, our aim is to determine the impact of a prescription digital therapeutic (PDT) (PEAR-003b, FDA-authorised as Somryst; herein called PDT) that provides mobile-delivered CBT-I on patient-reported outcomes (PROs) and healthcare utilisation. METHODS AND ANALYSIS: We are conducting a pragmatically designed, prospective, multicentre randomised controlled trial that leverages Hugo, a unique patient-centred health data-aggregating platform for data collection and patient follow-up from Hugo Health. A total of 100 participants with insomnia from two health centres will be enrolled onto the Hugo Health platform, provided with a linked Fitbit (Inspire 2) to track activity and then randomised 1:1 to receive (or not) the PDT for mobile-delivered CBT-I (Somryst). The primary outcome is a change in the insomnia severity index score from baseline to 9-week postrandomisation. Secondary outcomes include healthcare utilisation, health utility scores and clinical outcomes; change in sleep outcomes as measured with sleep diaries and a change in individual PROs including depressive symptoms, daytime sleepiness, health status, stress and anxiety. For those allocated to the PDT, we will also assess engagement with the PDT. ETHICS AND DISSEMINATION: The Institutional Review Boards at Yale University and the Mayo Clinic have approved the trial protocol. This trial will provide important data to patients, clinicians and policymakers about the impact of the PDT device delivering CBT-I on PROs, clinical outcomes and healthcare utilisation. Findings will be disseminated to participants, presented at professional meetings and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04909229.

Protocol for a multi-center randomized controlled trial to evaluate the benefits of exercise incentives and corticosteroid injections in osteoarthritis of the knee (MOVE-OK) (2022)

Trials

Authors: Leach, William; Doherty, Caleigh; Olave, Marianna; England, Bryant R.; Wysham, Katherine; Kerr, Gail; Quinones, Mercedes; Ogdie, Alexis; White, Dan; Neogi, Tuhina; Scanzello, Carla R.; Baker, Joshua F.

Abstract

Background: Knee osteoarthritis (KOA) is a high-priority problem among the aging population. While exercise has been shown to be beneficial in management of the disease, scalable and low-cost interventions to improve exercise in this population are lacking. Recent controversy over the value of corticosteroid injections for palliation has also arisen. Therefore, we designed a randomized, double-blind, placebo-controlled clinical trial with a 2-period crossover design to study (1) behavioral incentives to promote exercise and (2) corticosteroid injections to reduce pain and improve function in patients with KOA when compared to lidocaine only. Methods: The study design is a pragmatic factorial and crossover randomized clinical trial. Patients with KOA who are deemed eligible by their provider to receive knee injections and are able to walk without assistive devices will be recruited from clinical practices at four sites within the Veterans Affairs (VA) Health System in the USA. In total, 220 participants will be randomized to receive social incentives with gamification (i.e., incorporation of game elements) to promote exercise and compared to controls that receive a Fitbit but no incentive. Each patient will also be assigned to receive a blinded corticosteroid injection and a lidocaine-only injection in random order. The primary outcomes are the change in average daily step counts from baseline and the change in Knee Osteoarthritis Outcome Score (KOOS) from baseline. The study team will continuously collect step count, heart rate, and sleep data using activity monitors and patient-reported outcomes using the Way to Health (WTH) platform at two four-week intervals over eight months of follow-up. Mixed effects regression incorporating all available data points will be used for analysis. Discussion: The "Marching on for Veterans with Osteoarthritis of the Knee" (MOVE-OK) trial will take a pragmatic approach to evaluate (1) whether incentives based on behaviorally enhanced gamification can improve physical activity in this patient population and (2) whether corticosteroids injections reduce pain and disability in patients with KOA. Results of this trial will help to direct clinical practice and inform management guidelines.

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Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review (2022)

JMIR mHealth and uHealth

Authors: Giurgiu, Marco; Timm, Irina; Becker, Marlissa; Schmidt, Steffen; Wunsch, Kathrin; Nissen, Rebecca; Davidovsky, Denis; Bussmann, Johannes B. J.; Nigg, Claudio R.; Reichert, Markus; Ebner-Priemer, Ulrich W.; Woll, Alex; von Haaren-Mack, Birte

Abstract

Background: Wearable technology is a leading fitness trend in the growing commercial industry and an established method for collecting 24-hour physical behavior data in research studies. High-quality free-living validation studies are required to enable both researchers and consumers to make guided decisions on which study to rely on and which device to use. However, reviews focusing on the quality of free-living validation studies in adults are lacking. Objective: This study aimed to raise researchers' and consumers' attention to the quality of published validation protocols while aiming to identify and compare specific consistencies or inconsistencies between protocols. We aimed to provide a comprehensive and historical overview of which wearable devices have been validated for which purpose and whether they show promise for use in further studies. Methods: Peer-reviewed validation studies from electronic databases, as well as backward and forward citation searches (1970 to July 2021), with the following, required indicators were included: protocol must include real-life conditions, outcome must belong to one dimension of the 24-hour physical behavior construct (intensity, posture or activity type, and biological state), the protocol must include a criterion measure, and study results must be published in English-language journals. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool with 9 questions separated into 4 domains (patient selection or study design, index measure, criterion measure, and flow and time). Results: Of the 13,285 unique search results, 222 (1.67%) articles were included. Most studies (153/237, 64.6%) validated an intensity measure outcome such as energy expenditure. However, only 19.8% (47/237) validated biological state and 15.6% (37/237) validated posture or activity-type outcomes. Across all studies, 163 different wearables were identified. Of these, 58.9% (96/163) were validated only once. ActiGraph GT3X/GT3X+ (36/163, 22.1%), Fitbit Flex (20/163, 12.3%), and ActivPAL (12/163, 7.4%) were used most often in the included studies. The percentage of participants meeting the quality criteria ranged from 38.8% (92/237) to 92.4% (219/237). On the basis of our classification tree to evaluate the overall study quality, 4.6% (11/237) of studies were classified as low risk. Furthermore, 16% (38/237) of studies were classified as having some concerns, and 72.9% (173/237) of studies were classified as high risk. Conclusions: Overall, free-living validation studies of wearables are characterized by low methodological quality, large variability in design, and focus on intensity. Future research should strongly aim at biological state and posture or activity outcomes and strive for standardized protocols embedded in a validation framework. Standardized protocols for free-living validation embedded in a framework are urgently needed to inform and guide stakeholders (eg, manufacturers, scientists, and consumers) in selecting wearables for self-tracking purposes, applying wearables in health studies, and fostering innovation to achieve improved validity.

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Quantitative activity levels and gestational age at delivery: a prospective cohort study among nulliparous women (2022)

American journal of obstetrics & gynecology MFM

Authors: Booker, Whitney A.; Ekpe, Etoroabasi E.; Handal-Orefice, Roxane C.; Zhang, Yuan; Cande, Ananth; Gyamfi-Bannerman, Cynthia; Nieto, Vanessa

Abstract

OBJECTIVE: Despite the knowledge that bed rest does not reduce the risk of preterm birth (PTB), it continues to be recommended by many providers worldwide. This is because there are no quantitative data assessing the relationship between PTB and physical activity in pregnancy.1–3 We designed a prospective cohort study using a Fitbit activity tracker to quantitatively explore the association between baseline physical activity in pregnancy in steps/day and the risk of PTB (<37 weeks). STUDY DESIGN: This was a prospective cohort study assessing the association between the risk of PTB and physical activity in healthy nulliparous women from 10 to 24 weeks to delivery. The physical activity (San Francisco, California) was measured from the time of entry into the study until the day before admission for delivery using the Fitbit Flex 2. The participants wore the faceless device 24/7 without modifying their activity. The primary exposure was steps/day in low- (<5000 steps/d) and high-level (≥5000 steps/d) activity groups. The primary outcome was the rate of PTB (<37 weeks). An additional unplanned secondary analysis was performed using a 3500 steps/d cutoff. The secondary outcomes included peripartum complications and median steps/day in term vs preterm groups. Adjusted analyses were performed to account for possible confounders. RESULTS: A total of 134 women were enrolled, of which 25 (19%) and 109 (81%) were in the low- and high-level activity groups, respectively. Overall, 11 (8.2%) women delivered preterm. The high-level activity group was older, partnered, employed, and had a higher education level. The PTB did not differ between the groups (adjusted risk ratio, 0.99; 95% confidence interval [CI], 0.99–1.00) (Table). There was no difference in the median steps/d between preterm and term deliveries (7767 interquartile range, [5188–10,387] vs 6986 [5412–8528]); percentile difference, −442; (95% CI, −2233 to 1507) steps. Using a 3500 steps/d cutoff, there was a 75% reduction in the PTB risk (29% vs 7%, respectively; risk ratio, 0.25; 95% CI, 0.05–2.35) (Table). CONCLUSION: This prospective study of nulliparous women showed no difference in the risk of PTB between low- vs high-activity groups using a cutoff of 5000 steps/d. The gestational age at delivery was similar between the groups. No significant difference in the number of steps/d was observed between women who delivered preterm compared with term. The women who were prescribed activity restriction (AR) had a marked reduction in their median number of steps/d after AR was prescribed. However, their median number of steps per day (>5000) reflected that they remained active despite this instruction. An additional analysis using 3500 steps/d as a cutoff for exposure groups showed a significantly increased risk of PTB in the <3500 steps/d group than the ≥3500 steps/d group. It is therefore plausible that activity levels <3500 steps/d are associated with an increased risk of PTB.

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Reference Values for Wristband Accelerometry Data in Children Aged 6-11 Years of Age (2022)

Frontiers in pediatrics

Authors: Lammers, Astrid E.; Romanowski, Anna Lena; Baumgartner, Helmut; Diller, Gerhard-Paul; Uebing, Anselm

Abstract

Objectives: Wristband activity trackers (accelerometers) could serve as a convenient monitoring tool to continuously quantify physical activity throughout the day. We aim to provide reference values for the use of these devices in healthy children. Methods: Children were recruited at a local school and provided with activity trackers (Fitbit Charge 2). Pupils were instructed to wear devices during all normal daytime activities over a period of 11-15 days. Demographic data, total number of daily steps and heart rate were recorded. In addition, all children/parents were asked to complete a questionnaire providing information about daily physical routine (mode of transport to school, sporting activities as well as sport club memberships). Results: Three hundred two children (54.6% boys; median age 8.7 years) participated in this prospective study. Median wearing time of the device was 12.1 h/day. Overall, the median daily total step count was 12,095. Median step counts/day were significantly higher in boys compared to girls (13,015 vs. 11,305 steps/day; p < 0.0001). In addition, step counts were significantly higher during the week, compared to weekend days. The effect of age on daily step count was found to be non-linear: the total daily step count increased from 6 to 8.5 years of age, while older children (aged >8.5 years) had lower step counts compared to the younger children. Significant predictors of the daily step count were male gender (+1,324.9 steps, p = 0.0008), mode of transportation to school (walking, bicycle, scooter: +865.5 steps p = 0.049), active membership in a sports club (+1,324.9 steps/day, p = 0.0008), and number of structured units of physical exercise performed (+336.5/per 45 min, p < 0.0001). Severe obesity was associated with a significant reduction in total daily step count (-3037.7 steps/day, p = 0.015). Conclusion: Our prospective cohort study of healthy school children provides reference values for wristband accelerometers in normal individuals. In addition, it clarifies the effect of age, body weight and lifestyle on normal daily step counts in school children. This data should be helpful to judge the degree of physical limitation of patients compared to healthy peers.

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Responsiveness of an activity tracker as a measurement tool in a knee osteoarthritis clinical trial (ACTIVe-OA study) (2022)

Annals of physical and rehabilitation medicine

Authors: Yu, Shirley P.; Ferreira, Manuela L.; Duong, Vicky; Caroupapoull{\'{e}}, Jimmy; Arden, Nigel K.; Bennell, Kim L.; Hunter, David J.

Abstract

Background: In osteoarthritis (OA) clinical trials, reliable and responsive outcome measures to document physical and functional improvements are limited. Objective: This study aimed to assess whether the use of an activity tracker in an OA clinical trial is a responsive measurement tool. Secondary objectives assessed feasibility and validity. Methods: We recruited 65 participants in a prospective cohort study nested in a placebo-controlled clinical trial of platelet-rich plasma injection in knee OA. Participants wore an activity tracker (Fitbit Flex 2), and a smartphone was preloaded with a mobile application (OApp) designed to monitor load rates as a surrogate of knee loading. Participants used the systems for 7 days at baseline and for 7 days before the 2-month follow-up assessment. Effect size (ES) and standardised response mean (SRM) were calculated for change in step count and knee loading rate and regularly used knee OA outcome measures. Correlation coefficients (r) were calculated to examine the strength of the association between outcome measures. Results:. Step count showed a trivial ES and SRM and mean knee loading rate measurements a moderate ES and SRM. We found a weak but significant correlation between change in mean steps per day and global improvement overall (r= 0.28) and Western Ontario and McMaster Universities Osteoarthritis Index function (r = -0.28). Compliance was high with the activity trackers. Conclusions: Despite good feasibility, this study did not show significant responsiveness or validity of the activity trackers as compared with currently recommended outcome measures in OA clinical trials. The main challenge is the lack of a gold standard outcome measure to validate against, and because of the complex interplay between pain and measured function, a lack of correlation does not necessarily represent a failed validation in this context. Australian New Zealand Clinical Trials Registry: ACTRN12617000853347. This trial is a substudy of the “Platelet-rich plasma as a symptom-and disease-modifying treatment for knee osteoarthritis – the RESTORE trial”.

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Risk Factors for COVID-19 in College Students Identified by Physical, Mental, and Social Health Reported During the Fall 2020 Semester: Observational Study Using the Roadmap App and Fitbit Wearable Sensors (2022)

JMIR mental health

Authors: Gilley, Kristen N.; Baroudi, Loubna; Yu, Miao; Gainsburg, Izzy; Reddy, Niyanth; Bradley, Christina; Cislo, Christine; Rozwadowski, Michelle Lois; Clingan, Caroline Ashley; DeMoss, Matthew Stephen; Churay, Tracey; Birditt, Kira; Colabianchi, Natalie; Chowdhury, Mosharaf; Forger, Daniel; Gagnier, Joel; Zernicke, Ronald F.; Cunningham, Julia Lee; Cain, Stephen M.; Tewari, Muneesh; Choi, Sung Won

Abstract

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic triggered a seismic shift in education, to online learning. With nearly 20 million students enrolled in colleges across the U.S., the long-simmering mental health crisis in college students was likely further exacerbated by the pandemic. OBJECTIVE: This study leveraged mobile health (mHealth) technology and sought to: i) characterize self-reported outcomes of physical, mental, and social health by COVID-19 status; ii) assess physical activity through consumer-grade wearable sensors (Fitbit{\textregistered}); and iii) identify risk factors associated with COVID-19 positivity in a population of college students prior to release of the vaccine. METHODS: Detailed methods were previously published in JMIR Res Protocols (Cislo et al). After completing a baseline assessment (i.e., Time 0 [T0]) of demographics, mental, and social health constructs through the Roadmap 2.0 app, participants were instructed to use the app freely, to wear the Fitbit{\textregistered}, and complete subsequent assessments at T1, T2 and T3, followed by a COVID-19 assessment of history and timing of COVID-19 testing and diagnosis (T4: $\sim$14 days after T3). Continuous measures were described using means (M) and standard deviations (SD), while categorical measures were summarized using frequencies and proportions. Formal comparisons were made based on COVID-19 status. The multivariate model was determined by entering all statistically significant variables (P<.05) in univariable associations at once and then removing one variable at a time by backward selection until the optimal model was obtained. RESULTS: During the fall 2020 semester, 1,997 participants consented, enrolled, and met criteria for data analyses. There was a high prevalence of anxiety, as assessed by the State Trait Anxiety Index (STAI), with moderate and severe levels in N=465 (24%) and N=970 (49%) students, respectively. Approximately, one-third of students reported having a mental health disorder (N=656, 33%). The average daily steps recorded in this student population was approximately 6500 (M=6474, SD=3371). Neither reported mental health nor step count were significant based on COVID-19 status (P=.52). Our analyses revealed significant associations of COVID-positivity with use of marijuana and alcohol (P =.020 and .046, respectively) and lower belief in public health measures (P=.003). In addition, graduate students were less likely and those with ≥20 roommates were more likely to report a COVID-19 diagnosis (P=.009). CONCLUSIONS: Mental health problems were common in this student population. Several factors, including substance use, were associated with risk of COVID-19. These data highlight important areas for further attention, such as prioritizing innovative strategies that address health and well-being, considering the potential long-term effects of COVID-19 on college students. CLINICALTRIAL: ClinicalTrials.gov NCT04766788. INTERNATIONAL REGISTERED REPORT: RR2-10.2196/29561.

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Sex-based differences in remote monitoring of biometric, psychometric and biomarker indices in stable ischemic heart disease (2022)

Biology of sex differences

Authors: Barsky, Lili; Speier, William; Fuller, Garth; Cheng, Susan; Kim, Andy; Joung, Sandy; Arnold, Corey; Dhawan, Shivani; Lopez, Mayra; Mastali, Mitra; van den Broek, Irene; Wei, Janet; Spiegel, Brennan; Van Eyk, Jennifer E.; Bairey Merz, C. Noel; Shufelt, Chrisandra

Abstract

Background: Sex-based differences are crucial to consider in the formulation of a personalized treatment plan. We evaluated sex-based differences in adherence and remotely monitored biometric, psychometric, and biomarker data among patients with stable ischemic heart disease (IHD). Methods: The Prediction, Risk, and Evaluation of Major Adverse Cardiac Events (PRE-MACE) study evaluated patients with stable IHD over a 12-week period. We collected biometric and sleep data using remote patient monitoring via FitBit and psychometric data from Patient-Reported Outcomes Measurement Information System (PROMIS), Kansas City Cardiomyopathy (KCC) and Seattle Angina Questionnaire-7 (SAQ-7) questionnaires. Serum biomarker levels were collected at the baseline visit. We explored sex-based differences in demographics, adherence to study protocols, biometric data, sleep, psychometric data, and biomarker levels. Results: There were 198 patients enrolled, with mean age 65.5 ± 11 years (± Standard deviation, SD), and 60% were females. Females were less adherent to weekly collection of PROMIS, KCC and SAQ-7 physical limitations questionnaires (all p < 0.05), compared to males. There was no difference in biometric physical activity. There was a statistically significant (p < 0.05) difference in sleep duration between sexes, with females sleeping 6 min longer. However, females reported higher PROMIS sleep disturbance scores (p < 0.001) and poorer psychometric scores overall (p < 0.05). A higher proportion of males had clinically significant elevations of median N-terminal pro-brain natriuretic peptide (p = 0.005) and high-sensitivity cardiac troponin levels (p < 0.001) compared to females. Conclusions: Among females and males with stable IHD, there are sex-based differences in remote monitoring behavior and data. Females are less adherent to psychometric data collection and report poorer psychometric and sleep quality scores than males. Elevated levels of biomarkers for MACE are more common in males. These findings may improve sex-specific understanding of IHD using remote patient monitoring.

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Sign of the times: Community engagement to refine a cardiovascular mHealth intervention through a virtual focus group series during the COVID-19 Pandemic (2022)

Digital health

Authors: Brewer, LaPrincess C.; Cyriac, Jissy; Kumbamu, Ashok; Burke, Lora E.; Jenkins, Sarah; Hayes, Sharonne N.; Jones, Clarence; Cooper, Lisa A.; Patten, Christi A.

Abstract

Background: African-Americans are underrepresented in mobile health intervention research studies which can perpetuate health inequities and the digital divide. A community-based, user-centered approach to designing mobile health interventions may increase their sociocultural relevance and effectiveness, especially with increased smartphone use during the coronavirus disease 2019 pandemic. We aimed to refine an existing mobile health intervention via a virtual focus group series. Methods: African-American community members (n = 15) from churches in Minneapolis-St. Paul and Rochester, Minnesota were enrolled in a virtual (via videoconferencing), three-session focus group series over five months to refine a cardiovascular health-focused mobile health application (FAITH! [Fostering African-American Improvement in Total Health!] App). Participants accessed the app via their smartphones and received a Fitbit synced to the app. Participants engaged with multimedia cardiovascular health-focused education modules, a sharing board for social networking, and diet/physical activity self-monitoring. Participant feedback on app features prompted iterative revisions to the FAITH! App. Primary outcomes were app usability (assessed via Health Information Technology Usability Evaluation Scale range: 0-5) and user satisfaction. Results: Participants (mean age [SD]: 56.9 [12.3] years, 86.7% female) attended a mean 2.8 focus groups (80% attended all sessions). The revised FAITH! App exceeded the goal Health Information Technology Usability Evaluation Scale score threshold of ≥4 (mean: 4.39, range: 3.20-4.95). Participants positively rated updated app content, visual appeal, and use of social incentives to maintain engagement. Increasing user control and refinement of the moderated sharing board were identified as areas for future improvement. Conclusions: Community-partnered, virtual focus groups can optimize usability and increase participant satisfaction of mobile health lifestyle interventions that aim to promote cardiovascular health in African-Americans.

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Sleep and seizure risk in epilepsy: bed and wake times are more important than sleep duration (2022)

Brain: A Journal of Neurology

Authors: Stirling, Rachel E.; Hidajat, Cindy M.; Grayden, David B.; D'Souza, Wendyl J.; Naim-Feil, Jodie; Dell, Katrina L.; Schneider, Logan D.; Nurse, Ewan; Freestone, Dean; Cook, Mark J.; Karoly, Philippa J.

Abstract

Sleep duration, sleep deprivation and the sleep-wake cycle are thought to play an important role in the generation of epileptic activity and may also influence seizure risk. Hence, people diagnosed with epilepsy are commonly asked to maintain consistent sleep routines. However, emerging evidence paints a more nuanced picture of the relationship between seizures and sleep, with bidirectional effects between changes in sleep and seizure risk in addition to modulation by sleep stages and transitions between stages. We conducted a longitudinal study investigating sleep parameters and self-reported seizure occurrence in an ambulatory at-home setting using mobile and wearable monitoring. Sixty subjects wore a Fitbit smartwatch for at least 28 days while reporting their seizure activity in a mobile app. Multiple sleep features were investigated, including duration, oversleep and undersleep, and sleep onset and offset times. Sleep features in participants with epilepsy were compared to a large (n = 37921) representative population of Fitbit users, each with 28 days of data. For participants with at least 10 seizure days (n = 34), sleep features were analysed for significant changes prior to seizure days. A total of 4956 reported seizures (M = 83, SD = 130) and 30485 recorded sleep nights (M = 508, SD = 445) were included in the study. There was a trend for participants with epilepsy to sleep longer than the general population, although this difference was not significant. Just 5 of 34 participants showed a significant difference in sleep duration the night before seizure days compared to seizure-free days. However, 14 of 34 subjects showed significant differences between their sleep onset (bed) and/or offset (wake) times prior to seizure occurrence. In contrast to previous studies, the current study found undersleeping was associated with a marginal 2\% decrease in seizure risk in the following 48 h (p {\textless} 0.01). Nocturnal seizures were associated with both significantly longer sleep durations and increased risk of a seizure occurring in the following 48 h. Overall, the presented results demonstrated that day-to-day changes in sleep duration had a minimal effect on reported seizures, while patient-specific changes in bed- and wake-times were more important for identifying seizure risk the following day. Nocturnal seizures were the only factor that significantly increased the risk of seizures in the following 48 h on a group level. Wearables can be utilised to identify these sleep-seizure relationships and guide clinical recommendations or improve seizure forecasting algorithms.

Step-count outcomes of 13 different activity trackers: Results from laboratory and free-living experiments (2022)

Gait \& Posture

Authors: Nakagata, Takashi; Murakami, Haruka; Kawakami, Ryoko; Tripette, Julien; Nakae, Satoshi; Yamada, Yosuke; Ishikawa-Takata, Kazuko; Tanaka, Shigeho; Miyachi, Motohiko

Abstract

BACKGROUND: Many activity trackers have been developed, but steps can still be inconsistent from one monitor to another. RESEARCH QUESTION: What are the differences and associations between the steps of 13 selected consumer-based and research-grade wearable devices during 1 standardized day in a metabolic chamber and 15-day free-living trials? METHODS: In total, 19 healthy adults between 21 and 50 years-old participated in this study. Participants were equipped with 12 accelerometer-based active trackers and one pedometer (Yamasa) in order to monitor the number of steps per day. The devices were worn on the waist (ActiGraph, Omron, Actimarker, Lifedorder, Withings, and Yamasa) or non-dominant wrist (Fitbit, Garmin, Misfit, EPSON, and Jawbone), or placed in a pocket (Omron CaloriScan, and TANITA). Participants performed structured activities over a 24 h period in a chamber (Standardized day), and steps were monitored in the same participants in free-living trials for 15 successive days using the same monitors (free-living days). RESULTS: When the 13 monitors were ranked by their steps, waist-worn ActiGraph was located at the center (7th) of the monitors both in the Standardized (12,252 ± 598 steps/day, mean ± SD) and free-living days (9295 ± 4027 steps/day). The correlation between the accelerometer-based devices was very high (r = 0.87-0.99). However, the steps of Yamasa was significantly lower in both trials than ActiGraph. The wrist-worn accelerometers had significantly higher steps than other devices both trials (P {\textless} 0.05). The differences between ActiGraph and Actimarker or Lifecorder was less than 100 steps/day in the Standardized day, and the differences between ActiGraph and Active Style Pro was less than 100 steps/day in the free-living days. Regression equation was also performed for inter-device compatibility. SIGNIFICANCE: Step obtained from the wrist-worn, waist-worn, and pocket-type activity trackers were significantly different from each other but still highly correlated in free-living conditions.

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Systematic Review of Fitbit Charge 2 Validation Studies for Exercise Tracking (2022)

Translational Journal of the American College of Sports Medicine

Authors: Irwin, Crista; Gary, Rebecca

Abstract

CONTEXT: There are research-grade devices that have been validated to measure either heart rate (HR) by electrocardiography (ECG) with a Polar chest strap, or step count with ACTiGraph accelerometer. However, wearable activity trackers that measure HR and steps concurrently have been tested against research-grade accelerometers and HR monitors with conflicting results. This review examines validation studies of the Fitbit Charge 2 (FBC2) for accuracy in measuring HR and step count and evaluates the device's reliability for use by researchers and clinicians. DESIGN: This registered review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The robvis (risk-of-bias visualization) tool was used to assess the strength of each considered article. ELIGIBILITY CRITERIA: Eligible articles published between 2018 and 2019 were identified using PubMed, CINHAL, Embase, Cochran, and World of Science databases and hand-searches. All articles were HR and/or step count validation studies for the FBC2 in adult ambulatory populations. STUDY SELECTION: Eight articles were examined in accordance with the eligibility criteria alignment and agreement among the authors and research librarian. MAIN OUTCOME MEASURES: Concordance correlation coefficients (CCC) were used to measure agreement between the tracker and criterion devices. Mean absolute percent error (MAPE) was used to average the individual absolute percent errors. RESULTS: Studies that measured CCC found agreement between the FBC2 and criterion devices ranged between 26\% and 92\% for HR monitoring, decreasing in accuracy as exercise intensity increased. Inversely, CCC increased from 38\% to 99\% for step count when exercise intensity increased. HR error between MAPE was 9.21\% to 68\% and showed more error as exercise intensity increased. Step measurement error MAPE was 12\% for healthy persons aged 24-72 years but was reported at 46\% in an older population with heart failure. CONCLUSIONS: Relative agreement with criterion and low-to-moderate MAPE were consistent in most studies reviewed and support validation of the FBC2 to accurately measure HR at low or moderate exercise intensities. However, more investigation controlling testing and measurement congruency is needed to validate step capabilities. The literature supports the validity of the FBC2 to accurately monitor HR, but for step count is inconclusive so the device may not be suitable for recommended use in all populations.

The Development of a Novel mHealth Tool for Obstructive Sleep Apnea: Tracking Continuous Positive Airway Pressure Adherence as a Percentage of Time in Bed (2022)

Journal of Medical Internet Research

Authors: Pfammatter, Angela Fidler; Hughes, Bonnie Olivia; Tucker, Becky; Whitmore, Harry; Spring, Bonnie; Tasali, Esra

Abstract

Background: Continuous positive airway pressure (CPAP) is the mainstay obstructive sleep apnea (OSA) treatment; however, poor adherence to CPAP is common. Current guidelines specify 4 hours of CPAP use per night as a target to define adequate treatment adherence. However, effective OSA treatment requires CPAP use during the entire time spent in bed to optimally treat respiratory events and prevent adverse health effects associated with the time spent sleeping without wearing a CPAP device. Nightly sleep patterns vary considerably, making it necessary to measure CPAP adherence relative to the time spent in bed. Weight loss is an important goal for patients with OSA. Tools are required to address these clinical challenges in patients with OSA. Objective: This study aimed to develop a mobile health tool that combined weight loss features with novel CPAP adherence tracking (ie, percentage of CPAP wear time relative to objectively assessed time spent in bed) for patients with OSA. Methods: We used an iterative, user-centered process to design a new CPAP adherence tracking module that integrated with an existing weight loss app. A total of 37 patients with OSA aged 20 to 65 years were recruited. In phase 1, patients with OSA who were receiving CPAP treatment (n=7) tested the weight loss app to track nutrition, activity, and weight for 10 days. Participants completed a usability and acceptability survey. In phase 2, patients with OSA who were receiving CPAP treatment (n=21) completed a web-based survey about their interpretations and preferences for wireframes of the CPAP tracking module. In phase 3, patients with recently diagnosed OSA who were CPAP naive (n=9) were prescribed a CPAP device (ResMed AirSense10 AutoSet) and tested the integrated app for 3 to 4 weeks. Participants completed a usability survey and provided feedback. Results: During phase 1, participants found the app to be mostly easy to use, except for some difficulty searching for specific foods. All participants found the connected devices (Fitbit activity tracker and Fitbit Aria scale) easy to use and helpful. During phase 2, participants correctly interpreted CPAP adherence success, expressed as percentage of wear time relative to time spent in bed, and preferred seeing a clearly stated percentage goal ("Goal: 100%"). In phase 3, participants found the integrated app easy to use and requested push notification reminders to wear CPAP before bedtime and to sync Fitbit in the morning. Conclusions: We developed a mobile health tool that integrated a new CPAP adherence tracking module into an existing weight loss app. Novel features included addressing OSA-obesity comorbidity, CPAP adherence tracking via percentage of CPAP wear time relative to objectively assessed time spent in bed, and push notifications to foster adherence. Future research on the effectiveness of this tool in improving OSA treatment adherence is warranted.

The Effect of Tailored, Daily, Smartphone Feedback to Lifestyle Self-Monitoring on Weight Loss at 12 Months: the SMARTER Randomized Clinical Trial (2022)

Journal of medical Internet research

Authors: Burke, Lora E.; Sereika, Susan M.; Bizhanova, Zhadyra; Parmanto, Bambang; Kariuki, Jacob; Cheng, Jessica; Beatrice, Britney; Cedillo, Maribel; Loar, India; Pulantara, I. Wayan; Wang, Yuhan; Conroy, Molly B.

Abstract

Background: Self-monitoring (SM) is the centerpiece of behavioral weight loss treatment, but the efficacy of smartphone-delivered SM feedback (FB) has not been tested in large, long-term, randomized trials. Objective: The aim of this study was to establish the efficacy of providing remote FB to diet, physical activity (PA), and weight SM on improving weight loss outcomes when comparing the SM plus FB (SM+FB) condition to the SM-only condition in a 12-month randomized controlled trial. The study was a single-site, population-based trial that took place in southwestern Pennsylvania, USA, conducted between 2018 and 2021. Participants were smartphone users age ≥18 years, able to engage in moderate PA, with a mean BMI between 27 and 43 kg/m2. Methods: All participants received a 90-minute, one-to-one, in-person behavioral weight loss counseling session addressing behavioral strategies, establishing participants' dietary and PA goals, and instructing on use of the PA tracker (Fitbit Charge 2), smart scale, and diet SM app. Only SM+FB participants had access to an investigator-developed smartphone app that read SM data, in which an algorithm selected tailored messages sent to the smartphone up to 3 times daily. The SM-only participants did not receive any tailored FB based on SM data. The primary outcome was percent weight change from baseline to 12 months. Secondary outcomes included engagement with digital tools (eg, monthly percentage of FB messages opened and monthly percentage of days adherent to the calorie goal). Results: Participants (N=502) were on average 45.0 (SD 14.4) years old with a mean BMI of 33.7 (SD 4.0) kg/m2. The sample was 79.5% female (n=399/502) and 82.5% White (n=414/502). At 12 months, retention was 78.5% (n=394/502) and similar by group (SM+FB: 202/251, 80.5%; SM: 192/251, 76.5%; P=.28). There was significant percent weight loss from baseline in both groups (SM+FB: -2.12%, 95% CI -3.04% to -1.21%, P<.001; SM: -2.39%, 95% CI -3.32% to -1.47%; P<.001), but no difference between the groups (-0.27%; 95% CI -1.57% to 1.03%; t =-0.41; P=.68). Similarly, 26.3% (66/251) of the SM+FB group and 29.1% (73/251) of the SM group achieved ≥5% weight loss (chi-square value=0.49; P=.49). A 1% increase in FB messages opened was associated with a 0.10 greater percent weight loss at 12 months (b=-0.10; 95% CI -0.13 to -0.07; t =-5.90; P<.001). A 1% increase in FB messages opened was associated with 0.12 greater percentage of days adherent to the calorie goal per month (b=0.12; 95% CI 0.07-0.17; F=22.19; P<.001). Conclusions: There were no significant between-group differences in weight loss; however, the findings suggested that the use of commercially available digital SM tools with or without FB resulted in a clinically significant weight loss in over 25% of participants. Future studies need to test additional strategies that will promote greater engagement with digital tools.

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The Effectiveness of a Computer-Tailored Web-Based Physical Activity Intervention Using Fitbit Activity Trackers in Older Adults (Active for Life): Randomized Controlled Trial (2022)

Journal of medical Internet research

Authors: Alley, Stephanie J.; van Uffelen, Jannique; Schoeppe, Stephanie; Parkinson, Lynne; Hunt, Susan; Power, Deborah; Waterman, Natasha; Waterman, Courtney; To, Quyen G.; Duncan, Mitch J.; Schneiders, Anthony; Vandelanotte, Corneel

Abstract

Background Physical activity is an integral part of healthy aging; yet, most adults aged ≥65 years are not sufficiently active. Preliminary evidence suggests that web-based interventions with computer-tailored advice and Fitbit activity trackers may be well suited for older adults. Objective The aim of this study was to examine the effectiveness of Active for Life, a 12-week web-based physical activity intervention with 6 web-based modules of computer-tailored advice to increase physical activity in older Australians. Methods Participants were recruited both through the web and offline and were randomly assigned to 1 of 3 trial arms: tailoring+Fitbit, tailoring only, or a wait-list control. The computer-tailored advice was based on either participants’ Fitbit data (tailoring+Fitbit participants) or self-reported physical activity (tailoring-only participants). The main outcome was change in wrist-worn accelerometer (ActiGraph GT9X)–measured moderate to vigorous physical activity (MVPA) from baseline to after the intervention (week 12). The secondary outcomes were change in self-reported physical activity measured by means of the Active Australia Survey at the midintervention point (6 weeks), after the intervention (week 12), and at follow-up (week 24). Participants had a face-to-face meeting at baseline for a demonstration of the intervention and at baseline and week 12 to return the accelerometers. Generalized linear mixed model analyses were conducted with a γ distribution and log link to compare MVPA and self-reported physical activity changes over time within each trial arm and between each of the trial arms. Results A total of 243 participants were randomly assigned to tailoring+Fitbit (n=78, 32.1%), tailoring only (n=96, 39.5%), and wait-list control (n=69, 28.4%). Attrition was 28.8% (70/243) at 6 weeks, 31.7% (77/243) at 12 weeks, and 35.4% (86/243) at 24 weeks. No significant overall time by group interaction was observed for MVPA (P=.05). There were no significant within-group changes for MVPA over time in the tailoring+Fitbit group (+3%, 95% CI –24% to 40%) or the tailoring-only group (–4%, 95% CI –24% to 30%); however, a significant decline was seen in the control group (–35%, 95% CI –52% to –11%). The tailoring+Fitbit group participants increased their MVPA 59% (95% CI 6%-138%) more than those in the control group. A significant time by group interaction was observed for self-reported physical activity (P=.02). All groups increased their self-reported physical activity from baseline to week 6, week 12, and week 24, and this increase was greater in the tailoring+Fitbit group than in the control group at 6 weeks (+61%, 95% CI 11%-133%). Conclusions A computer-tailored physical activity intervention with Fitbit integration resulted in improved MVPA outcomes in comparison with a control group in older adults.

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The effectiveness of the Structured Health Intervention For Truckers (SHIFT): a cluster randomised controlled trial (RCT) (2022)

BMC Medicine

Authors: Clemes, Stacy A.; Varela-Mato, Veronica; Bodicoat, Danielle H.; Brookes, Cassandra L.; Chen, Yu-Ling; Edwardson, Charlotte L.; Gray, Laura J.; Guest, Amber J.; Johnson, Vicki; Munir, Fehmidah; Paine, Nicola J.; Richardson, Gerry; Ruettger, Katharina; Sayyah, Mohsen; Sherry, Aron; Paola, Ana Suazo Di; Troughton, Jacqui; Yates, Thomas; King, James A.

Abstract

Background Long distance heavy goods vehicle (HGV) drivers exhibit higher than nationally representative rates of obesity, and obesity-related co-morbidities, and are underserved in terms of health promotion initiatives. The purpose of this study was to evaluate the effectiveness of the multicomponent ‘Structured Health Intervention For Truckers’ (SHIFT), compared to usual care, at 6- and 16–18-month follow-up. Methods We conducted a two-arm cluster RCT in transport sites throughout the Midlands, UK. Outcome measures were assessed at baseline, at 6- and 16–18-month follow-up. Clusters were randomised (1:1) following baseline measurements to either the SHIFT arm or usual practice control arm. The 6-month SHIFT programme included a group-based interactive 6-h education and behaviour change session, health coach support and equipment provision (Fitbit® and resistance bands/balls to facilitate a ‘cab workout’). The primary outcome was device-assessed physical activity (mean steps/day) at 6 months. Secondary outcomes included the following: device-assessed sitting, physical activity intensity and sleep; cardiometabolic health, diet, mental wellbeing and work-related psychosocial variables. Data were analysed using mixed-effect linear regression models using a complete-case population. Results Three hundred eighty-two HGV drivers (mean ± SD age: 48.4 ± 9.4 years, BMI: 30.4 ± 5.1 kg/m2, 99% male) were recruited across 25 clusters (sites) and randomised into either the SHIFT (12 clusters, n = 183) or control (13 clusters, n = 199) arms. At 6 months, 209 (55%) participants provided primary outcome data. Significant differences in mean daily steps were found between groups, in favour of the SHIFT arm (adjusted mean difference: 1008 steps/day, 95% CI: 145–1871, p = 0.022). Favourable differences were also seen in the SHIFT group, relative to the control group, in time spent sitting (− 24 mins/day, 95% CI: − 43 to − 6), and moderate-to-vigorous physical activity (6 mins/day, 95% CI: 0.3–11). Differences were not maintained at 16–18 months. No differences were observed between groups in the other secondary outcomes at either follow-up. Conclusions The SHIFT programme led to a potentially clinically meaningful difference in daily steps, between trial arms, at 6 months. Whilst the longer-term impact is unclear, the programme offers potential to be incorporated into driver training courses to promote activity in this at-risk, underserved and hard-to-reach essential occupational group.

The structured health intervention for truckers (SHIFT) cluster randomised controlled trial: a mixed methods process evaluation (2022)

The international journal of behavioral nutrition and physical activity

Authors: Guest, Amber J.; Paine, Nicola J.; Chen, Yu-Ling; Chalkley, Anna; Munir, Fehmidah; Edwardson, Charlotte L.; Gray, Laura J.; Johnson, Vicki; Ruettger, Katharina; Sayyah, Mohsen; Sherry, Aron; Troughton, Jacqui; Varela-Mato, Veronica; Yates, Thomas; King, James; Clemes, Stacy A.

Abstract

BACKGROUND: Long distance heavy goods vehicle (HGV) drivers exhibit higher than nationally representative rates of obesity, and obesity-related co-morbidities, and are underserved in terms of health promotion initiatives. The purpose of this study was to evaluate the effectiveness of the multicomponent 'Structured Health Intervention For Truckers' (SHIFT), compared to usual care, at 6- and 16-18-month follow-up. METHODS: We conducted a two-arm cluster RCT in transport sites throughout the Midlands, UK. Outcome measures were assessed at baseline, at 6- and 16-18-month follow-up. Clusters were randomised (1:1) following baseline measurements to either the SHIFT arm or usual practice control arm. The 6-month SHIFT programme included a group-based interactive 6-h education and behaviour change session, health coach support and equipment provision (Fitbit{\textregistered} and resistance bands/balls to facilitate a 'cab workout'). The primary outcome was device-assessed physical activity (mean steps/day) at 6 months. Secondary outcomes included the following: device-assessed sitting, physical activity intensity and sleep; cardiometabolic health, diet, mental wellbeing and work-related psychosocial variables. Data were analysed using mixed-effect linear regression models using a complete-case population. RESULTS: Three hundred eighty-two HGV drivers (mean ± SD age: 48.4 ± 9.4 years, BMI: 30.4 ± 5.1 kg/m(2), 99% male) were recruited across 25 clusters (sites) and randomised into either the SHIFT (12 clusters, n = 183) or control (13 clusters, n = 199) arms. At 6 months, 209 (55%) participants provided primary outcome data. Significant differences in mean daily steps were found between groups, in favour of the SHIFT arm (adjusted mean difference: 1008 steps/day, 95% CI: 145-1871, p = 0.022). Favourable differences were also seen in the SHIFT group, relative to the control group, in time spent sitting (- 24 mins/day, 95% CI: - 43 to - 6), and moderate-to-vigorous physical activity (6 mins/day, 95% CI: 0.3-11). Differences were not maintained at 16-18 months. No differences were observed between groups in the other secondary outcomes at either follow-up. CONCLUSIONS: The SHIFT programme led to a potentially clinically meaningful difference in daily steps, between trial arms, at 6 months. Whilst the longer-term impact is unclear, the programme offers potential to be incorporated into driver training courses to promote activity in this at-risk, underserved and hard-to-reach essential occupational group. TRIAL REGISTRATION: ISRCTN10483894 (date registered: 01/03/2017).

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Usability and acceptability of wearable technology in the early detection of dementia (2022)

Alzheimer's \& Dementia: The Journal of the Alzheimer's Association

Authors: Wilson, Sarah; Ardle, Ríona Mc; Tolley, Clare; Slight, Sarah

Abstract

BACKGROUND: The Early Detection of Neurodegeneration (EDoN) is a global initiative that aims to explore the potential of wearable technologies and smartphone applications to detect preclinical dementia, with aspirations to validate a digital toolkit for clinical practice. To enhance the development of an inclusive digital toolkit, we conducted a study to assess the usability and acceptability of different digital devices in people with cognitive impairments and their carers. METHOD: Recruitment was conducted across various UK networks such as Join Dementia Research. Participants received the EDoN toolkit, which includes a smartwatch (Fitbit Charge 4), EEG headband (Dreem 3) and two smartphone applications (Longevity and Mezurio). Guides were provided to support the setup process. Initial interviews were conducted approximately three days after the participant received the devices, to explore initial perspectives regarding the toolkit and experiences of the setup process. Follow-up interviews were conducted two weeks later to explore the acceptability and usability of the toolkit. NVivo was used to thematically analyse the interview transcripts. Emerging themes were discussed and refined by the research group. RESULT: Sixteen semi-structured interviews were conducted with nine participants, at two-time points. Four participants had mild cognitive impairment, two had frontotemporal dementia, one had Alzheimer's and two were carers. We identified three key themes, which centred around usability, acceptability and inequity. Participants expressed the wearable devices were comfortable but individuals with physical disabilities or cognitive impairments struggled to use some devices. Participants valued the feedback the devices provided such as information on sleep and heart rate, although some information was not fully understood. Participants also shared their concerns around detecting preclinical dementia and the increased anxiety around the consequences of this such as being put in a home". Various inequities of the toolkit were uncovered such as digital exclusion relating to a lack of access to strong WiFi connection

Utility of Fitbit devices among children and adolescents with chronic health conditions: a scoping review (2022)

mHealth

Authors: Kasparian, Alexandra M.; Badawy, Sherif M.

Abstract

Background: While Fitbit® devices were initially intended for leisurely, consumer use, there has been recent interest among scientific and medical communities in the prospective use of Fitbit devices for clinical and research purposes. Those who have chronic health conditions are often required to spend considerable amounts of money and time undergoing physiological tests and activity monitoring to support, stabilize, and manage their health. This disease burden is only amplified in pediatric populations. Devices that are used to collect these data can be invasive, uncomfortable, and disconcerting. Using the Fitbit tracker to acquire such biometric data could ease this burden. Our scoping review seeks to summarize the research that has been conducted on the utilization of Fitbit devices in studies of children and adolescents with chronic health conditions and the feasibility, accuracy, and potential benefits of doing so. Methods: Searches were conducted on PubMed for articles relating pediatric health to Fitbit device usage (using a Boolean search strategy). The eligibility criteria included trials being clinical and/or randomized controlled and articles being in English. Once articles were obtained, they underwent screening and exclusion processes and were charted for their titles, authors, objectives, results, and respective chronic illnesses. In the subsequent full-text review, further charting was conducted, collecting study designs, Fitbit parameters, feasibility, accuracy, and related health and clinical outcomes. Results: Fitbit trackers were unanimously demonstrated to be feasible devices in this population for physical activity monitoring and were determined to be potentially beneficial in measuring and improving overall wellbeing and physical health in children with chronic illness. Nevertheless, sufficient evidence was not found in support of Fitbit accuracy. Additional biases were identified against the population of children with chronic health conditions that may further enable inaccurate data. Conclusions: While Fitbit devices may be beneficial for those interested in improving physical health, discretion is advised for those seeking to collect accurate and/or medically necessitated data. Given the existing literature evaluated, medical-grade technologies are preferred in instances of the latter, as Fitbit devices have not been found to provide reliably accurate data.

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Wrist-worn devices for the measurement of heart rate and energy expenditure: A validation study for the Apple Watch 6, Polar Vantage V and Fitbit Sense (2022)

European journal of sport science

Authors: Hajj-Boutros, Guy; Landry-Duval, Marie Anne; Comtois, Alain Steve; Gouspillou, Gilles; Karelis, Antony D.

Abstract

The purpose of this study was to investigate the accuracy of 3 recently released wrist-worn devices (Apple Watch 6, Polar Vantage V and Fitbit Sense) for heart rate and energy expenditure during various activities. The study population consisted of 60 young healthy individuals (30 men and 30 women; age: 24.9 ± 3.0 years, BMI: 23.1 ± 2.7 kg/m2). Heart rate and energy expenditure were measured using the Polar H10 and Metamax 3B, respectively (reference measures) as well as with the 3 wrist-worn devices during 5 different activities (sitting, walking, running, resistance exercises and cycling). The Apple Watch 6 displayed the highest level of accuracy for heart rate measurement with a coefficient of variation (CV) (%) of less than 5% for all 5 activities, whereas the Polar Vantage V and the Fitbit Sense presented various degrees of accuracy (from high to poor accuracy) dependent on the activity (CVs between 2.44-8.80% and 4.14-10.76%, respectively). As for energy expenditure, all 3 devices displayed poor accuracy for all 5 physical activities (CVs between 14.68-24.85% for Apple Watch 6, 16.54-25.78% for Polar Vantage V and 13.44-29.66% for Fitbit Sense). Results of the present study indicate that the Apple Watch 6 was the most accurate for measuring heart rate across all 5 activities, whereas variable levels of accuracy for heart rate measurement for the Polar Vantage V and the Fitbit Sense were observed depending on the activity. As for energy expenditure, all 3 devices showed poor accuracy during all activities. Highlights The Apple Watch 6 was the most accurate for measuring heart rate, whereas the Polar Vantage V and Fitbit Sense showed variable results dependent on the activity The Apple Watch 6, Polar Vantage V and Fitbit Sense showed poor accuracy for energy expenditure during 5 different physical activities Healthcare care professionals, athletes/coaches and the general population may want to proceed with caution on the clinical utility of energy expenditure of these devices during the implementation of an exercise training or nutritional programme.

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¡Mi Vida Saludable! A randomized, controlled, 2 × 2 factorial trial of a diet and physical activity intervention among Latina breast cancer survivors: Study design and methods (2021)

Contemporary clinical trials

Authors: Santiago-Torres, Margarita; Contento, Isobel; Koch, Pamela; Tsai, Wei Yann; Brickman, Adam M.; Gaffney, Ann Ogden; Thomson, Cynthia A.; Crane, Tracy E.; Dominguez, Naxielly; Sepulveda, Jhack; Mar{\'{i}}n-Chollom, Amanda M.; Paul, Rachel; Shi, Zaixing; Ulanday, Kathleene T.; Hale, Christiane; Hershman, Dawn; Greenlee, Heather

Abstract

Background: Most Latina breast cancer survivors do not meet diet and physical activity (PA) guidelines for cancer survivors and effective lifestyle interventions to adopt and maintain these recommendations are limited, especially among underserved populations. Here we describe the design, methods and enrollment of a 2 × 2 factorial-designed trial testing the separate effects of the ¡Mi Vida Saludable! (My Healthy Life!) intervention program on changes in diet and PA behaviors among Latina breast cancer survivors. Methods: Latinas with a history of stage 0-III breast cancer, no evidence of recurrent/metastatic disease, and > 90 days post-treatment were primarily identified via cancer registries and physician referral. Participants were randomized to four arms: 1) 4 weeks of in-person group sessions plus 11 months of eHealth communication, 2) in-person group sessions alone, 3) eHealth alone, or 4) control. All participants received a Fitbit to self-monitor PA. Assessments at baseline, 6 and 12 months include diet, PA, anthropometrics, predictors and mediators of behavior change, psychosocial and quality of life outcomes, and blood draw. Results: Of 884 women screened between January 2016 and September 2018, 27% were eligible. Primary reasons for ineligibility included not being willing/able to participate due to work/life responsibilities, health reasons, or transportation. Of 241 eligible women, 167 completed baseline assessment and enrolled. Conclusions: We successfully enrolled a diverse group of breast cancer survivors representing more than 15 Latin American nationalities to a diet and physical activity trial. If effective, the ¡Mi Vida Saludable! program can be implemented by community groups and medical centers. Trial registration: ClinicalTrials.gov, NCT02780271, registered May 2016.

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A Mental Health-Informed Physical Activity Intervention for First Responders and Their Partners Delivered Using Facebook: Mixed Methods Pilot Study (2021)

JMIR formative research

Authors: McKeon, Grace; Steel, Zachary; Wells, Ruth; Newby, Jill; Hadzi-Pavlovic, Dusan; Vancampfort, Davy; Rosenbaum, Simon

Abstract

Background: First responders (eg, police, firefighters, and paramedics) are at high risk of experiencing poor mental health. Physical activity interventions can help reduce symptoms and improve mental health in this group. More research is needed to evaluate accessible, low-cost methods of delivering programs. Social media may be a potential platform for delivering group-based physical activity interventions. Objective: This study aims to examine the feasibility and acceptability of delivering a mental health–informed physical activity program for first responders and their self-nominated support partners. This study also aims to assess the feasibility of applying a novel multiple time series design and to explore the impact of the intervention on mental health symptoms, sleep quality, quality of life, and physical activity levels. Methods: We co-designed a 10-week web-based physical activity program delivered via a private Facebook group. We provided education and motivation around different topics weekly (eg, goal setting, overcoming barriers to exercise, and reducing sedentary behavior) and provided participants with a Fitbit. A multiple time series design was applied to assess psychological distress levels, with participants acting as their own control before the intervention. Results: In total, 24 participants (12 first responders and 12 nominated support partners) were recruited, and 21 (88%) completed the postassessment questionnaires. High acceptability was observed in the qualitative interviews. Exploratory analyses revealed significant reductions in psychological distress during the intervention. Preintervention and postintervention analysis showed significant improvements in quality of life (P=.001; Cohen d=0.60); total depression, anxiety, and stress scores (P=.047; Cohen d=0.35); and minutes of walking (P=.04; Cohen d=0.55). Changes in perceived social support from family (P=.07; Cohen d=0.37), friends (P=.10; Cohen d=0.38), and sleep quality (P=.28; Cohen d=0.19) were not significant. Conclusions: The results provide preliminary support for the use of social media and a multiple time series design to deliver mental health–informed physical activity interventions for first responders and their support partners. Therefore, an adequately powered trial is required.

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A 'novel' multi-component approach to promote physical activity among older cancer survivors: a pilot randomized controlled trial (2021)

Acta oncologica (Stockholm, Sweden)

Authors: Pinto, Bernardine M.; Kindred, Madison; Franco, Regina; Simmons, Virginia; Hardin, James

Abstract

Background: Physical activity (PA) provides many benefits for recovery from cancer treatments. Many older (65+ years) cancer survivors which comprise the majority of the cancer survivor population, do not meet recommended PA guidelines. This study explored the feasibility and acceptability of using audiobooks as part of a 12-week multi-component intervention to increase steps/day, light and moderate-to-vigorous intensity PA among older survivors. Methods: Twenty older cancer survivors (95% female, mean age = 71.55 years, 90% White, 85% overweight/obese, 75% breast cancer survivors, mean 1.96 years since treatment completion) were randomized into one of the two study groups (Audiobook Group, n = 12, Comparison Group, n = 8). Both study groups were provided a tailored step goal program over the 12-week intervention; weekly step increases were based on a percent increase from baseline. Participant self-monitored their steps using a Fitbit Charge 2. In addition, the Audiobook group were encouraged to listen to audiobooks (downloaded onto a smartphone device via an app available at no cost from the local library) during PA to add enjoyment and increase PA. Regression analyses on steps/day, light and moderate-to-vigorous PA/week and sedentary time/week as assessed by the Actigraph were conducted, after adjusting for Actigraph wear time. Data from the post-intervention questionnaire were summarized. Results: Overall, majority of participants (89%) stated they were very satisfied with their participation and 100% reported that they were able to maintain their activity upon study completion. Retention rates were high. At post-intervention, there were significant differences favoring the Audiobook group for steps/day and moderate-to-vigorous PA/week. No significant group differences were found for minutes of light intensity PA/week and sedentary time/week. Conclusion: Piloting the implementation of a sustainable, innovative intervention among older survivors to increase their PA has significance for this group of survivors.

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A qualitative study on participants' experiences with a community-based mindful walking intervention and mobile device activity measurement (2021)

Complementary therapies in medicine

Authors: Jones, Karyn O.; Lopes, Snehal S.; Kelly, Claire; Welsh, Ralph S.; Chen, Liwei; Wilson, Mark; Jindal, Meenu; Zinzow, Heidi; Zhang, Lingling; Shi, Lu

Abstract

Background: Mindful walking (MW) interventions employ mindfulness training combined with physical activity. Wearable mobile devices have been increasingly used to measure outcomes of physical activity interventions. The purpose of this study was to understand MW participants' attitudes towards MW and the use of mobile devices in health promotion interventions, including barriers and facilitators of intervention engagement and adherence. Few qualitative studies have documented participant experience with these two types of interventions. Method: The pilot study involved a randomized MW intervention including 38 participants with self-reported inadequate physical activity. Half of them were randomized to receive MW intervention plus a FitBit device and the other received the FitBit device only. We used a qualitative thematic analysis of the narrative data collected through open-ended survey questions at three time points. Participants in the MW intervention were asked to describe their experiences with MW, while all participants were asked to describe their experience with wearing the FitBit to track their step counts. Results: Participants reported a broad range of perceived benefits and challenges related to adopting the MW intervention and using the mobile device. Participants were generally willing to try to adopt the recommended MW practice and to see value of MW in increasing physical activity and improving overall health. Participants reported using a variety of additional device features beyond goal setting and step counts, indicating using the devices may have been effective in providing additional motivation for participants in meeting physical activity goals in both the control and intervention groups. While most of the feedback about MW (in the intervention group) and the device (all participants) was overwhelmingly positive, a minority of participants reported barriers such as lack of patience with meditation and discomfort with wearing the device. Conclusion: Most participants in the MW intervention see the health benefits of this program and most participants using the wearable physical activity tracking device reported the motivational benefits of this device. Issues with the MW intervention (e.g., lack of patience) and the wearable device (e.g., discomfort with wearing) need to be addressed in future interventions.

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A systematic review of the validity, reliability, and feasibility of measurement tools used to assess the physical activity and sedentary behaviour of pre-school aged children (2021)

The international journal of behavioral nutrition and physical activity

Authors: Phillips, Sophie M.; Summerbell, Carolyn; Hobbs, Matthew; Hesketh, Kathryn R.; Saxena, Sonia; Muir, Cassey; Hillier-Brown, Frances C.

Abstract

Physical activity (PA) and sedentary behaviour (SB) of pre-school aged children are associated with important health and developmental outcomes. Accurate measurement of these behaviours in young children is critical for research and practice in this area. The aim of this review was to examine the validity, reliability, and feasibility of measurement tools used to assess PA and SB of pre-school aged children. Searches of electronic databases, and manual searching, were conducted to identify articles that examined the measurement properties (validity, reliability or feasibility) of measurement tools used to examine PA and/or SB of pre-school aged children (3–7 years old). Following screening, data were extracted and risk of bias assessment completed on all included articles. A total of 69 articles, describing 75 individual studies were included. Studies assessed measurement tools for PA (n = 27), SB (n = 5), and both PA and SB (n = 43). Outcome measures of PA and SB differed between studies (e.g. moderate to vigorous activity, step count, posture allocation). Most studies examined the measurement properties of one measurement tool only (n = 65). Measurement tools examined included: calorimetry, direct observation, combined heart rate and accelerometry, heart rate monitors, accelerometers, pedometers, and proxy report (parent, carer or teacher reported) measures (questionnaires or diaries). Studies most frequently assessed the validity (criterion and convergent) (n = 65), face and content validity (n = 2), test-retest reliability (n = 10) and intra-instrument reliability (n = 1) of the measurement tools. Feasibility data was abstracted from 41 studies. Multiple measurement tools used to measure PA and SB in pre-school aged children showed some degree of validity, reliability and feasibility, but often for different purposes. Accelerometers, including the Actigraph (in particular GT3X versions), Actical, ActivPAL and Fitbit (Flex and Zip), and proxy reported measurement tools used in combination may be useful for a range of outcome measures, to measure intensity alongside contextual information.

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A Technology-Based Physical Activity Intervention for Patients With Metastatic Breast Cancer (Fit2ThriveMB): Protocol for a Randomized Controlled Trial (2021)

JMIR research protocols

Authors: Phillips, Siobhan; Solk, Payton; Welch, Whitney; Auster-Gussman, Lisa; Lu, Marilyn; Cullather, Erin; Torre, Emily; Whitaker, Madelyn; Izenman, Emily; La, Jennifer; Lee, Jungwha; Spring, Bonnie; Gradishar, William

Abstract

Background: Increased incidence and life expectancy have resulted in a growing population of patients with metastatic breast cancer, and these patients experience high rates of morbidity and premature mortality. Increased physical activity (PA) is consistently associated with improved health and disease outcomes among early-stage survivors. However, there is a paucity of research on PA in patients with metastatic breast cancer, and existing PA interventions have exhibited low feasibility because of their focus on intense PA and/or requirement of on-site visits. Mobile health (mHealth)–based PA interventions may be particularly useful for patients with metastatic breast cancer because they allow for remote monitoring, which facilitates individual tailoring of PA recommendations to patients' abilities and may minimize participant burden. However, no studies have examined mHealth PA interventions in patients with metastatic breast cancer. Objective: We aim to address these critical research gaps by testing a highly tailored technology-based intervention to promote PA of any intensity (ie, light, moderate, or vigorous) by increasing daily steps in patients with metastatic breast cancer. The primary aim of this study is to test the feasibility and acceptability of the Fit2ThriveMB intervention. We will also examine outcome patterns suggesting the efficacy of Fit2ThriveMB on symptom burden, quality of life, and functional performance. Methods: The Fit2ThriveMB trial is a two-arm pilot randomized controlled trial that will compare the effects of a smartphone-delivered, home-based PA intervention and an attention-control education condition on PA and quality of life in low-active female patients with metastatic breast cancer. A subsample (n=25) will also complete functional performance measures. This innovative trial will recruit 50 participants who will be randomized into the study's intervention or control arm. The intervention will last 12 weeks. The Fit2ThriveMB intervention consists of a Fitbit, coaching calls, and the Fit2ThriveMB smartphone app that provides self-monitoring, a tailored goal-setting tool, real-time tailored feedback, app notifications, and a group message board. Assessments will occur at baseline and post intervention. Results: The Fit2ThriveMB study is ongoing. Data collection ended in February 2021. Conclusions: Data from this study will provide the preliminary effect sizes needed to assemble an intervention that is to be evaluated in a fully powered trial. In addition, these data will provide essential evidence to support the feasibility and acceptability of using a technology-based PA promotion intervention, a scalable strategy that could be easily integrated into care, among patients with metastatic breast cancer.

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Acceptability of a Mobile Health Behavior Change Intervention for Cancer Survivors With Obesity or Overweight: Nested Mixed Methods Study Within a Randomized Controlled Trial (2021)

JMIR mHealth and uHealth

Authors: Groarke, Jenny M.; Richmond, Janice; Mc Sharry, Jenny; Groarke, Ann Marie; Harney, Owen M.; Kelly, Mary Grace; Walsh, Jane C.

Abstract

Background: A significant proportion of cancer survivors have overweight or obesity. Although this has negative implications for health, weight management is not a standard component of oncology aftercare. Mobile health (mHealth) technology, in combination with behavior change techniques (BCTs), has the potential to support positive lifestyle changes. Few studies have been carried out with cancer survivors; therefore, the acceptability of these tools and techniques requires further investigation. Objective: The aim of this study is to examine the acceptability of a behavior change intervention using mHealth for cancer survivors with a BMI of 25 or more and to gather constructive feedback from participants. Methods: The intervention consisted of educational sessions and an 8-week physical activity goal setting intervention delivered using mobile technology (ie, Fitbit activity monitor plus SMS contact). In the context of a two-arm randomized controlled trial, semistructured interviews were conducted to assess the retrospective acceptability of the intervention from the perspective of the recipients. The theoretical framework for the acceptability of health care interventions was used to inform a topic guide. The interviews were transcribed and analyzed using thematic analysis. A quantitative survey was also conducted to determine the acceptability of the intervention. A total of 13 participants were interviewed, and 36 participants completed the quantitative survey. Results: The results strongly support the acceptability of the intervention. The majority of the survey respondents held a positive attitude toward the intervention (35/36, 97%). In qualitative reports, many of the intervention components were enjoyed and the mHealth components (ie, Fitbit and goal setting through text message contact) were rated especially positively. Responses were mixed as to whether the burden of participating in the intervention was high (6/36, 17%) or low (5/36, 14%). Participants perceived the intervention as having high efficacy in improving health and well-being (34/36, 94%). Most respondents said that they understood how the intervention works (35/36, 97%), and qualitative data show that participants' understanding of the aim of the intervention was broader than weight management and focused more on moving on psychologically from cancer. Conclusions: On the basis of the coherence of responses with theorized aspects of intervention acceptability, we are confident that this intervention using mHealth and BCTs is acceptable to cancer survivors with obesity or overweight. Participants made several recommendations concerning the additional provision of social support. Future studies are needed to assess the feasibility of delivery in clinical practice and the acceptability of the intervention to those delivering the intervention.

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Annual rhythms in adults' lifestyle and health (ARIA): protocol for a 12-month longitudinal study examining temporal patterns in weight, activity, diet, and wellbeing in Australian adults (2021)

BMC Public Health

Authors: Curtis, Rachel G.; Olds, Timothy; Fraysse, Fran{\c{c}}ois; Dumuid, Dorothea; Hendrie, Gilly A.; Esterman, Adrian; Brown, Wendy J.; Ferguson, Ty; Lagiseti, Rajini; Maher, Carol A.

Abstract

Background: Almost one in three Australian adults are now obese, and the rate continues to rise. The causes of obesity are multifaceted and include environmental, cultural and lifestyle factors. Emerging evidence suggests there may be temporal patterns in weight gain related, for example, to season and major festivals such as Christmas, potentially due to changes in diet, daily activity patterns or both. The aim of this study is to track the annual rhythm in body weight, 24 h activity patterns, dietary patterns, and wellbeing in a cohort of Australian adults. In addition, through data linkage with a concurrent children's cohort study, we aim to examine whether changes in children's body mass index, activity and diet are related to those of their parents. Methods: A community-based sample of 375 parents aged 18 to 65 years old, residing in or near Adelaide, Australia, and who have access to a Bluetooth-enabled mobile device or a computer and home internet, will be recruited. Across a full year, daily activities (minutes of moderate to vigorous physical activity, light physical activity, sedentary behaviour and sleep) will be measured using wrist-worn accelerometry (Fitbit Charge 3). Body weight will be measured daily using Fitbit wifi scales. Self-reported dietary intake (Dietary Questionnaire for Epidemiological Studies V3.2), and psychological wellbeing (WHOQOL-BREF and DASS-21) will be assessed eight times throughout the 12-month period. Annual patterns in weight will be examined using Lowess curves. Associations between changes in weight and changes in activity and diet compositions will be examined using repeated measures multi-level models. The associations between parent's and children's weight, activity and diet will be investigated using multi-level models. Discussion: Temporal factors, such as day type (weekday or weekend day), cultural celebrations and season, may play a key role in weight gain. The aim is to identify critical opportunities for intervention to assist the prevention of weight gain. Family-based interventions may be an important intervention strategy. Trial registration: Australia New Zealand Clinical Trials Registry, identifier ACTRN12619001430123. Prospectively registered on 16 October 2019.

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Applying Mobile Technology to Sustain Physical Activity After Completion of Cardiac Rehabilitation: Acceptability Study (2021)

JMIR human factors

Authors: Elnaggar, A.; von Oppenfeld, J.; Whooley, M. A.; Merek, S.; Park, L. G.

Abstract

Background: Many patients do not meet the recommended levels of physical activity after completing a cardiac rehabilitation (CR) program. Wearable activity trackers and mobile phone apps are promising potential self-management tools for maintaining physical activity after CR completion. Objective: This study aims to evaluate the acceptability of a wearable device, mobile app, and push messages to facilitate physical activity following CR completion. Methods: We used semistructured interviews to assess the acceptability of various mobile technologies after participation in a pilot randomized controlled trial. Intervention patients in the randomized controlled trial wore the Fitbit Charge 2, used the Movn mobile app, and received push messages on cardiovascular disease prevention and physical activity for over 2 months. We asked 26 intervention group participants for feedback about their experience with the technology and conducted semistructured individual interviews with 7 representative participants. We used thematic analysis to create the main themes from individual interviews. Results: Our sample included participants with a mean age of 66.7 (SD 8.6) years; 23% (6/26) were female. Overall, there were varying levels of satisfaction with different technology components. There were 7 participants who completed the satisfaction questionnaires and participated in the interviews. The Fitbit and Movn mobile app received high satisfaction scores of 4.86 and 4.5, respectively, whereas push messages had a score of 3.14 out of 5. We identified four main themes through the interviews: technology use increased motivation to be physically active, technology use served as a reminder to be physically active, recommendations for technology to improve user experience, and desire for personal feedback. Conclusions: By applying a wearable activity tracker, mobile phone app, and push messages, our study showed strong potential for the adoption of new technologies by older adults to maintain physical activity after CR completion. Future research should include a larger sample over a longer period using a mixed methods approach to assess the efficacy of technology use for promoting long-term physical activity behavior in older adults.

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BAILAMOS With mHealth Technology! Improving Physical Activity and Well-Being in Middle-Aged and Older Latinxs: A Pre-Post Feasibility Study (2021)

Health education & behavior : the official publication of the Society for Public Health Education

Authors: Aguinaga, Susan; Marques, Isabela G.; Kitsiou, Spyros; Balbim, Guilherme M.; Gerber, Ben S.; Buchholz, Susan W.; Bustamante, Eduardo E.; Marquez, David X.

Abstract

Older Latinxs engage in lower levels of leisure-time physical activity (PA) compared with non-Latinx Whites. Latin dance is a culturally relevant type of leisure-time PA that may engage older Latinx populations, particularly when coupled with mobile health technologies (mHealth). This single group pre–post feasibility study described the PA and health outcomes of middle-aged and older Latinxs participating in BAILA TECH—an intervention that combines the BAILAMOS Latin dance program with mHealth (Fitbit Charge 2, Fitbit app, and motivational text messages). Participants (n = 20, Mage = 67 ± 7.1, female n = 15, 75%) were enrolled in the 16-week BAILA TECH intervention held twice a week. Participants received a Fitbit Charge 2 to assess PA at baseline, during the intervention, and postintervention. An mHealth platform (iCardia) collected Fitbit data and staff delivered weekly motivational and informational text messages. Participants completed questionnaires about PA, sedentary behavior, cardiorespiratory fitness, social support, quality of life, and cognitive function at baseline and postintervention. Paired t tests evaluated change in pre–post measures. There was a significant increase in device-assessed moderate-to-vigorous PA (d = 0.69), self-reported light-leisure (d = 1.91) and moderate-to-vigorous PA (d = 1.05), moderate-to-vigorous leisure PA (d = 1.55), predicted cardiorespiratory fitness (d = 1.10), and PA social support (d = 0.81 [family]; d = 0.95 [friends]) from baseline to postintervention. Although nonsignificant, there was a small effect on physical health–related quality of life (d = 0.32) and executive function (d = 0.29). These data describe an increase in PA levels and health-related outcomes of middle-aged and older Latinxs from participation in an mHealth-infused Latin dance intervention. An adequately powered trial is necessary to establish efficacy.

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Connecting breast cancer survivors for exercise: protocol for a two-arm randomized controlled trial (2021)

BMC sports science, medicine & rehabilitation

Authors: Smith-Turchyn, Jenna; McCowan, Michelle E.; O'Loughlin, Erin; Fong, Angela J.; McDonough, Meghan H.; Santa Mina, Daniel; Arbour-Nicitopoulos, Kelly P.; Trinh, Linda; Jones, Jennifer M.; Bender, Jackie L.; Culos-Reed, S. Nicole; Tomasone, Jennifer R.; Vani, Madison F.; Sabiston, Catherine M.

Abstract

Background: Peer-based exercise interventions that cultivate new opportunities for support with a fellow cancer survivor may result in increased exercise volume. It is not clear whether adding qualified exercise professional (QEP) support to peer-based interventions improves health outcomes. Therefore, the purpose of this study is to determine whether breast cancer survivor (BCS) dyads who receive 10 weekly sessions of virtually delivered QEP support have improved outcomes compared to BCS dyads who do not receive QEP support. Methods: Participants Adult BCS with medical clearance for exercise, who have an internet-connected device, and currently engage in < 150 min of moderate-intensity exercise per week. Intervention BCS will be matched using evidence-based criteria. The intervention group will receive dyadic exercise information sessions and a program tailored by a QEP for 10 weeks (intervention period) and have access to the QEP for an additional 4 weeks (tapering period). The control will not receive any QEP support. Outcomes The primary outcome is post-intervention self-reported exercise volume. Secondary outcomes include device-assessed exercise volume (i.e., Fitbit), social support, and health-related quality of life. Randomization 108 participants, matched in dyads, will be randomized 1:1 to the MatchQEP or Match groups using a web-based scheme. Statistical analysis Outcomes will be measured at baseline, post-intervention, post-tapering, and at 12 weeks post-intervention follow-up. Discussion: The findings from this RCT will determine if matched BCS dyads who receive 10 weeks of virtually delivered QEP support have higher levels of self-report and device-measured exercise, social support, and health related quality of life compared to matched dyads without QEP-delivered exercise guidance. To our knowledge this will be the first study to assess the combined effect of peer- and QEP support on exercise volume. Project findings will inform and optimize intervention methods aimed to increase exercise among BCS through accessible exercise supports. Trial Registration: The study is registered on ClinicalTrials.gov (study identifier: NCT04771975, protocol Version Number: 2, date: July 22, 2021).

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Consumer-Based Activity Trackers as a Tool for Physical Activity Monitoring in Epidemiological Studies During the COVID-19 Pandemic: Development and Usability Study (2021)

JMIR public health and surveillance

Authors: Henriksen, A.; Johannessen, E.; Hartvigsen, G.; Grimsgaard, S.; Hopstock, L. A.

Abstract

Background: Consumer-based physical activity trackers have increased in popularity. The widespread use of these devices and the long-term nature of the recorded data provides a valuable source of physical activity data for epidemiological research. The challenges include the large heterogeneity between activity tracker models in terms of available data types, the accuracy of recorded data, and how this data can be shared between different providers and third-party systems. Objective: The aim of this study is to develop a system to record data on physical activity from different providers of consumer-based activity trackers and to examine its usability as a tool for physical activity monitoring in epidemiological research. The longitudinal nature of the data and the concurrent pandemic outbreak allowed us to show how the system can be used for surveillance of physical activity levels before, during, and after a COVID-19 lockdown. Methods: We developed a system (mSpider) for automatic recording of data on physical activity from participants wearing activity trackers from Apple, Fitbit, Garmin, Oura, Polar, Samsung, and Withings, as well as trackers storing data in Google Fit and Apple Health. To test the system throughout development, we recruited 35 volunteers to wear a provided activity tracker from early 2019 and onward. In addition, we recruited 113 participants with privately owned activity trackers worn before, during, and after the COVID-19 lockdown in Norway. We examined monthly changes in the number of steps, minutes of moderate-to-vigorous physical activity, and activity energy expenditure between 2019 and 2020 using bar plots and two-sided paired sample t tests and Wilcoxon signed-rank tests. Results: Compared to March 2019, there was a significant reduction in mean step count and mean activity energy expenditure during the March 2020 lockdown period. The reduction in steps and activity energy expenditure was temporary, and the following monthly comparisons showed no significant change between 2019 and 2020. A small significant increase in moderate-to-vigorous physical activity was observed for several monthly comparisons after the lockdown period and when comparing March-December 2019 with March-December 2020. Conclusions: mSpider is a working prototype currently able to record physical activity data from providers of consumer-based activity trackers. The system was successfully used to examine changes in physical activity levels during the COVID-19 period.

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Co-occurrence of pain and dyspnea in Veterans with COPD: Relationship to functional status and a pilot study of neural correlates using structural and functional magnetic resonance imaging (2021)

PLOS ONE

Authors: Moy, Marilyn L.; Daniel, Rinu A.; Rivera, Paola N. Cruz; Mongiardo, Maria A.; Goldstein, Rebekah L.; Higgins, Diana M.; Salat, David H.

Abstract

Persons with COPD experience co-occurring dyspnea and pain. Little is known about the relationship between symptom co-occurrence with physical activity (PA) and exercise. Novel diagnostic tools are needed for accurate symptom discrimination. In this secondary analysis, we examined relationships between baseline assessments of pain, dyspnea, objectively measured PA, and exercise capacity in persons with COPD who previously enrolled in three PA studies. Pain was assessed with the bodily pain domain of the Veterans RAND-36 (VR-36), and dyspnea with the modified Medical Research Council (mMRC) scale. Average daily step count was assessed with the Omron HJ-720ITC or FitBit Zip pedometer, and exercise capacity with 6-minute walk test (6MWT). We also conducted a pilot neuroimaging study. Neuroimaging data were acquired on a Siemens 3-Tesla Magnetom Prismafit whole-body scanner. Analysis of variance assessed trends in daily step count and 6MWT distance across categories of co-occurring pain and dyspnea. General linear models examined relationships between cortical thickness and resting state functional connectivity (fc) with symptoms and functional status. In 373 Veterans, 98% were male with mean age 70.5± 8.3 years and FEV1% predicted 59 ± 21%. Compared to those with no co-occurrence of pain and dyspnea, those with co-occurrence walked 1,291–1,444 fewer steps per day and had an 80–85 m lower 6MWT distance. Ten males participated in the pilot neuroimaging study. Predominant findings were that lower cortical thickness and greater fc were associated with higher pain and dyspnea, p<0.05. Greater cortical thickness and lower fc were associated with higher daily step count and 6MWT distance, p<0.05. Regional patterns of associations differed for pain and dyspnea, suggesting that cortical thickness and fc may discriminate symptoms. Co-occurring dyspnea and pain in COPD are associated with significant reductions in PA and exercise capacity. It may be feasible for neuroimaging markers to discriminate between pain and dyspnea.

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Dynamics of sleep, sedentary behavior, and moderate-to-vigorous physical activity on school versus nonschool days (2021)

Sleep

Authors: Armstrong, Bridget; Beets, Michael W.; Starrett, Angela; Brazendale, Keith; Turner-McGrievy, Gabrielle; Saelens, Brian E.; Pate, Russell R.; Youngstedt, Shawn D.; Maydeu-Olivares, Alberto; Weaver, R. Glenn

Abstract

STUDY OBJECTIVES: Studies examining time-use activity behaviors (sleep, sedentary behavior, and physical activity) on school days compared with nonschool days have examined these behaviors independently, ignoring their interrelated nature, limiting our ability to optimize the health benefits of these behaviors. This study examines the associations of school-day (vs. nonschool day) with time-use activity behaviors. METHODS: Time series data (6,642 days) from Fitbits (Charge-2) were collected (n = 196, 53% female, 5-10 years). We used a variable-centered dynamic structural equation modeling approach to estimate day-to-day associations of time-use activity behaviors on school days for each child. We then used person-centered cluster analyses to group individuals based on these estimates. RESULTS: Within-participant analysis showed that on school days (vs. nonschool days), children (1) slept less (β = -0.17, 95% CI = -0.21, -0.13), (2) were less sedentary (β = -0.05, 95% CI = -0.09, -0.02), and (3) had comparable moderate-to-vigorous physical activity (MVPA; β = -0.05, 95% CI = -0.11, 0.00). Between-participant analysis showed that, on school days, children with higher sleep carryover experienced greater decreases in sleep (β = 0.44, 95% CI = 0.08, 0.71), children with higher body mass index z-score decreased sedentary behavior more (β = -0.41, 95% CI = -0.64, -0.13), and children with lower MVPA increased MVPA more (β = -0.41, 95% CI -0.64, -0.13). Cluster analysis demonstrated four distinct patterns of connections between time-use activity behaviors and school (High Activity, Sleep Resilient, High Sedentary, and Dysregulated Sleep). CONCLUSIONS: Using a combination of person-centered and more traditional variable-centered approaches, we identified patterns of interrelated behaviors that differed on school, and nonschool days. Findings can inform targeted intervention strategies tailored to children's specific behavior patterns.

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Effect of commercial wearables and digital behaviour change resources on the physical activity of adolescents attending schools in socio-economically disadvantaged areas: the RAW-PA cluster-randomised controlled trial (2021)

The international journal of behavioral nutrition and physical activity

Authors: Ridgers, Nicola D.; Timperio, Anna; Ball, Kylie; Lai, Samuel K.; Brown, Helen; Macfarlane, Susie; Salmon, Jo

Abstract

Background: There has been increasing interest in using wearable activity trackers to promote physical activity in youth. This study examined the short- and longer-term effects of a wearable activity tracker combined with digital behaviour change resources on the physical activity of adolescents attending schools in socio-economically disadvantaged areas. Methods: The Raising Awareness of Physical Activity (RAW-PA) Study was a 12-week, multicomponent intervention that combined a Fitbit Flex (and accompanying app), and online digital behaviour change resources and weekly challenges delivered via Facebook. RAW-PA was evaluated using a cluster-randomised controlled trial with 275 adolescents (50.2% female; 13.7 ± 0.4 years) from 18 Melbourne secondary schools (intervention n = 9; wait-list control group n = 9). The primary outcome was moderate- to vigorous-intensity physical activity (MVPA), measured using hip-worn ActiGraph accelerometers. The secondary outcome was self-reported physical activity. Data were collected at baseline, 12-weeks (immediately post-intervention), and 6-months post-intervention (follow-up). Multilevel models were used to determine the effects of the intervention on daily MVPA over time, adjusting for covariates. Results: No significant differences were observed between intervention and wait-list control adolescents' device-assessed MVPA immediately post-intervention. At 6-months post-intervention, adolescents in the intervention group engaged in 5 min (95% CI: − 9.1 to − 1.0) less MVPA per day than those in the wait-list control group. Males in the intervention group engaged in 11 min (95% CI: − 17.6 to − 4.5) less MVPA than males in the wait-list control group at 6-months post-intervention. No significant differences were observed for females at either time point. For self-reported physical activity, no significant effects were found at 12-weeks and 6-months post-intervention. Conclusions: Combining a wearable activity tracker with digital behaviour change resources and weekly challenges did not increase inactive adolescents' accelerometer-derived and self-reported physical activity levels immediately post-intervention. This contrasts previous research that has suggested wearable activity tracker may increase youth physical activity levels in the short-term. Lower engagement in MVPA 6-months post-intervention was observed for males but not for females, though it is unclear why this finding was observed. The results suggest wearable activity trackers, in combination with supporting materials, may not be effective for increasing physical activity levels in adolescents. Trial registration: ACTRN12616000899448. Australian and New Zealand Clinical Trials Registry. Registered 7 July 2016.

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Effectiveness of Distance Technology in Promoting Physical Activity in Cardiovascular Disease Rehabilitation: Cluster Randomized Controlled Trial, A Pilot Study (2021)

JMIR rehabilitation and assistive technologies

Authors: Hakala, Sanna; Kivisto; Heikki; Paajanen; Teemu; Kankainen; Annaliisa; Anttila; Marjo Riitta; Heinonen; Ari; Sjogren; Tuulikki

Abstract

Background: Physical activity is beneficial for cardiovascular rehabilitation. Digitalization suggests using technology in the promotion of physical activity and lifestyle changes. The effectiveness of distance technology interventions has previously been found to be similar to that of conventional treatment, but the added value of the technology has not been frequently studied. Objective: The aim of this pilot study was to investigate whether additional distance technology intervention is more effective in promoting physical activity than non-technology-based treatment in 12 months of cardiac rehabilitation. Methods: The cardiovascular disease rehabilitation intervention consisted of three 5-day inpatient periods in a rehabilitation center and two 6-month self-exercise periods at home in between. Participants were recruited from among cardiac patients who attended the rehabilitation program and were cluster-randomized into unblinded groups: conventional rehabilitation control clusters (n=3) and similar rehabilitation with additional distance technology experimental group clusters (n=3). Experimental groups used Fitbit Charge HR for self-monitoring, and they set goals and reported their activity using Movendos mCoach, through which they received monthly automated and in-person feedback. Physical activity outcomes for all participants were measured using the Fitbit Zip accelerometer and the International Physical Activity Questionnaire. Results: During the first 6 months, the experimental group (n=29) engaged in light physical activity more often than the control group (n=30; mean difference [MD] 324.2 minutes per week, 95% CI 77.4 to 571.0; P=.01). There were no group differences in the duration of moderate to vigorous physical activity (MD 12.6 minutes per week, 95% CI -90.5 to 115.7; P=.82) or steps per day (MD 1084.0, 95% CI -585.0 to 2752.9; P=.20). During the following 6 months, no differences between the groups were observed in light physical activity (MD -87.9 minutes per week, 95% CI -379.2 to 203.3; P=.54), moderate to vigorous physical activity (MD 70.9 minutes per week, 95% CI -75.7 to 217.6; P=.33), or steps per day (MD 867.1, 95% CI -2099.6 to 3833.9; P=.55). Conclusions: The use of additional distance technology increased the duration of light physical activity at the beginning of cardiac rehabilitation (for the first 6 months), but statistically significant differences were not observed between the two groups for moderate or vigorous physical activity or steps per day for both 6-month self-exercise periods.

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Exploring the Use of Fitbit Consumer Activity Trackers to Support Active Lifestyles in Adults with Type 2 Diabetes: A Mixed-Methods Study (2021)

International journal of environmental research and public health

Authors: Hodgson, William; Kirk, Alison; Lennon, Marilyn; Paxton, Gregor

Abstract

Background: People with type 2 diabetes are less active than those without the condition. Physical activity promotion within diabetes health care is limited. This project explored the use of Fitbit activity trackers (Fitbit, San Francisco, CA, USA) to support active lifestyles in adults with type 2 diabetes through a mixed-methods study. Methods: Two stages were conducted. In stage 1, adults with type 2 diabetes used a Fitbit Charge 4 (Fitbit, San Francisco, CA, USA) for 4 weeks. Fitbit and self-reported physical activity data was examined through quantitative analysis. Qualitative analysis was conducted to explore the experiences of participants. In stage 2, health professionals were interviewed to examine their views on using Fitbit activity trackers within type 2 diabetes care. Results: Adults with type 2 diabetes were recruited for stage 1 and adult health care and fitness professionals were recruited for stage 2. Stage 1 participants' self-reported increases in physical activity (mean weekly minutes of walking increased from 358.75 to 507.50 min, p = 0.046) and a decrease in sedentary behaviour (mean daily hours of sedentary behaviour decreased from 10.65 to 10.05 h, p = 0.575). Fitbit activity data ranges identified individuals who led inactive and sedentary lifestyles below levels recommended and in need of physical activity support to reduce the risk to their health. During interviews, participants stated that the Fitbit activity tracker motivated them to be more active. Stage 2 participants intimated that Fitbit activity trackers could improve the promotion of physical activity within type 2 diabetes care. Interventions involving the Fitbit premium service, community prescription and combined use of Fitbits with physical activity behaviour change models were recommended by stage 2 participants. Conclusion: This study found that there is future scope for using Fitbit activity trackers to support active lifestyles in adults diagnosed with type 2 diabetes.

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Feasibility and acceptability of a technology-based, rural weight management intervention in older adults with obesity (2021)

BMC Geriatrics

Authors: Batsis, John A.; Petersen, Curtis L.; Clark, Matthew M.; Cook, Summer B.; Kotz, David; Gooding, Tyler L.; Roderka, Meredith N.; Al-Nimr, Rima I.; Pidgeon, Dawna; Haedrich, Ann; Wright, K. C.; Aquila, Christina; Mackenzie, Todd A.

Abstract

Background: Older adults with obesity residing in rural areas have reduced access to weight management programs. We determined the feasibility, acceptability and preliminary outcomes of an integrated technology-based health promotion intervention in rural-living, older adults using remote monitoring and synchronous video-based technology. Methods: A 6-month, non-randomized, non-blinded, single-arm study was conducted from October 2018 to May 2020 at a community-based aging center of adults aged ≥65 years with a body mass index (BMI) ≥30 kg/m2. Weekly dietitian visits focusing on behavior therapy and caloric restriction and twice-weekly physical therapist-led group strength, flexibility and balance training classes were delivered using video-conferencing to participants in their homes. Participants used a Fitbit Alta HR for remote monitoring with data feedback provided by the interventionists. An aerobic activity prescription was provided and monitored. Results: Mean age was 72.9±3.9 years (82{\%} female). Baseline anthropometric measures of weight, BMI, and waist circumference were 97.8±16.3 kg, 36.5±5.2 kg/m2, and 115.5±13.0 cm, respectively. A total of 142 participants were screened (n=27 ineligible), and 53 consented. There were nine dropouts (17{\%}). Overall satisfaction with the trial (4.7+ 0.6, scale: 1 (low) to 5 (high)) and with Fitbit (4.2+ 0.9) were high. Fitbit was worn an average of 81.7±19.3{\%} of intervention days. In completers, mean weight loss was 4.6±3.5 kg or 4.7±3.5{\%} (p{\textless} 0.001). Physical function measures of 30-s sit-to-stand repetitions increased from 13.5±5.7 to 16.7±5.9 (p{\textless} 0.001), 6-min walk improved by 42.0±77.3 m (p=0.005) but no differences were observed in gait speed or grip strength. Subjective measures of late-life function improved (3.4±4.7 points, p{\textless} 0.001). Conclusions: A technology-based obesity intervention is feasible and acceptable to older adults with obesity and may lead to weight loss and improved physical function. Clinical trial registration: Registered on Clinicaltrials.gov {\#}NCT03104205. Registered on April 7, 2017. First participant enrolled on October 1st, 2018.

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Feasibility and efficacy of enteral tube feeding on weight stability, lean body mass, and patient-reported outcomes in pancreatic cancer cachexia (2021)

Journal of cachexia, sarcopenia and muscle

Authors: Gresham, Gillian; Placencio-Hickok, Veronica R.; Lauzon, Marie; Nguyen, Tyra; Kim, Haesoo; Mehta, Sejal; Paski, Shirley; Pandol, Stephen J.; Osipov, Arsen; Gong, Jun; Jamil, Laith H.; Nissen, Nicholas; Lo, Simon K.; Hendifar, Andrew E.

Abstract

Background: Advanced pancreatic ductal adenocarcinoma (PDAC) is characterized by progressive weight loss and nutritional deterioration. This wasting has been linked to poor survival outcomes, alterations in host defenses, decreased functional ability, and diminished health-related quality of life (HRQOL) in pancreatic cancer patients. There are currently no standardized approaches to the management of pancreatic cancer cachexia. This study explores the feasibility and efficacy of enteral tube feeding of a peptide-based formula to improve weight stability and patient-reported outcomes (PROs) in advanced PDAC patients with cachexia. Methods: This was a single-institution, single-arm prospective trial conducted between April 2015 and March 2019. Eligible patients were adults (>18 years) diagnosed with advanced or locally advanced PDAC and cachexia, defined as greater than 5% unexplained weight loss within 6 months from screening. The study intervention included three 28 day cycles of a semi-elemental peptide-based formula, administered through a jejunal or gastrojejunal feeding tube. The primary outcome was weight stability at 3 months (Cycle 3), defined as weight change less than 0.1 kg/baseline BMI unit from baseline. Secondary outcomes included changes in lean body mass, appendicular lean mass, bone mineral density, fat mass, and percent body fat, as measured with a DEXA scan, HRQOL (EORTC QLQC30) and NIH PROMIS PROs assessed at each cycle. Daily activity (steps, distance, active minutes, heart rate, and sleep) were remotely monitored using a wearable activity monitor (Fitbit) over the 3 month study period. Results: Thirty-six patients were screened for eligibility, 31 patients consented onto study and underwent jejunal tube placement, and 16 patients completed treatment: mean age 67 years (SD 9.3), 43.8% male. Among evaluable patients (n = 16), weight stability was achieved in 10 patients (62.5%), thus completing the trial early. Increases in lean body mass (1273.1, SD: 4078, P = 0.01) and appendicular lean mass (0.45, SD: 0.6, P = 0.02) were observed. Statistically significant improvements at Cycle 3 from baseline were also observed for QLQC30 role function [mean difference (MD): 20.1, P = 0.03], appetite (MD: 27.4, P = 0.02), and global health scores (MD: 13.3, P = 0.05) as well as for NIH PROMIS t-scores for depression (MD: −10.4, P = 0.006) and pain interference (MD: −7.5, P = 0.05). Objectively monitored (Fitbit) activity levels increased, although statistical significance was not reached. Conclusions: Our findings suggest that enteral nutrition support may improve weight stability, lean body mass, appendicular lean mass and PROs in PDAC patients with cachexia who completed treatment, representing a subsample of the study population. The feasibility and role of enteral feeding in routine care remain unclear, and larger and randomized controlled trials are warranted.

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Feasibility of a behavioral intervention using mobile health applications to reduce cardiovascular risk factors in cancer survivors: a pilot randomized controlled trial (2021)

Journal of cancer survivorship : research and practice

Authors: Chow, Eric J.; Doody, David R.; Di, Chongzhi; Armenian, Saro H.; Baker, K. Scott; Bricker, Jonathan B.; Gopal, Ajay K.; Hagen, Anna M.; Ketterl, Tyler G.; Lee, Stephanie J.; Reding, Kerryn W.; Schenk, Jeannette M.; Syrjala, Karen L.; Taylor, Sarah A.; Wang, Guangxing; Neuhouser, Marian L.; Mendoza, Jason A.

Abstract

Purpose: Determine the feasibility of a remotely delivered mobile health (mHealth)-supported intervention to improve diet and physical activity in hematologic malignancy survivors. Methods: Pilot randomized controlled trial of a 16-week intervention for improving diet and physical activity: individualized goal-setting (daily steps, sodium, saturated fat, added sugar intake) per feedback from mHealth trackers (Fitbit for activity; Healthwatch360 for diet), supplemented by a Facebook peer support group. Controls accessed the trackers without goal-setting or peer support. Everyone received standardized survivorship counseling with tailored advice from a clinician. Actigraphy and food frequency questionnaires assessed activity and diet at baseline and follow-up. Results: Forty-one participants (51.2% male; median age 45.1 years; 7.0 years from treatment) were randomized (24 intervention; 17 control). Fitbit and Healthwatch360 use were more common among intervention versus control participants (75.0% versus 70.6% and 50.0% versus 17.7% of eligible days, respectively). Most intervention participants (66.7%) engaged with Facebook; overall, 91.7% interacted with the study's mHealth applications. While no comparisons in activity or dietary outcomes between intervention versus control group met statistical significance, the intervention was associated with greater reductions in the targeted dietary factors and improvements in Healthy Eating Index-2015 score, moderate-vigorous physical activity time, and daily steps. Participant retention at 6 months was 90.2%. Conclusions: An intervention for cardiovascular risk reduction based on individualized goal-setting enhanced by mHealth and social media peer support was feasible and acceptable among cancer survivors. Implications for Cancer Survivors: Effective and easily disseminated strategies that improve diet and physical activity in this population are needed. Trial registration: Registered in ClinicalTrials.gov (NCT03574012) on June 29, 2018.

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Feasibility of Fitness Tracker Usage to Assess Activity Level and Toxicities in Patients With Colorectal Cancer (2021)

JCO clinical cancer informatics

Authors: Ward, William H.; Meeker, Caitlin R.; Handorf, Elizabeth; Hill, Maureen V.; Einarson, Margret; Alpaugh, R. Katherine; Holden, Thomas L.; Astsaturov, Igor; Denlinger, Crystal S.; Hall, Michael J.; Reddy, Sanjay S.; Sigurdson, Elin R.; Dotan, Efrat; Zibelman, Matthew; Meyer, Joshua E.; Farma, Jeffrey M.; Vijayvergia, Namrata

Abstract

PURPOSE: Performance status (PS) is a subjective assessment of patients' overall health. Quantification of physical activity using a wearable tracker (Fitbit Charge [FC]) may provide an objective measure of patient's overall PS and treatment tolerance. MATERIALS AND METHODS: Patients with colorectal cancer were prospectively enrolled into two cohorts (medical and surgical) and asked to wear FC for 4 days at baseline (start of new chemotherapy [± 4 weeks] or prior to curative resection) and follow-up (4 weeks [± 2 weeks] after initial assessment in medical and postoperative discharge in surgical cohort). Primary end point was feasibility, defined as 75% of patients wearing FC for at least 12 hours/d, 3 of 4 assigned days. Mean steps per day (SPD) were correlated with toxicities of interest (postoperative complication or ≥ grade 3 toxicity). A cutoff of 5,000 SPD was selected to compare outcomes. RESULTS: Eighty patients were accrued over 3 years with 55% males and a median age of 59.5 years. Feasibility end point was met with 68 patients (85%) wearing FC more than predefined duration and majority (91%) finding its use acceptable. The mean SPD count for patients with PS 0 was 6,313, and for those with PS 1, it was 2,925 (122 and 54 active minutes, respectively) (P = .0003). Occurrence of toxicity of interest was lower among patients with SPD > 5,000 (7 of 33, 21%) compared with those with SPD < 5,000 (14 of 43, 32%), although not significant (P = .31). CONCLUSION: Assessment of physical activity with FC is feasible in patients with colorectal cancer and well-accepted. SPD may serve as an adjunct to PS assessment and a possible tool to help predict toxicities, regardless of type of therapy. Future studies incorporating FC can standardize patient assessment and help identify vulnerable population.

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Feasibility, preliminary efficacy, and accessibility of a twitter-based social support group vs Fitbit only to decrease sedentary behavior in women (2021)

Internet Interventions

Authors: Oppezzo, M. A.; Tremmel, J. A.; Kapphahn, K.; Desai, M.; Baiocchi, M.; Sanders, M.; Prochaska, J. J.

Abstract

Background Health behavior change interventions delivered by social media allow for real-time, dynamic interaction, peer social support, and experimenter-provided content. Aims We tested the feasibility, acceptability, and preliminary efficacy of a novel Twitter-based walking break intervention with daily behavior change strategies and prompts for social support, combined with a Fitbit, vs. Fitbit alone. Methods In a 2-group pilot, 45 sedentary women from a heart clinic were randomized to Twitter + Fitbit activity tracker (Tweet4Wellness, n = 23) or Fitbit-only (control, n = 22). All received a Fitbit Inspire and 13 weeks of tailored weekly step goals. Tweet4Wellness consisted of a private Twitter support group, with daily automated behavior change “tweets” informed by behavior change theory, and encouragement to communicate within the group. Feasibility outcomes included recruitment and enrollment numbers, implementation challenges, and number and type of help requests from participants throughout the study period. Preliminary efficacy outcomes provided by Fitbit data were sedentary minutes, number of hours with >250 steps, maximum sitting bout, weighted sedentary median bout length, total steps, intensity minutes (>3.0 METS), and ratio of time spent sitting-to-moving. Acceptability outcomes included level of Twitter participation within Tweet4Wellness, and Likert scale plus open-ended survey questions on enjoyment and perceived effectiveness of intervention components. Survey data on acceptability of the features of the intervention were collected at 13 weeks (end-of-treatment [EOT]) and 22 weeks (follow-up). Results The study was feasible, with addressable implementation challenges. Tweet4Wellness participants changed significantly from baseline to EOT relative to control participants on number of active hours p = .018, total steps p = .028, and ratio of sitting-to-moving, p = .014. Only sitting-to-moving was significant at follow-up (p = .047). Among Tweet4Wellness participants, each tweet sent during treatment was associated with a 0.11 increase in active hours per day (p = .04) and a 292-step increase per day (p < .001). Tweet4Wellness participants averaged 54.8 (SD = 35.4) tweets, totaling 1304 tweets, and reported liking the accountability and peer support provided by the intervention. Conclusion A Twitter-delivered intervention for promoting physical activity among inactive women from a heart clinic was feasible, acceptable, and demonstrated preliminary efficacy in increasing daily active hours, daily total steps, and the ratio of sitting-to-moving from pre to post for the intervention compared with the control. Lessons learned from this pilot suggest that the next study should expand the recruitment pool, refine the intervention to increase group engagement, and select active hours, total steps, and ratio of sitting-to-movement as primary sedentary behavior measures.

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Feasibility, Usability, and Effectiveness of a Machine Learning-Based Physical Activity Chatbot: Quasi-Experimental Study (2021)

JMIR mHealth and uHealth

Authors: To, Quyen G.; Green, Chelsea; Vandelanotte, Corneel

Abstract

Background: Behavioral eHealth and mobile health interventions have been moderately successful in increasing physical activity, although opportunities for further improvement remain to be discussed. Chatbots equipped with natural language processing can interact and engage with users and help continuously monitor physical activity by using data from wearable sensors and smartphones. However, a limited number of studies have evaluated the effectiveness of chatbot interventions on physical activity. Objective: This study aims to investigate the feasibility, usability, and effectiveness of a machine learning-based physical activity chatbot. Methods: A quasi-experimental design without a control group was conducted with outcomes evaluated at baseline and 6 weeks. Participants wore a Fitbit Flex 1 (Fitbit LLC) and connected to the chatbot via the Messenger app. The chatbot provided daily updates on the physical activity level for self-monitoring, sent out daily motivational messages in relation to goal achievement, and automatically adjusted the daily goals based on physical activity levels in the last 7 days. When requested by the participants, the chatbot also provided sources of information on the benefits of physical activity, sent general motivational messages, and checked participants' activity history (ie, the step counts/min that were achieved on any day). Information about usability and acceptability was self-reported. The main outcomes were daily step counts recorded by the Fitbit and self-reported physical activity. Results: Among 116 participants, 95 (81.9%) were female, 85 (73.3%) were in a relationship, 101 (87.1%) were White, and 82 (70.7%) were full-time workers. Their average age was 49.1 (SD 9.3) years with an average BMI of 32.5 (SD 8.0) kg/m2. Most experienced technical issues were due to an unexpected change in Facebook policy (93/113, 82.3%). Most of the participants scored the usability of the chatbot (101/113, 89.4%) and the Fitbit (99/113, 87.6%) as at least “OK.” About one-third (40/113, 35.4%) would continue to use the chatbot in the future, and 53.1% (60/113) agreed that the chatbot helped them become more active. On average, 6.7 (SD 7.0) messages/week were sent to the chatbot and 5.1 (SD 7.4) min/day were spent using the chatbot. At follow-up, participants recorded more steps (increase of 627, 95% CI 219-1035 steps/day) and total physical activity (increase of 154.2 min/week; 3.58 times higher at follow-up; 95% CI 2.28-5.63). Participants were also more likely to meet the physical activity guidelines (odds ratio 6.37, 95% CI 3.31-12.27) at follow-up. Conclusions: The machine learning-based physical activity chatbot was able to significantly increase participants' physical activity and was moderately accepted by the participants. However, the Facebook policy change undermined the chatbot functionality and indicated the need to use independent platforms for chatbot deployment to ensure successful delivery of this type of intervention.

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Management of fatigue with physical activity and behavioural change support in vasculitis: a feasibility study (2021)

Rheumatology (Oxford, England)

Authors: Harper, L.; Hewitt, C. A.; Litchfield, I.; Morgan, M. D.; Chanouzas, D.; Caulfield, H. K.; Coughlan, L.; Dean, C.; Fletcher, K.; Cramp, F.; Greenfield, S.; Ives, N. J.; Jowett, S.; Kodabuckus, S.; Tearne, S.; Sehmi, S.; Edwardson, C.; Dawkins, N. P.; Daley, A. J.

Abstract

OBJECTIVE: Patients with ANCA associated vasculitis (AAV) experience high levels of fatigue, despite disease remission. This study assessed the feasibility and acceptability of a definitive randomised controlled trial of a behavioural-based physical activity intervention to support fatigue self-management in AAV patients. METHODS: AAV patients in disease remission with fatigue (Multidimensional Fatigue Inventory-20 general fatigue domain ≥) were randomly allocated to intervention or standard care in this single-centre open-label randomised controlled feasibility study. The intervention lasted 12 weeks and comprised eight face-to-face physical activity sessions with a facilitator and 12 weekly telephone calls. Participants were encouraged to monitor their physical activity using a tracker device (Fitbit). Standard care involved sign-posting to fatigue websites. The primary outcome was feasibility of a phase III trial assessed against three stop-go traffic light criteria, (recruitment, intervention adherence and study withdrawal). A qualitative study assessed participant views about the intervention. RESULTS: 248 patients were screened and 134 were eligible to participate (54%). Stop-go criteria were amber for recruitment; 43/134 (32%, 95% CI 24-40) eligible participants randomised, amber for adherence; 73% of participants attended all eight physical activity sessions, but only 11/22 (50%, 95% CI 29-71%) completed the intervention as per the intended schedule, and green for study withdrawal; 2/43 participants withdrew before 24 weeks (5%, 95% CI 0-11). Qualitative results suggested the intervention was acceptable. CONCLUSION: This study suggests a behavioural-based physical activity intervention targeting fatigue self-management was acceptable to patients with AAV, although recruitment and protocol adherence will need modification prior to a definitive trial. Clinical Trial Registration Number ISRCTN11929227.

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Measurement of Heart Rate Using the Polar OH1 and Fitbit Charge 3 Wearable Devices in Healthy Adults During Light, Moderate, Vigorous, and Sprint-Based Exercise: Validation Study (2021)

JMIR mHealth and uHealth

Authors: Muggeridge, D. J.; Hickson, K.; Davies, A. V.; Giggins, O. M.; Megson, I. L.; Gorely, T.; Crabtree, D. R.

Abstract

Background: Accurate, continuous heart rate measurements are important for health assessment, physical activity, and sporting performance, and the integration of heart rate measurements into wearable devices has extended its accessibility. Although the use of photoplethysmography technology is not new, the available data relating to the validity of measurement are limited, and the range of activities being performed is often restricted to one exercise domain and/or limited intensities. Objective: The primary objective of this study was to assess the validity of the Polar OH1 and Fitbit Charge 3 devices for measuring heart rate during rest, light, moderate, vigorous, and sprint-type exercise. Methods: A total of 20 healthy adults (9 female; height: mean 1.73 [SD 0.1] m; body mass: mean 71.6 [SD 11.0] kg; and age: mean 40 [SD 10] years) volunteered and provided written informed consent to participate in the study consisting of 2 trials. Trial 1 was split into 3 components: 15-minute sedentary activities, 10-minute cycling on a bicycle ergometer, and incremental exercise test to exhaustion on a motorized treadmill (18-42 minutes). Trial 2 was split into 2 components: 4 × 15-second maximal sprints on a cycle ergometer and 4 × 30- to 50-m sprints on a nonmotorized resistance treadmill. Data from the 3 devices were time-aligned, and the validity of Polar OH1 and Fitbit Charge 3 was assessed against Polar H10 (criterion device). Validity was evaluated using the Bland and Altman analysis, Pearson moment correlation coefficient, and mean absolute percentage error. Results: Overall, there was a very good correlation between the Polar OH1 and Polar H10 devices (r=0.95), with a mean bias of −1 beats{\textperiodcentered}min-1 and limits of agreement of −20 to 19 beats{\textperiodcentered}min-1. The Fitbit Charge 3 device underestimated heart rate by 7 beats{\textperiodcentered}min-1 compared with Polar H10, with a limit of agreement of −46 to 33 beats{\textperiodcentered}min-1 and poor correlation (r=0.8). The mean absolute percentage error for both devices was deemed acceptable (<5%). Polar OH1 performed well across each phase of trial 1; however, validity was worse for trial 2 activities. Fitbit Charge 3 performed well only during rest and nonsprint-based treadmill activities. Conclusions: Compared with our criterion device, Polar OH1 was accurate at assessing heart rate, but the accuracy of Fitbit Charge 3 was generally poor. Polar OH1 performed worse during trial 2 compared with the activities in trial 1, and the validity of the Fitbit Charge 3 device was particularly poor during our cycling exercises.

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Measuring Daily Compliance With Physical Activity Tracking in Ambulatory Surgery Patients: Comparative Analysis of Five Compliance Criteria (2021)

JMIR mHealth and uHealth

Authors: Kelly, Ryan; Jones, Simon; Price, Blaine; Katz, Dmitri; McCormick, Ciaran; Pearce, Oliver

Abstract

Background: Physical activity trackers such as the Fitbit can allow clinicians to monitor the recovery of their patients following surgery. An important issue when analyzing activity tracker data is to determine patients' daily compliance with wearing their assigned device, using an appropriate criterion to determine a valid day of wear. However, it is currently unclear as to how different criteria can affect the reported compliance of patients recovering from ambulatory surgery. Investigating this issue can help to inform the use of activity data by revealing factors that may impact compliance calculations. Objective: This study aimed to understand how using different criteria can affect the reported compliance with activity tracking in ambulatory surgery patients. It also aimed to investigate factors that explain variation between the outcomes of different compliance criteria. Methods: A total of 62 patients who were scheduled to undergo total knee arthroplasty (TKA, ie, knee replacement) volunteered to wear a commercial Fitbit Zip activity tracker over an 8-week perioperative period. Patients were asked to wear the Fitbit Zip daily, beginning 2 weeks prior to their surgery and ending 6 weeks after surgery. Of the 62 patients who enrolled in the study, 20 provided Fitbit data and underwent successful surgery. The Fitbit data were analyzed using 5 different daily compliance criteria, which consider patients as compliant with daily tracking if they either register >0 steps in a day, register >500 steps in a day, register at least one step in 10 different hours of the day, register >0 steps in 3 distinct time windows, or register >0 steps in 3 out of 4 six-hour time windows. The criteria were compared in terms of compliance outcomes produced for each patient. Data were explored using heatmaps and line graphs. Linear mixed models were used to identify factors that lead to variation between compliance outcomes across the sample. Results: The 5 compliance criteria produce different outcomes when applied to the patients' data, with an average 24% difference in reported compliance between the most lenient and strictest criteria. However, the extent to which each patient's reported compliance was impacted by different criteria was not uniform. Some individuals were relatively unaffected, whereas others varied by up to 72%. Wearing the activity tracker as a clip-on device, rather than on the wrist, was associated with greater differences between compliance outcomes at the individual level (P=.004, r=.616). This effect was statistically significant (P<.001) in the first 2 weeks after surgery. There was also a small but significant main effect of age on compliance in the first 2 weeks after surgery (P=.040). Gender and BMI were not associated with differences in individual compliance outcomes. Finally, the analysis revealed that surgery has an impact on patients' compliance, with noticeable reductions in activity following surgery. These reductions affect compliance calculations by discarding greater amounts of data under strict criteria. Conclusions: This study suggests that different compliance criteria cannot be used interchangeably to analyze activity data provided by TKA patients. Surgery leads to a temporary reduction in patients' mobility, which affects their reported compliance when strict thresholds are used. Reductions in mobility suggest that the use of lenient compliance criteria, such as >0 steps or windowed approaches, can avoid unnecessary data exclusion over the perioperative period. Encouraging patients to wear the device at their wrist may improve data quality by increasing the likelihood of patients wearing their tracker and ensuring that activity is registered in the 2 weeks after surgery.

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Measuring Daily Compliance with Physical Activity Tracking in Ambulatory Surgery Patients: Comparative Analysis of Five Compliance Criteria (Preprint) (2021)

JMIR mHealth and uHealth

Authors: Kelly, Ryan; Jones, Simon; Price, Blaine; Katz, Dmitri; McCormick, Ciaran; Pearce, Oliver

Abstract

Background: Physical activity trackers such as the Fitbit can allow clinicians to monitor the recovery of their patients following surgery. An important issue when analyzing activity tracker data is to determine patients' daily compliance with wearing their assigned device, using an appropriate criterion to determine a valid day of wear. However, it is currently unclear as to how different criteria can affect the reported compliance of patients recovering from ambulatory surgery. Investigating this issue can help to inform the use of activity data by revealing factors that may impact compliance calculations. Objective: This study aimed to understand how using different criteria can affect the reported compliance with activity tracking in ambulatory surgery patients. It also aimed to investigate factors that explain variation between the outcomes of different compliance criteria. Methods: A total of 62 patients who were scheduled to undergo total knee arthroplasty (TKA, ie, knee replacement) volunteered to wear a commercial Fitbit Zip activity tracker over an 8-week perioperative period. Patients were asked to wear the Fitbit Zip daily, beginning 2 weeks prior to their surgery and ending 6 weeks after surgery. Of the 62 patients who enrolled in the study, 20 provided Fitbit data and underwent successful surgery. The Fitbit data were analyzed using 5 different daily compliance criteria, which consider patients as compliant with daily tracking if they either register {\textgreater}0 steps in a day, register {\textgreater}500 steps in a day, register at least one step in 10 different hours of the day, register {\textgreater}0 steps in 3 distinct time windows, or register {\textgreater}0 steps in 3 out of 4 six-hour time windows. The criteria were compared in terms of compliance outcomes produced for each patient. Data were explored using heatmaps and line graphs. Linear mixed models were used to identify factors that lead to variation between compliance outcomes across the sample. Results: The 5 compliance criteria produce different outcomes when applied to the patients' data, with an average 24{\%} difference in reported compliance between the most lenient and strictest criteria. However, the extent to which each patient's reported compliance was impacted by different criteria was not uniform. Some individuals were relatively unaffected, whereas others varied by up to 72{\%}. Wearing the activity tracker as a clip-on device, rather than on the wrist, was associated with greater differences between compliance outcomes at the individual level (P=.004, r=.616). This effect was statistically significant (P{\textless}.001) in the first 2 weeks after surgery. There was also a small but significant main effect of age on compliance in the first 2 weeks after surgery (P=.040). Gender and BMI were not associated with differences in individual compliance outcomes. Finally, the analysis revealed that surgery has an impact on patients' compliance, with noticeable reductions in activity following surgery. These reductions affect compliance calculations by discarding greater amounts of data under strict criteria. Conclusions: This study suggests that different compliance criteria cannot be used interchangeably to analyze activity data provided by TKA patients. Surgery leads to a temporary reduction in patients' mobility, which affects their reported compliance when strict thresholds are used. Reductions in mobility suggest that the use of lenient compliance criteria, such as {\textgreater}0 steps or windowed approaches, can avoid unnecessary data exclusion over the perioperative period. Encouraging patients to wear the device at their wrist may improve data quality by increasing the likelihood of patients wearing their tracker and ensuring that activity is registered in the 2 weeks after surgery. Trial Registration: ClinicalTrials.gov NCT03518866; https://clinicaltrials.gov/ct2/show/NCT03518866

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Mobile Health Intervention Promoting Physical Activity in Adults Post Cardiac Rehabilitation: Pilot Randomized Controlled Trial (2021)

JMIR formative research

Authors: Park, Linda G.; Elnaggar, Abdelaziz; Lee, Sei J.; Merek, Stephanie; Hoffmann, Thomas J.; von Oppenfeld, Julia; Ignacio, Nerissa; Whooley, Mary A.

Abstract

Background: Cardiac rehabilitation (CR) is an exercise-based program prescribed after cardiac events associated with improved physical, mental, and social functioning; however, many patients return to a sedentary lifestyle leading to deteriorating functional capacity after discharge from CR. Physical activity (PA) is critical to avoid recurrence of cardiac events and mortality and maintain functional capacity. Leveraging mobile health (mHealth) strategies to increase adherence to PA is a promising approach. Based on the social cognitive theory, we sought to determine whether mHealth strategies (Movn mobile app for self-monitoring, supportive push-through messages, and wearable activity tracker) would improve PA and functional capacity over 2 months. Objective: The objectives of this pilot randomized controlled trial were to examine preliminary effects of an mHealth intervention on group differences in PA and functional capacity and group differences in depression and self-efficacy to maintain exercise after CR. Methods: During the final week of outpatient CR, patients were randomized 1:1 to the intervention group or usual care. The intervention group downloaded the Movn mobile app, received supportive push-through messages on motivation and educational messages related to cardiovascular disease (CVD) management 3 times per week, and wore a Charge 2 (Fitbit Inc) activity tracker to track step counts. Participants in the usual care group wore a pedometer and recorded their daily steps in a diary. Data from the 6-minute walk test (6MWT) and self-reported questionnaires were collected at baseline and 2 months. Results: We recruited 60 patients from 2 CR sites at a community hospital in Northern California. The mean age was 68.0 (SD 9.3) years, and 23% (14/60) were female; retention rate was 85% (51/60). Our results from 51 patients who completed follow-up showed the intervention group had a statistically significant higher mean daily step count compared with the control (8860 vs 6633; P=.02). There was no difference between groups for the 6MWT, depression, or self-efficacy to maintain exercise. Conclusions: This intervention addresses a major public health initiative to examine the potential for mobile health strategies to promote PA in patients with CVD. Our technology-based pilot mHealth intervention provides promising results on a pragmatic and contemporary approach to promote PA by increasing daily step counts after completing CR.

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Monitoring Beliefs and Physiological Measures Using Wearable Sensors and Smartphone Technology Among Students at Risk of COVID-19: Protocol for a mHealth Study (2021)

JMIR Res Protoc 2021;10(6):e29561 https://www.researchprotocols.org/2021/6/e29561

Authors: Christine; Clingan, Caroline; Gilley, Kristen; Rozwadowski, Michelle; Gainsburg, Izzy; Bradley, Christina; Barabas, Jenny; Sandford, Erin; Olesnavich, Mary; Tyler, Jonathan; Mayer, Caleb; DeMoss, Matthew; Flora, Christopher; Forger, Daniel B.; Cunningham, Julia Lee; Tewari, Muneesh; Choi, Sung Won

Abstract

Background: The COVID-19 pandemic has significantly impacted lives and greatly affected the mental health and public safety of an already vulnerable population—college students. Social distancing and isolation measures have presented challenges to students' mental health. mHealth apps and wearable sensors may help monitor students at risk of COVID-19 and support their mental well-being. Objective: This study aimed to monitor students at risk of COVID-19 by using a wearable sensor and a smartphone-based survey. Methods: We conducted a prospective study on undergraduate and graduate students at a public university in the Midwest United States. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal smartphone devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints: at baseline, 1 month later, 2 months later, 3 months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population. Results: This study enrolled 2158 college students between September 2020 and January 2021. Subjects are currently being followed-up for 1 academic year. Data collection and analysis are currently underway. Conclusions: This study examined student health and well-being during the COVID-19 pandemic and assessed the feasibility of using a wearable sensor and a survey in a college student population, which may inform the role of our mHealth tools in assessing student health and well-being. Finally, using data derived from a wearable sensor, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data toward the development of a model for the early prediction and detection of COVID-19. Trial Registration: ClinicalTrials.gov NCT04766788; https://clinicaltrials.gov/ct2/show/NCT04766788

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Monitoring work-related physical activity and estimating lower-limb loading: a proof-of-concept study (2021)

BMC musculoskeletal disorders

Authors: Wang, Xia; Perry, Thomas A.; Caroupapoull{\'{e}}, Jimmy; Forrester, Alexander; Arden, Nigel K.; Hunter, David J.

Abstract

Background: Physical activity (PA) is important to general health and knee osteoarthritis (OA). Excessive workplace PA is an established risk factor for knee OA however, appropriate methods of measurement are unclear. There is a need to examine and assess the utility of new methods of measuring workplace PA and estimating knee load prior to application to large-scale, knee OA cohorts. Our aims, therefore, were to monitor workplace PA and estimate lower-limb loading across different occupations in health participants. Methods: Twenty-four healthy adults, currently working full-time in a single occupation (≥ 35 h/week) and free of musculoskeletal disease, comorbidity and had no history of lower-limb injury/surgery (past 12-months) were recruited across New South Wales (Australia). A convenience sample was recruited with occupations assigned to levels of workload; sedentary, light manual and heavy manual. Metrics of workplace PA including tasks performed (i.e., sitting), step-count and lower-limb loading were monitored over 10 working days using a daily survey, smartwatch, and a smartphone. Results: Participants of light manual occupations had the greatest between-person variations in mean lower-limb load (from 2 to 59 kg*m/s3). Lower-limb load for most participants of the light manual group was similar to a single participant in heavy manual work (30 kg*m/s3) and was at least three times greater than the sedentary group (2 kg*m/s3). The trends of workplace PA over working hours were largely consistent, per individual, but rare events of extreme loads were observed across all participants (up to 760 kg*m/s3). Conclusions: There are large interpersonal variations in metrics of workplace PA, particularly among light and heavy manual occupations. Our estimates of lower-limb loading were largely consistent with pre-conceived levels of physical demand. We present a new approach to monitoring PA and estimating lower-limb loading, which could be applied to future occupational studies of knee OA.

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Optimization of a technology-supported physical activity promotion intervention for breast cancer survivors: Results from Fit2Thrive (2021)

Cancer

Authors: Phillips, Siobhan M.; Penedo, Frank J.; Collins, Linda M.; Solk, Payton; Siddique, Juned; Song, Jing; Cella, David; Courneya, Kerry S.; Ackermann, Ronald T.; Welch, Whitney A.; Auster-Gussman, Lisa A.; Whitaker, Madelyn; Cullather, Erin; Izenman, Emily; Spring, Bonnie

Abstract

Background: The benefits of moderate to vigorous physical activity (MVPA) for breast cancer survivors are well established. However, most are insufficiently active. Fit2Thrive used the Multiphase Optimization Strategy methodology to determine the effect of 5 intervention components on MVPA in this population. Methods: Two hundred sixty-nine participants (mean age, 52.5 years; SD, 9.9 years) received a core intervention (the Fit2Thrive self-monitoring app and Fitbit) and were randomly assigned to 5 intervention components set to on/off in a full factorial experiment: support calls, deluxe app, buddy, online gym, and text messages. The intervention was delivered over 12 weeks with a 12-week follow-up. MVPA was measured via accelerometry at the baseline (T1), at 12 weeks (T2), and at 24 weeks (T3). The main effects and interaction effects at each time point were examined for all components. Results: Trial retention was high: 91.8% had valid accelerometer data at T2 or T3. Across all conditions, there were significant increases in MVPA (+53.6 min/wk; P <.001) and in the proportion of survivors meeting MVPA guidelines (+22.3%; P <.001) at T2 that were maintained but attenuated at T3 (MVPA, +24.6 min/wk; P <.001; meeting guidelines, +12.6%; P <.001). No individual components significantly improved MVPA, although increases were greater for the on level versus the off level for support calls, buddy, and text messages at T2 and T3. Conclusions: The Fit2Thrive core intervention (the self-monitoring app and Fitbit) is promising for increasing MVPA in breast cancer survivors, but the components provided no additional increases in MVPA. Future research should evaluate the core intervention in a randomized trial and determine what components optimize MVPA behaviors in breast cancer survivors.

Performance of Fitbit Charge 3 against polysomnography in measuring sleep in adolescent boys and girls (2021)

Chronobiology International

Authors: Menghini, Luca; Yuksel, Dilara; Goldstone, Aimee; Baker, Fiona C.; de Zambotti, Massimiliano

Abstract

We evaluated the performance of Fitbit Charge 3™ (FC3), a multi-sensor commercial sleep-tracker, for measuring sleep in adolescents against gold-standard laboratory polysomnography (PSG). Single-night PSG and FC3 sleep outcomes were compared in thirty-nine adolescents (22 girls; 16–19 years), 12 of whom presented with clinical/subclinical DSM-5 insomnia symptoms (7 girls). Discrepancy analysis, Bland–Altman plots, and epoch-by-epoch analyses were used to evaluate FC3 performance. The influence of several factors potentially affecting FC3 performance (e.g., sex, age, body mass index, firmware version, and magnitude of heart rate changes between consecutive PSG epochs) was also tested. In the sample of healthy adolescents, FC3 systematically underestimated PSG total sleep time by about 11 min and sleep efficiency by 2.5%, and overestimated wake after sleep onset by 9 min. Proportional biases were detected for “light” and “deep” sleep duration, resulting in significant underestimation of these parameters for those participants having longer PSG N1+ N2 and N3 durations, respectively. No significant systematic bias was detected for sleep efficiency and sleep onset latency. Epoch-by-epoch analysis showed sleep-stage sensitivity (average proportion of PSG epochs correctly classified by the device for a given sleep stage) of 68% for wake, 78% for “light” sleep, 59% for “deep” sleep, and 69% for rapid eye movement (REM) sleep in healthy sleepers. Similar results were found in the sample of adolescents with insomnia symptoms. Body mass index was positively associated with FC3-PSG discrepancies in wake after sleep onset (R2 = .16, p = .048). The magnitude of the heart rate acceleration/deceleration between consecutive PSG epochs was an important factor affecting FC3 classifications of sleep stages. Our results are in line with a general trend in the literature, suggesting better performance for the recently introduced multi-sensor devices compared to motion-only devices, although further developments are needed to improve accuracy in sleep stage classification and wake detection. Further insight is needed to determine factors potentially affecting device performance, such as accuracy and reliability (consistency of performance over time), in different samples and conditions.

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Physical activity in hemodialysis patients on nondialysis and dialysis days: Prospective observational study (2021)

Hemodialysis international. International Symposium on Home Hemodialysis

Authors: Malhotra, R.; Kumar, U.; Virgen, P.; Magallon, B.; Garimella, P. S.; Chopra, T.; Kotanko, P.; Ikizler, T. A.; Trzebinska, D.; Cadmus-Bertram, L.; Ix, J. H.

Abstract

Introduction: The physical decline in patients with end-stage kidney disease (ESKD) is associated with morbidity and mortality. Prior studies have attempted to promote physical activity at the time of dialysis; however, physical activity patterns on the nondialysis days are unknown. This study aimed to quantify physical activity on dialysis and nondialysis days in hemodialysis patients using a wearable actigraph. Methods: In this prospective study, subjects receiving hemodialysis were recruited from two outpatient dialysis units in urban San Diego and rural Imperial County, CA, between March 2018 and April 2019. Key inclusion criteria included: (1) receiving thrice weekly hemodialysis for ≥3 months, (2) age ≥ 18 years, and (3) able to walk with or without assistive devices. All participants wore a Fitbit Charge 2 tracker for a minimum of 4 weeks. The primary outcome was the number of steps per day. Each participant completed the Physical Activity Questionnaire, the Patient Health Questionnaire (PHQ)-9, the PROMIS Short form Fatigue Questionnaire at baseline, and the Participant Technology Experience Questionnaire at day 7 after study enrolment. Findings: Of the 52 recruited, 45 participants (urban = 25; rural = 20) completed the study. The mean age was 61 ± 15 years, 42% were women, 64% were Hispanic, and the mean dialysis vintage was 4.4 ± 3.0 years. For those with valid Fitbit data (defined as ≥10 hours of wear per day) for 28 days (n = 45), participants walked an average of 3688 steps per day, and 73% of participants were sedentary (<5000 steps/day). Participants aged >80 years were less active than younger (age < 65 years) participants (1232 vs. 4529 steps, P = 0.01). There were no statistical differences between the groups when stratified by gender (women vs. men [2817 vs. 4324 steps, respectively]), urbanicity (rural vs. urban dialysis unit [3141 vs. 4123 steps, respectively]), and dialysis/nondialysis day (3177 vs. 4133 steps, respectively). Due to the small sample size, we also calculated effect sizes. The effect size was medium for the gender differences (cohen's d = 0.57) and small to medium for urbanicity and dialysis/nondialysis day (d = 0.37 and d = 0.33, respectively). We found no association between physical activity and self-reported depression and fatigue scale. The majority of participants (62%, 28/45) found the Fitbit tracker easy to wear and comfortable. Discussion: ESKD participants receiving hemodialysis are frequently sedentary, and differences appear more pronounced in older patients. These findings may assist in designing patient-centered interventions to increase physical activity among hemodialysis patients.

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Physical Activity Monitoring Using a Fitbit Device in Ischemic Stroke Patients: Prospective Cohort Feasibility Study (2021)

JMIR mHealth and uHealth

Authors: Katzan, I.; Schuster, A.; Kinzy, T.

Abstract

Background: Continuous tracking of ambulatory activity in real-world settings using step activity monitors has many potential uses. However, feasibility, accuracy, and correlation with performance measures in stroke patients have not been well-established. Objective: The primary study objective was to determine adherence with wearing a consumer-grade step activity monitor, the Fitbit Charge HR, in home-going ischemic stroke patients during the first 90 days after hospital discharge. Secondary objectives were to (1) determine accuracy of step counts of the Fitbit Charge HR compared with a manual tally; (2) calculate correlations between the Fitbit step counts and the mobility performance scores at discharge and 30 days after stroke; (3) determine variability and change in weekly step counts over 90 days; and (4) evaluate patient experience with using the Fitbit Charge HR poststroke. Methods: A total of 15 participants with recent mild ischemic stroke wore a Fitbit Charge HR for 90 days after discharge and completed 3 mobility performance tests from the National Institutes of Health Toolbox at discharge and Day 30: (1) Standing Balance Test, (2) 2-Minute Walk Endurance Test, and (3) 4-Meter Walk Gait Speed Test. Accuracy of step activity monitors was assessed by calculating differences in steps recorded on the step activity monitor and a manual tally during 2-minute walk tests. Results: Participants had a mean age of 54 years and a median modified Rankin scale score of 1. Mean daily adherence with step activity monitor use was 83.6%. Mean daily step count in the first week after discharge was 4376. Daily step counts increased slightly during the first 30 days after discharge (average increase of 52.5 steps/day; 95% CI 32.2-71.8) and remained stable during the 30-90 day period after discharge. Mean step count difference between step activity monitor and manual tally was –4.8 steps (–1.8%). Intraclass correlation coefficients for step counts and 2-minute walk, standing balance, and 4-meter gait speed at discharge were 0.41 (95% CI –0.14 to 0.75), –0.12 (95% CI –0.67 to 0.64), and 0.17 (95% CI –0.46 to 0.66), respectively. Values were similarly poor at 30 days. Conclusions: The use of consumer-grade Fitbit Charge HR in patients with recent mild stroke is feasible with reasonable adherence and accuracy. There was poor correlation between step counts and gait speed, balance, and endurance. Further research is needed to evaluate the association between step counts and other outcomes relevant to patients, including patient-reported outcomes and measures of physical function.

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Physical activity patterns, adherence to using a wearable activity tracker during a 12-week period and correlation between self-reported function and physical activity in working age individuals with hip and/or knee osteoarthritis (2021)

BMC Musculoskeletal Disorders 2021 22:1

Authors: Östlind, Elin; Sant’Anna, Anita; Eek, Frida; Stigmar, Kjerstin; Hansson, Eva Ekvall

Abstract

A majority of individuals with osteoarthritis (OA) are insufficiently physically active. Self-monitoring with wearable activity trackers (WAT) could promote physical activity (PA), and increased knowledge of PA patterns and adherence to using a WAT is needed. The aim of this study was to describe PA patterns and adherence to WAT-use during an intervention among participants of working age with hip and/or knee OA. The study further explores the correlation between self-reported joint function and PA. Individuals of working age with hip and/or knee OA who used a WAT, Fitbit Flex 2, for 12 weeks were included. Participants monitored their PA in the Fitbit-app. An activity goal of 7,000 steps/day was set. Steps and minutes in light (L), moderate and vigorous (MV) PA were collected from the Fitbit. Self-reported joint function (HOOS/KOOS) was completed. Data was analyzed with linear mixed models and Spearman’s rank correlation. Seventy-five participants (45–66 years) walked on average 10 593 (SD 3431) steps/day, spent 248.5 (SD 42.2) minutes in LPA/day, 48.1 (SD 35.5) minutes in MVPA/day, 336.0 (SD 249.9) minutes in MVPA/week and used the Fitbit for an average of 88.4 % (SD 11.6) of the 12-week period. 86.7 % took > 7,000 steps/day and 77.3 % spent > 150 min in MVPA/week. Mean daily steps/week decreased significantly over the 12 weeks (β-coefficient − 117, 95 % CI -166 to -68, p = < 0.001) as well as mean daily minutes in LPA/week (β-coefficient − 2.3, 95 % CI -3.3 to -1.4, p = < 0.001), mean daily minutes in MVPA/week (β-coefficient − 0.58, 95 % CI -1.01 to -0.16, p = 0.008) and mean adherence to Fitbit-use per week (β-coefficient − 1.3, 95 % CI -1.8 to -0.8, p = < 0.001). There were no significant correlations between function (HOOS/KOOS) and PA. The majority of participants reached 7,000 steps/day and the recommended 150 min in MVPA per week. However, PA decreased slightly but gradually over time. Adherence to using the Fitbit was high but also decreased during the intervention. Understanding PA patterns and the use of a Fitbit to promote PA could be beneficial in tailoring interventions for individuals with hip and/or knee OA.

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Stepping into survivorship pilot study: Harnessing mobile health and principles of behavioral economics to increase physical activity in ovarian cancer survivors (2021)

Gynecologic oncology

Authors: Schrier, Elizabeth; Xiong, Niya; Thompson, Embree; Poort, Hanneke; Schumer, Susan; Liu, Joyce F.; Krasner, Carolyn; Campos, Susana M.; Horowitz, Neil S.; Feltmate, Colleen; Konstantinopoulos, Panagiotis A.; Dinardo, Margaret M.; Tayob, Nabihah; Matulonis, Ursula A.; Patel, Mitesh; Wright, Alexi A.

Abstract

Objective: Physical activity improves physical function, quality of life, and mental health, yet fewer than 80% of ovarian cancer survivors meet activity guidelines. This pilot intervention study aimed to increase physical activity in ovarian cancer survivors by leveraging principles of behavioral economics, gamification, and social support. Methods: This 24-week study (12-week intervention; 12-week follow-up) enrolled women with ovarian cancer after completion of first-line treatment with a self-selected “teammate.” Participants used Fitbits to measure daily steps, select an increased step goal, and enroll in a collaborative game, including points and levels for achieving step goals. Primary outcomes were feasibility (defined a priori as ≥60% approach-to-consent ratio and ≥ 70% adherence to Fitbit), acceptability (≤20% of participants reporting burden or regret for participation) and preliminary efficacy (≥70% reporting increased motivation); exploratory outcomes included change in steps. Results: We recruited 24 participants (mean age = 63 years, range = 37–79 years) with a 94% approach-to-consent ratio. All participants completed the intervention with 94% tracker adherence. At 24-week follow-up, 1/24 (≤5%) of participants reported burden; 0/24 (0%) reported regret for study participation; and 22/24 (>90%) agreed/strongly agreed that “the study motivated me to increase activity levels.” Participants' mean daily steps were 6210.7 (±3328.1) at baseline and increased to 7643 (± 3610.9) steps (p < 0.001) during the 12-week intervention. Conclusions: This pilot study demonstrated feasibility, acceptability, and preliminary efficacy, justifying a larger randomized clinical trial to test efficacy at increasing activity levels. Future studies should examine strategies for maintaining increased activity levels in survivors over time.

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The Association Between Logging Steps Using a Website, App, or Fitbit and Engaging With the 10,000 Steps Physical Activity Program: Observational Study (2021)

Journal of medical Internet research

Authors: Rayward, A. T.; Vandelanotte, C.; Van Itallie, A.; Duncan, M. J.

Abstract

Background: Engagement is positively associated with the effectiveness of digital health interventions. It is unclear whether tracking devices that automatically synchronize data (eg, Fitbit) produce different engagement levels compared with manually entering data. Objective: This study examines how different step logging methods in the freely available 10,000 Steps physical activity program differ according to age and gender and are associated with program engagement. Methods: A subsample of users (n=22,142) of the free 10,000 Steps physical activity program were classified into one of the following user groups based on the step-logging method: Website Only (14,617/22,142, 66.01%), App Only (2100/22,142, 9.48%), Fitbit Only (1705/22,142, 7.7%), Web and App (2057/22,142, 9.29%), and Fitbit Combination (combination of web, app, and Fitbit; 1663/22,142, 7.51%). Generalized linear regression and binary logistic regression were used to examine differences between user groups' engagement and participation parameters. The time to nonusage attrition was assessed using Cox proportional hazards regression. Results: App Only users were significantly younger and Fitbit user groups had higher proportions of women compared with other groups. The following outcomes were significant and relative to the Website Only group. The App Only group had fewer website sessions (odds ratio [OR] −6.9, 95% CI −7.6 to −6.2), whereas the Fitbit Only (OR 10.6, 95% CI 8.8-12.3), Web and App (OR 1.5, 95% CI 0.4-2.6), and Fitbit Combination (OR 8.0; 95% CI 6.2-9.7) groups had more sessions. The App Only (OR −0.7, 95% CI −0.9 to −0.4) and Fitbit Only (OR −0.5, 95% CI −0.7 to −0.2) groups spent fewer minutes on the website per session, whereas the Fitbit Combination group (OR 0.2, 95% CI 0.0-0.5) spent more minutes. All groups, except the Fitbit Combination group, viewed fewer website pages per session. The mean daily step count was lower for the App Only (OR −201.9, 95% CI −387.7 to −116.0) and Fitbit Only (OR −492.9, 95% CI −679.9 to −305.8) groups but higher for the Web and App group (OR 258.0, 95% CI 76.9-439.2). The Fitbit Only (OR 5.0, 95% CI 3.4-6.6), Web and App (OR 7.2, 95% CI 5.9-8.6), and Fitbit Combination (OR 15.6, 95% CI 13.7-17.5) groups logged a greater number of step entries. The App Only group was less likely (OR 0.65, 95% CI 0.46-0.94) and other groups were more likely to participate in Challenges. The mean time to nonusage attrition was 35 (SD 26) days and was lower than average in the Website Only and App Only groups and higher than average in the Web and App and Fitbit Combination groups. Conclusions: Using a Fitbit in combination with the 10,000 Steps app or website enhanced engagement with a real-world physical activity program. Integrating tracking devices that synchronize data automatically into real-world physical activity interventions is one strategy for improving engagement.

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The Effect of Aerobic Training and Increasing Nonexercise Physical Activity on Cardiometabolic Risk Factors (2021)

Medicine and science in sports and exercise

Authors: Swift, Damon L.; Nevels, Tyara R.; Solar, Chelsey A.; Brophy, Patricia M.; McGee, Joshua E.; Brewer, Savanna B.; Clark, Angela; Houmard, Joseph A.; Lutes, Lesley D.

Abstract

PURPOSE: Epidemiological studies suggest that sedentary behavior is an independent risk factor for cardiovascular mortality independent of meeting physical activity guidelines. However, limited evidence of this relationship is available from prospective interventions. The purpose of the present study is to evaluate the combined effect of aerobic training and increasing nonexercise physical activity on body composition and cardiometabolic risk factors. METHODS: Obese adults (N = 45) were randomized to 6 months of aerobic training (AERO), aerobic training and increasing nonexercise physical activity ($\sim$3000 steps above baseline levels; AERO-PA), or a control (CON) group. The AERO and AERO-PA groups performed supervised aerobic training (3-4 times per week). The AERO-PA group wore Fitbit One accelerometers and received behavioral coaching to increase nonexercise physical activity. RESULTS: There was a larger increase in fitness in the AERO-PA group (0.27 L{\textperiodcentered}min-1; confidence interval (CI), 0.16 to 0.40 L{\textperiodcentered}min-1) compared with the AERO group (0.09 L{\textperiodcentered}min-1; CI, -0.04 to 0.22 L{\textperiodcentered}min-1) and the CON group (0.01; CI, -0.11 to 0.12 L{\textperiodcentered}min-1). Although significant findings were not observed in the entire study sample, when the analysis was restricted to participants compliant to the intervention (n = 33), we observed significant reductions in waist circumference, percent weight loss, body fat, 2-h glucose, and 2-h insulin in comparison to the CON group (P < 0.05), but not the AERO group. Furthermore, linear regression models showed that change in steps was associated with 21% and 26% of the variation in percent weight loss and percent fat loss, respectively. CONCLUSIONS: Increasing nonexercise physical activity with aerobic training may represent a viable strategy to augment the fitness response in comparison to aerobic training alone and has promise for other health indicators.

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Use of Fitbit Devices in Physical Activity Intervention Studies Across the Life Course: Narrative Review (2021)

JMIR mHealth and uHealth

Authors: St Fleur, R. G.; St George, S. M.; Leite, R.; Kobayashi, M.; Agosto, Y.; Jake-Schoffman, D. E.

Abstract

Background: Commercial off-the-shelf activity trackers (eg, Fitbit) allow users to self-monitor their daily physical activity (PA), including the number of steps, type of PA, amount of sleep, and other features. Fitbits have been used as both measurement and intervention tools. However, it is not clear how they are being incorporated into PA intervention studies, and their use in specific age groups across the life course is not well understood. Objective: This narrative review aims to characterize how PA intervention studies across the life course use Fitbit devices by synthesizing and summarizing information on device selection, intended use (intervention vs measurement tool), participant wear instructions, rates of adherence to device wear, strategies used to boost adherence, and the complementary use of other PA measures. This review provides intervention scientists with a synthesis of information that may inform future trials involving Fitbit devices. Methods: We conducted a search of the Fitabase Fitbit Research Library, a database of studies published between 2012 and 2018. Of the 682 studies available on the Fitabase research library, 60 interventions met the eligibility criteria and were included in this review. A supplemental search in PubMed resulted in the inclusion of 15 additional articles published between 2019 and 2020. A total of 75 articles were reviewed, which represented interventions conducted in childhood; adolescence; and early, middle, and older adulthood. Results: There was considerable heterogeneity in the use of Fitbit within and between developmental stages. Interventions for adults typically required longer wear periods, whereas studies on children and adolescents tended to have more limited device wear periods. Most studies used developmentally appropriate behavior change techniques and device wear instructions. Regardless of the developmental stage and intended Fitbit use (ie, measurement vs intervention tool), the most common strategies used to enhance wear time included sending participants reminders through texts or emails and asking participants to log their steps or synchronize their Fitbit data daily. The rates of adherence to the wear time criteria were reported using varying metrics. Most studies supplemented the use of Fitbit with additional objective or self-reported measures for PA. Conclusions: Overall, the heterogeneity in Fitbit use across PA intervention studies reflects its relative novelty in the field of research. As the use of monitoring devices continues to expand in PA research, the lack of uniformity in study protocols and metrics of reported measures represents a major issue for comparability purposes. There is a need for increased transparency in the prospective registration of PA intervention studies. Researchers need to provide a clear rationale for the use of several PA measures and specify the source of their main PA outcome and how additional measures will be used in the context of Fitbit-based interventions.

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Using a consumer-based wearable activity tracker for physical activity goal setting and measuring steps in pregnant women with gestational diabetes mellitus: exploring acceptance and validity (2021)

BMC Pregnancy and Childbirth

Authors: Ehrlich, Samantha F.; Maples, Jill M.; Barroso, Cristina S.; Brown, Kathleen C.; Bassett, David R.; Zite, Nikki B.; Fortner, Kimberly B.

Abstract

Background: Activity monitoring devices may be used to facilitate goal-setting, self-monitoring, and feedback towards a step-based physical activity (PA) goal. This study examined the performance of the wrist-worn Fitbit Charge 3™ (FC3) and sought opinions on walking and stepping-in-place from women with gestational diabetes (GDM). Methods: Participants completed six 2-min metronome-assisted over ground bouts that varied by cadence (67, 84, or 100 steps per minute) and mode (walking or stepping-in-place; N = 15), with the sequence randomized. Steps were estimated by FC3 and measured, in duplicate, by direct observation (hand-tally device, criterion). Equivalence testing by the two one-sided tests (TOST) method assessed agreement within ± 15%. Mean absolute percent error (MAPE) of steps were compared to 10%, the accuracy standard of the Consumer Technology Association (CTA)™. A subset (n = 10) completed a timed, 200-m self-paced walk to assess natural walking pace and cadence. All participants completed semi-structured interviews, which were transcribed and analyzed using descriptive and interpretive coding. Results: Mean age was 27.0 years (SD 4.2), prepregnancy BMI 29.4 kg/m2 (8.3), and gestational age 32.8 weeks (SD 2.6). The FC3 was equivalent to hand-tally for bouts of metronome-assisted walking and stepping-in-place at 84 and 100 steps per minute (i.e., P <.05), although walking at 100 steps per minute (P =.01) was no longer equivalent upon adjustment for multiple comparisons (i.e., at P <.007). The FC3 was equivalent to hand-tally during the 200-m walk (i.e., P <.001), in which mean pace was 68.2 m per minute (SD 10.7), or 2.5 miles per hour, and mean cadence 108.5 steps per minute (SD 6.5). For walking at 84 and 100 steps per minute, stepping-in-place at 100 steps per minute, and the 200-m walk, MAPE was within 10%, the accuracy standard of the CTA™. Interviews revealed motivation for PA, that stepping-in-place was an acceptable alternative to walking, and competing responsibilities made it difficult to find time for PA. Conclusions: The FC3 appears to be a valid step counter during the third trimester, particularly when walking or stepping-in-place at or close to women's preferred cadence.

Using an activity tracker to increase motivation for physical activity in patients with type 2 diabetes in primary care: a randomized pilot trial (2021)

mHealth

Authors: Pelletier, Cynthia; Gagnon, Marie Pierre; Alm{\'{e}}ras, Natalie; Despr{\'{e}}s, Jean Pierre; Poirier, Paul; Tremblay, Angelo; Chabot, Christian; Rh{\'{e}}aume, Caroline

Abstract

Background: Adopting healthy lifestyle habits reduces the risk of type 2 diabetes (T2D) and its complications. The use of an activity tracker to monitor physical activity (PA) could favor behavior changes in patients with chronic diseases such as diabetes. The aims of this study were: (I) to evaluate the impact of an activity tracker on PA and cardiometabolic risk variables in patients with T2D; (II) to assess the feasibility of its implantation in a primary care setting. Methods: This 3-month study was a pilot randomized controlled trial of 30 patients with T2D followed at a university-affiliated Family Medicine Group. Patients were randomly assigned to either: (I) control group, including a PA promotion intervention supported by a kinesiologist or (II) intervention group, including a PA promotion intervention supported by a kinesiologist with the addition of an activity tracker (Fitbit). Cardiometabolic risk variables, PA and motivation were assessed at baseline and after three months. Satisfaction and acceptability of wearing the activity tracker were measured in the intervention group. Results: PA assessed by questionnaires increased in both groups, change being greater in the intervention group (P<0.05). Autonomous motivation in both groups was higher than controlled motivation (P<0.001). Eighty-six percent of the participants in the intervention group were satisfied with their activity tracker use and the compliance remained high. High-density lipoprotein cholesterol increased in the intervention group and decreased in the control group (P=0.014). Resting systolic and diastolic blood pressure decreased over time in both groups (P<0.05) whereas glycated hemoglobin tended to decrease in both groups (P=0.080). Significant correlations were observed between average steps per day and changes in waist circumference (pre: -0.721, P=0.044; post: -0.736, P=0.038), body mass index (pre: -0.764, P=0.010; post: -0.771, P=0.009) and fat percentage (pre: -0.654, P=0.040; post: -0.686, P=0.028) in the intervention group. Conclusions: Our pilot study shows that the use of an activity tracker improves cardiometabolic risk variables in patients with T2D and could potentially be a motivation tool to increase PA in primary care setting.

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Using fitbit as an mHealth intervention tool to promote physical activity: Potential challenges and solutions (2021)

JMIR mHealth and uHealth

Authors: Balbim, Guilherme M.; Marques, Isabela G.; Marquez, David X.; Patel, Darshilmukesh; Sharp, Lisa K.; Kitsiou, Spyros; Nyenhuis, Sharmilee M.

Abstract

Consumer-based physical activity (PA) trackers, also known as wearables, are increasingly being used in research studies as intervention or measurement tools. One of the most popular and widely used brands of PA trackers is Fitbit. Since the release of the first Fitbit in 2009, hundreds of experimental studies have used Fitbit devices to facilitate PA self-monitoring and behavior change via goal setting and feedback tools. Fitbit's ability to capture large volumes of PA and physiological data in real time creates enormous opportunities for researchers. At the same time, however, it introduces a number of challenges (eg, technological, operational, logistical), most of which are not sufficiently described in study publications. Currently, there are no technical reports, guidelines, nor other types of publications discussing some of these challenges and offering guidance to researchers on how to best incorporate Fitbit devices in their study design and intervention to achieve their research goals. As a result, researchers are often left alone to discover and address some of these issues during the study through “trial and error.” This paper aims to address this gap. Drawing on our cumulative experience of conducting multiple studies with various Fitbit PA trackers over the years, we present and discuss various key challenges associated with the use of Fitbit PA trackers in research studies. Difficulties with the use of Fitbit PA trackers are encountered throughout the entire research process. Challenges and solutions are categorized in 4 main categories: study preparation, intervention delivery, data collection and analysis, and study closeout. Subsequently, we describe a number of empirically tested strategies used in 4 of our interventional studies involving participants from a broad range of demographic characteristics, racial/ethnic backgrounds, and literacy levels. Researchers should be prepared to address challenges and issues in a timely fashion to ensure that the Fitbit effectively assists participants and researchers in achieving research and outcome goals.

Validity and Acceptability of Wearable Devices for Monitoring Step-Count and Activity Minutes Among People With Multiple Sclerosis (2021)

Frontiers in Rehabilitation Sciences

Authors: Lavelle, Grace; Norris, Meriel; Flemming, Julie; Harper, Jamie; Bradley, Joan; Johnston, Helen; Fortune, Jennifer; Stennett, Andrea; Kilbride, Cherry; Ryan, Jennifer M.

Abstract

Multiple wearable devices that purport to measure physical activity are widely available to consumers. While they may support increases in physical activity among people with multiple sclerosis (MS) by providing feedback on their performance, there is little information about the validity and acceptability of these devices. Providing devices that are perceived as inaccurate and difficult to use may have negative consequences for people with MS, rather than supporting participation in physical activity. The aim of this study was, therefore, to assess the validity and acceptability of commercially available devices for monitoring step-count and activity time among people with MS. Nineteen ambulatory adults with MS [mean (SD) age 52.1 (11.9) years] participated in the study. Step-count was assessed using five commercially available devices (Fitbit Alta, Fitbit Zip, Garmin Vivofit 4, Yamax Digi Walker SW200, and Letscom monitor) and an activPAL3μ while completing nine everyday activities. Step-count was also manually counted. Time in light activity, moderate-to-vigorous activity, and total activity were measured during activities using an Actigraph GT3X accelerometer. Of the 19 participants who completed the validity study, fifteen of these people also wore the five commercially available devices for three consecutive days each, and participated in a semi-structured interview regarding their perception of the acceptability of the monitors. Mean percentage error for step-count ranged from 12.1\% for the Yamax SW200 to -112.3\% for the Letscom. Mean step-count as manually determined differed to mean step-count measured by the Fitbit Alta (p = 0.002), Garmin vivofit 4 (p {\textless} 0.001), Letscom (p {\textless} 0.001) and the research standard device, the activPAL3μ (p {\textless} 0.001). However, 95\% limits of agreement were smallest for the activPAL3μ and largest for the Fitbit Alta. Median percentage error for activity minutes was 52.9\% for the Letscom and 100\% for the Garmin Vivofit 4 and Fitbit Alta compared to minutes in total activity. Three inductive themes were generated from participant accounts: Interaction with device; The way the device looks and feels; Functionality. In conclusion, commercially available devices demonstrated poor criterion validity when measuring step-count and activity time in people with MS. This negatively affected the acceptability of devices, with perceived inaccuracies causing distrust and frustration. Additional considerations when designing devices for people with MS include an appropriately sized and lit display and ease of attaching and charging devices.

Validity of Wrist-Wearable Activity Devices for Estimating Physical Activity in Adolescents: Comparative Study (2021)

JMIR mHealth and uHealth

Authors: Hao, Yingying; Ma, Xiao Kai; Zhu, Zheng; Cao, Zhen Bo

Abstract

Background: The rapid advancements in science and technology of wrist-wearable activity devices offer considerable potential for clinical applications. Self-monitoring of physical activity (PA) with activity devices is helpful to improve the PA levels of adolescents. However, knowing the accuracy of activity devices in adolescents is necessary to identify current levels of PA and assess the effectiveness of intervention programs designed to increase PA. Objective: The study aimed to determine the validity of the 11 commercially available wrist-wearable activity devices for monitoring total steps and total 24-hour total energy expenditure (TEE) in healthy adolescents under simulated free-living conditions. Methods: Nineteen (10 male and 9 female) participants aged 14 to 18 years performed a 24-hour activity cycle in a metabolic chamber. Each participant simultaneously wore 11 commercial wrist-wearable activity devices (Mi Band 2 [XiaoMi], B2 [Huawei], Bong 2s [Meizu], Amazfit [Huamei], Flex [Fitbit], UP3 [Jawbone], Shine 2 [Misfit], GOLiFE Care-X [GoYourLife], Pulse O2 [Withings], Vivofit [Garmin], and Loop [Polar Electro]) and one research-based triaxial accelerometer (GT3X+ [ActiGraph]). Criterion measures were total EE from the metabolic chamber (mcTEE) and total steps from the GT3X+ (AGsteps). Results: Pearson correlation coefficients r for 24-hour TEE ranged from.78 (Shine 2, Amazfit) to.96 (Loop) and for steps ranged from 0.20 (GOLiFE) to 0.57 (Vivofit). Mean absolute percent error (MAPE) for TEE ranged from 5.7% (Mi Band 2) to 26.4% (Amazfit) and for steps ranged from 14.2% (Bong 2s) to 27.6% (Loop). TEE estimates from the Mi Band 2, UP3, Vivofit, and Bong 2s were equivalent to mcTEE. Total steps from the Bong 2s were equivalent to AGsteps. Conclusions: Overall, the Bong 2s had the best accuracy for estimating TEE and total steps under simulated free-living conditions. Further research is needed to examine the validity of these devices in different types of physical activities under real-world conditions.

Wrist-mounted accelerometers provide objective evidence of disease and recovery in patients with frozen shoulder (2021)

JSES international

Authors: Mackenzie, Samuel P.; McLean, Michael; Spasojevic, Milo{\v{s}}; Niu, Rui; Kruse, Lisa; Gwynne, Jasmin; Young, Allan; Cass, Benjamin

Abstract

Background: Commercially available wrist-mounted exercise monitors may offer objective data on disease and recovery. This study is the first to evaluate the potential of such devices in the assessment of frozen shoulder and the effects of treatment. Methods: Twenty-one patients with isolated, unilateral frozen shoulder wore a wrist-mounted accelerometer (Fitbit Fire II, Fitbit Inc. 2007, California, USA) on each wrist for two separate seven-day periods, one week before and six months after treatment. The monitors produced an activity count for each 24-hour period, accounting for all movements of the upper limb. Three values were calculated for each time period: (1) the mean activity count for each limb, (2) the total activity count for both limbs, and (3) an activity count ratio calculated by dividing the activity of the frozen limb by the unaffected limb. Constant score, American Shoulder and Elbow Surgeons, visual analog scale–pain, and range of movement were recorded before and after treatment. Results: Mean activity counts were significantly lower in the frozen shoulder limb than those in the unaffected limb over the initial seven-day period (6066 vs. 7516; P = .04). The activity count ratio significantly improved after treatment (0.83 vs. 096; p 0.01), whereas the mean total activity count remained similar before and after treatment (14915 vs. 12371; P = .18), demonstrating that activity transferred from the unaffected limb back to the previously frozen limb. Range of movement (P < .01), Constant (P < .01), American Shoulder and Elbow Surgeons (P < .01), and visual analog scale–pain (P < .01) scores all significantly improved after treatment, but there was no correlation with the data from the activity monitor. Discussion: Wrist-mounted accelerometers are sufficiently sensitive to detect a difference in limb activity in patients affected by frozen shoulder. The movement deficit between the affected and unaffected limbs improved by 14% after treatment. These data could be used in conjunction with subjective scores to offer a clearer insight into patient disease burden and recovery.

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A Mind-Body Physical Activity Program for Chronic Pain With or Without a Digital Monitoring Device: Proof-of-Concept Feasibility Randomized Controlled Trial (2020)

JMIR formative research

Authors: Greenberg, Jonathan; Popok, Paula J.; Lin, Ann; Kulich, Ronald J.; James, Peter; Macklin, Eric A.; Millstein, Rachel A.; Edwards, Robert R.; Vranceanu, Ana Maria

Abstract

Background: Chronic pain is associated with poor physical and emotional functioning. Nonpharmacological interventions can help, but improvements are small and not sustained. Previous clinical trials do not follow recommendations to comprehensively target objectively measured and performance-based physical function in addition to self-reported physical function. Objective: This study aimed to establish feasibility benchmarks and explore improvements in physical (self-reported, performance based, and objectively measured) and emotional function, pain outcomes, and coping through a pilot randomized controlled trial of a mind-body physical activity program (GetActive) with and without a digital monitoring device (GetActive-Fitbit), which were iteratively refined through mixed methods. Methods: Patients with chronic pain were randomized to the GetActive (n=41) or GetActive-Fitbit (n=41) programs, which combine relaxation, cognitive behavioral, and physical restoration skills and were delivered in person. They completed in-person assessments before and after the intervention. Performance-based function was assessed with the 6-min walk test, and step count was measured with an ActiGraph. Results: Feasibility benchmarks (eg, recruitment, acceptability, credibility, therapist adherence, adherence to practice at home, ActiGraph wear, and client satisfaction) were good to excellent and similar in both programs. Within each program, we observed improvement in the 6-min walk test (mean increase=+41 m, SD 41.15; P<.001; effect size of 0.99 SD units for the GetActive group and mean increase=+50 m, SD 58.63; P<.001; effect size of 0.85 SD units for the GetActive-Fitbit group) and self-reported physical function (P=.001; effect size of 0.62 SD units for the GetActive group and P=.02; effect size of 0.38 SD units for the GetActive-Fitbit group). The mean step count increased only among sedentary patients (mean increase=+874 steps for the GetActive group and +867 steps for the GetActive-Fitbit group). Emotional function, pain intensity, pain coping, and mindfulness also improved in both groups. Participants rated themselves as much improved at the end of the program, and those in the GetActive-Fitbit group noted that Fitbit greatly helped with increasing their activity. Conclusions: These preliminary findings support a fully powered efficacy trial of the two programs against an education control group. We present a model for successfully using the Initiative on the Methods, Measurement, and Pain Assessment in Clinical Trials criteria for a comprehensive assessment of physical function and following evidence-based models to maximize feasibility before formal efficacy testing.

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Accuracy and precision of three consumer-grade motion sensors during overground and treadmill walking in people with parkinson disease: Cross-sectional comparative study (2020)

JMIR Rehabilitation and Assistive Technologies

Authors: Lai, Byron; Sasaki, Jeffer E.; Jeng, Brenda; Cederberg, Katie L.; Bamman, Marcas M.; Motl, Robert W.

Abstract

Background: Wearable motion sensors are gaining popularity for monitoring free-living physical activity among people with Parkinson disease (PD), but more evidence supporting the accuracy and precision of motion sensors for capturing step counts is required in people with PD. Objective: This study aimed to examine the accuracy and precision of 3 common consumer-grade motion sensors for measuring actual steps taken during prolonged periods of overground and treadmill walking in people with PD. Methods: A total of 31 ambulatory participants with PD underwent 6-min bouts of overground and treadmill walking at a comfortable speed. Participants wore 3 devices (Garmin Vivosmart 3, Fitbit One, and Fitbit Charge 2 HR), and a single researcher manually counted the actual steps taken. Accuracy and precision were based on absolute and relative metrics, including intraclass correlation coefficients (ICCs) and Bland-Altman plots. Results: Participants walked 628 steps over ground based on manual counting, and Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR devices had absolute (relative) error values of 6 (6/628, 1.0{\%}), 8 (8/628, 1.3{\%}), and 30 (30/628, 4.8{\%}) steps, respectively. ICC values demonstrated excellent agreement between manually counted steps and steps counted by both Garmin Vivosmart (0.97) and Fitbit One (0.98) but poor agreement for Fitbit Charge 2 HR (0.47). The absolute (relative) precision values for Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR were 11.1 (11.1/625, 1.8{\%}), 14.7 (14.7/620, 2.4{\%}), and 74.4 (74.4/598, 12.4{\%}) steps, respectively. ICC confidence intervals demonstrated low variability for Garmin Vivosmart (0.96 to 0.99) and Fitbit One (0.93 to 0.99) but high variability for Fitbit Charge 2 HR (–0.57 to 0.74). The Fitbit One device maintained high accuracy and precision values for treadmill walking, but both Garmin Vivosmart and Fitbit Charge 2 HR (the wrist-worn devices) had worse accuracy and precision for treadmill walking. Conclusions: The waist-worn sensor (Fitbit One) was accurate and precise in measuring steps with overground and treadmill walking. The wrist-worn sensors were accurate and precise only during overground walking. Similar research should inform the application of these devices in clinical research and practice involving patients with PD.

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Comparison of Physical Activity Measures Derived From the Fitbit Flex and the ActiGraph GT3X+ in an Employee Population With Chronic Knee Symptoms (2020)

ACR Open Rheumatology

Authors: Semanik, Pamela; Lee, Jungwha; Pellegrini, Christine A.; Song, Jing; Dunlop, Dorothy D.; Chang, Rowland W.

Abstract

Background/Purpose: There is increasing public health interest in the objective measurement of free-living physical activity in persons with arthritis, but research grade wearable monitors can be expensive. We therefore sought to examine the accuracy of the affordable personal monitor (Fitbit Flex) by comparing that output with data from the GT3X+ accelerometer (amount of time spent in light, moderate, and vigorous PA) worn simultaneously for 7 days; high accuracy would support substitution with this less expensive personal activity monitor in future arthritis research. Methods: Subjects (n=35) with chronic knee symptoms were recruited for a pilot intervention study using Fitbits to increase physical activity in employees with chronic knee symptoms at an urban insurance corporation. Subjects simultaneously wore for 7 days a Fitbit Flex (wrist-worn)and ActiGraph GT3x+ (waist-worn) as part of 12-week postintervention follow-upevaluation. Fitbit Flex data was regularly stored on a research storage service (Fitabase)by participants. Correlation tables were constructed to examine the association between the amount of time spent in activity intensity categories(Light, Moderate, Vigorous, and Moderate/Vigorous - the last three categories in bouts of 10 min or more). Due to discrepancy in wear time (Fitbit worn for 24hours/day, ActiGraph unit was not), sedentary minutes were not included for comparison. Comparisons were calculated by matching Fitabase data from calendar days Fitbit was worn with data from valid monitoring days (≥10hours wear time) of the ActiGraph. Results: Participants at baseline were primarily female (69{\%}), Caucasian (57{\%}), with mean age 52 years, BMI 32 kg/m2. Table I provides an overview of the definitions and distinctions of each measured activity intensity level. Table 2 provides the comparison of data from Fitbit Flex and ActiGraph GT3x+, including Spearman correlations, within each of the activity intensity categories. Conclusion: The individual intensity category correlations for the two devices are not strong. However, the bouted Moderate-Vigorous activity categories are moderately well correlated. One potential confounder includes the wrist vs waist location of the monitoring device during data collection. This moderate correlation of moderate/vigorous intensity between devices is reassuring to consumers/researchers using the Fitbit to track bouted higher intensity activities, but may not support substitution of the ActiGraph with the Fitbit in population studies that seek to accurately measure all levels of activity and sedentary time.

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Estimating physical activity and sedentary behaviour in a free-living environment: A comparative study between Fitbit Charge 2 and Actigraph GT3X (2020)

PLOS ONE

Authors: Mikkelsen, Marie-Louise K.; Berg-Beckhoff, Gabriele; Frederiksen, Peder; Horgan, Graham; O'Driscoll, Ruairi; Palmeira, Ant{\'{o}}nio L.; Scott, Sarah E.; Stubbs, James; Heitmann, Berit L.; Larsen, Sofus C.

Abstract

Background Activity trackers such as the Fitbit Charge 2 enable users and researchers to monitor physical activity in daily life, which could be beneficial for changing behaviour. However, the accuracy of the Fitbit Charge 2 in a free-living environment is largely unknown. Objective To investigate the agreement between Fitbit Charge 2 and ActiGraph GT3X for the estimation of steps, energy expenditure, time in sedentary behaviour, and light and moderate-to-vigorous physical activity under free-living conditions, and further examine to what extent placing the ActiGraph on the wrist as opposed to the hip would affect the findings. Methods 41 adults (n = 10 males, n = 31 females) were asked to wear a Fitbit Charge 2 device and two ActiGraph GT3X devices (one on the hip and one on the wrist) for seven consecutive days and fill out a log of wear times. Agreement was assessed through Bland-Altman plots combined with multilevel analysis. Results The Fitbit measured 1,492 steps/day more than the hip-worn ActiGraph (limits of agreement [LoA] = -2,250; 5,234), while for sedentary time, it measured 25 min/day less (LoA = -137; 87). Both Bland-Altman plots showed fixed bias. For time in light physical activity, the Fitbit measured 59 min/day more (LoA = -52;169). For time in moderate-to-vigorous physical activity, the Fitbit measured 31 min/day less (LoA = -132; 71) and for activity energy expenditure it measured 408 kcal/day more than the hip-worn ActiGraph (LoA = -385; 1,200). For the two latter outputs, the plots indicated proportional bias. Similar or more pronounced discrepancies, mostly in opposite direction, appeared when comparing to the wrist-worn ActiGraph. Conclusion Moderate to substantial differences between devices were found for most outputs, which could be due to differences in algorithms. Caution should be taken if replacing one device with another and when comparing results.

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Fitbit\textregistered-derived evidence of enhanced mobility of patients with knee osteoarthritis treated with triamcinolone acetonide extended release: Results from a phase 3B, single-ARM, open-label study (2020)

Osteoarthritis and Cartilage

Authors: Huffman, K. M.; Spitzer, A.; Richmond, J. C.; Gomoll, A.; Kraus, V. B.; Jones, D. G.; Concoff, A.; Cinar, A.; Kelley, S.

Abstract

Purpose: Repeated treatment with intra-articular corticosteroid is often used to manage recurrent osteoarthritis (OA) symptoms. Triamcinolone acetonide extended-release (TA-ER) is an intra-articular injection approved for the treatment of pain in patients with knee OA. We conducted a Phase 3b, single-arm, open-label study and assessed safety and exploratory efficacy endpoints in patients with knee OA treated with repeat administration of TA-ER (NCT03046446). This analysis assessed the clinical benefit of treatment based on patient mobility defined as numbers of steps per day. Method(s): Enrolled patients were aged {\textgreater}=40 years with symptomatic knee OA for {\textgreater}=6 months, ACR clinical and radiological diagnosis, Kellgren-Lawrence Grade 2-4, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain total sum score {\textgreater}=6, and index-knee pain for {\textgreater}15 days during the past month. Patients received the 1st injection of TA-ER on Day 1 and the 2nd injection at either Week 12, 16, 20, or 24. This analysis collected patient mobility data within the 1st injection period only. Patient movements were analyzed with a measured function device [Fitbit] that was worn beginning at least 7 days prior to Day 1 and continuing to the end of Week 12. Weekly average step values were recorded if 3 out of 7 daily values were obtained with a lower threshold of 1000 steps per day. Exploratory efficacy endpoints included WOMAC A (pain) assessed every 4 weeks. A mixed effects model was generated to assess an outcome of change from baseline in steps per day using data from Weeks 4, 8, and 12. The primary independent variable of interest was change from baseline in WOMAC-A average pain scale. Other covariates examined were age, sex, baseline body mass index (BMI), region, month of the start of trial (categorical), visit (continuous, indicating time in weeks from receiving 1st injection), baseline global physical activity questionnaire (GPAQ) values (average MET-minutes of moderate or vigorous physical activity per day), baseline steps per day, and baseline average pain scale. Result(s): 208 patients were enrolled, most patients were female (55.8{\%}), and 67.8{\%} had radiographic OA severity of Kellgren-Lawrence Grade 3 or 4 at baseline. Mean age was 60.8 years and mean BMI was 31.4 kg/m2. The baseline mean WOMAC pain score was 2.17. Patients treated with TA-ER exhibited an immediate improvement in mobility as shown by increases in weekly mean steps per day (Figure 1) and mean change from baseline in weekly mean steps per day (Figure 2). Treatment with TA-ER was effective with mean changes from baseline in WOMAC-A scores of -1.4, -1.2, and -0.8 at Weeks 4, 8, and 12, respectively. A statistically significant greater change in step count from baseline was observed in association with larger decreases in WOMAC pain scores, male gender, lower BMI, lower baseline GPAQ average MET, and lower baseline steps per day. For every 1-unit decrease (from baseline) in mean WOMAC pain scale, the mean step count per day increased by 339 steps (95{\%} confidence limits, 58 and 620 steps) (Figure 3). [Formula presented] [Formula presented] [Formula presented] Conclusion(s): Patients with knee OA treated with TA-ER exhibited a decrease in pain and increased mobility as measured by their Fitbit. Limitations to this study include incomplete patient adherence to usage of the Fitbit device and that this was an open-label study with no control arm for comparison. Furthermore, it is unclear why the patient population had a relatively high mean number of steps per day at baseline. This study shows the feasibility of using personal fitness monitors to assess the effectiveness of treatments for OA. Sponsor: This study was funded by Flexion Therapeutics (Burlington, MA, USA).Copyright {\textcopyright} 2020

Fitbit-Based Interventions for Healthy Lifestyle Outcomes: Systematic Review and Meta-Analysis (2020)

Journal of Medical Internet Research

Authors: Ringeval, Mickael; Wagner, Gerit; Denford, James; Par{\'{e}}, Guy; Kitsiou, Spyros

Abstract

Background: Unhealthy behaviors, such as physical inactivity, sedentary lifestyle, and unhealthful eating, remain highly prevalent, posing formidable challenges in efforts to improve cardiovascular health. While traditional interventions to promote healthy lifestyles are both costly and effective, wearable trackers, especially Fitbit devices, can provide a low-cost alternative that may effectively help large numbers of individuals become more physically fit and thereby maintain a good health status. Objective: The objectives of this meta-analysis are (1) to assess the effectiveness of interventions that incorporate a Fitbit device for healthy lifestyle outcomes (eg, steps, moderate-to-vigorous physical activity, and weight) and (2) to identify which additional intervention components or study characteristics are the most effective at improving healthy lifestyle outcomes. Methods: A systematic review was conducted, searching the following databases from 2007 to 2019: MEDLINE, EMBASE, CINAHL, and CENTRAL (Cochrane). Studies were included if (1) they were randomized controlled trials, (2) the intervention involved the use of a Fitbit device, and (3) the reported outcomes were related to healthy lifestyles. The main outcome measures were related to physical activity, sedentary behavior, and weight. All the studies were assessed for risk of bias using Cochrane criteria. A random-effects meta-analysis was conducted to estimate the treatment effect of interventions that included a Fitbit device compared with a control group. We also conducted subgroup analysis and fuzzy-set qualitative comparative analysis (fsQCA) to further disentangle the effects of intervention components. Results: Our final sample comprised 41 articles reporting the results of 37 studies. For Fitbit-based interventions, we found a statistically significant increase in daily step count (mean difference [MD] 950.54, 95{\%} CI 475.89-1425.18; P{\textless}.001) and moderate-to-vigorous physical activity (MD 6.16, 95{\%} CI 2.80-9.51; P{\textless}.001), a significant decrease in weight (MD −1.48, 95{\%} CI −2.81 to −0.14; P=.03), and a nonsignificant decrease in objectively assessed and self-reported sedentary behavior (MD −10.62, 95{\%} CI −35.50 to 14.27; P=.40 and standardized MD −0.11, 95{\%} CI −0.48 to 0.26; P=.56, respectively). In general, the included studies were at low risk for bias, except for performance bias. Subgroup analysis and fsQCA demonstrated that, in addition to the effects of the Fitbit devices, setting activity goals was the most important intervention component. Conclusions: The use of Fitbit devices in interventions has the potential to promote healthy lifestyles in terms of physical activity and weight. Fitbit devices may be useful to health professionals for patient monitoring and support.

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Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study (2020)

The Lancet Digital Health

Authors: Radin, Jennifer M.; Wineinger, Nathan E.; Topol, Eric J.; Steinhubl, Steven R.

Abstract

Background: Acute infections can cause an individual to have an elevated resting heart rate (RHR) and change their routine daily activities due to the physiological response to the inflammatory insult. Consequently, we aimed to evaluate if population trends of seasonal respiratory infections, such as influenza, could be identified through wearable sensors that collect RHR and sleep data. Methods: We obtained de-identified sensor data from 200 000 individuals who used a Fitbit wearable device from March 1, 2016, to March 1, 2018, in the USA. We included users who wore a Fitbit for at least 60 days and used the same wearable throughout the entire period, and focused on the top five states with the most Fitbit users in the dataset: California, Texas, New York, Illinois, and Pennsylvania. Inclusion criteria included having a self-reported birth year between 1930 and 2004, height greater than 1 m, and weight greater than 20 kg. We excluded daily measurements with missing RHR, missing wear time, and wear time less than 1000 min per day. We compared sensor data with weekly estimates of influenza-like illness (ILI) rates at the state level, as reported by the US Centers for Disease Control and Prevention (CDC), by identifying weeks in which Fitbit users displayed elevated RHRs and increased sleep levels. For each state, we modelled ILI case counts with a negative binomial model that included 3-week lagged CDC ILI rate data (null model) and the proportion of weekly Fitbit users with elevated RHR and increased sleep duration above a specified threshold (full model). We also evaluated weekly change in ILI rate by linear regression using change in proportion of elevated Fitbit data. Pearson correlation was used to compare predicted versus CDC reported ILI rates. Findings: We identified 47 249 users in the top five states who wore a Fitbit consistently during the study period, including more than 13{\textperiodcentered}3 million total RHR and sleep measures. We found the Fitbit data significantly improved ILI predictions in all five states, with an average increase in Pearson correlation of 0{\textperiodcentered}12 (SD 0{\textperiodcentered}07) over baseline models, corresponding to an improvement of 6{\textperiodcentered}3–32{\textperiodcentered}9{\%}. Correlations of the final models with the CDC ILI rates ranged from 0{\textperiodcentered}84 to 0{\textperiodcentered}97. Week-to-week changes in the proportion of Fitbit users with abnormal data were associated with week-to-week changes in ILI rates in most cases. Interpretation: Activity and physiological trackers are increasingly used in the USA and globally to monitor individual health. By accessing these data, it could be possible to improve real-time and geographically refined influenza surveillance. This information could be vital to enact timely outbreak response measures to prevent further transmission of influenza cases during outbreaks. Funding: Partly supported by the US National Institutes of Health National Center for Advancing Translational Sciences.

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Minimal Detectable Change Thresholds and Responsiveness of Zephyr Bioharness and Fitbit Charge Devices (2020)

Journal of Strength and Conditioning Research

Authors: Nazari, Goris; MacDermid, Joy C.

Abstract

Nazari, G and MacDermid, JC. Minimal detectable change thresholds and responsiveness of zephyr bioharness and Fitbit Charge devices. J Strength Cond Res 34(1): 257-263, 2020-The aim of the current study was to define the minimal detectable change (MDC) thresholds for Zephyr Bioharness (ZB) and Fitbit Charge Heart Rate (FC-HR) variables and to establish the internal responsiveness of ZB and FC-HR devices in terms of their HR, respiratory rate variables, and number of steps taken variables, in a healthy sample of men and women at resting, submaximal activity and throughout recovery phases. A total of sixty participants (30 women, 48 ± 15) and (30 men, 48 ± 15) were recruited using stratified convenience and snowball sampling approaches from our university student, staff, and faculty population. At rest, MDC90 values of ±4.89 and ±5.15 were noted for ZB and FC-HR devices, respectively. Throughout the recovery, thresholds of ±8.14 for ZB and 8.74 for FC-HR were reported. During the submaximal phases, scores of ±8.18 and ±9.35 were established for ZB and FC-HR, respectively. From a resting to a submaximal state, the standardized response means (SRMs) for ZB and FC-HR variables exhibited large responsiveness of SRMZB-HR = 4.42; SRMFC-HR = 4.04. In addition, the ZB respiratory rate variable showed the largest effect size of SRMZB-RR = 2.55. Similarly, the large effect size of SRMFC-ST = 1.76 was reported for the FC-HR steps taken variable. From a submaximal to a recovery state, the SRMs for ZB and FC-HR variables demonstrated effect sizes of SRMZB-HR = -3.10; SRMFC-HR = -3.12. Furthermore, the ZB respiratory rate variable displayed similar internal responsiveness measures of SRMZB-RR = -2.45. To conclude, Similar MDC HR thresholds can be expected using the ZB and FC-HR devices and that the two devices demonstrated large internal responsiveness in our healthy male and female cohort when transitioning from resting to submaximal states and vice-versa. Our findings suggest that the ZB and FC-HR devices can be used in monitoring performance improvements or deterioration over time and would allow qualified personnel in assessing the effectiveness of exercise programs in healthy individuals.

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Performance assessment of new-generation Fitbit technology in deriving sleep parameters and stages (2020)

Chronobiology International

Authors: Haghayegh, Shahab; Khoshnevis, Sepideh; Smolensky, Michael H.; Diller, Kenneth R.; Castriotta, Richard J.

Abstract

We compared performance in deriving sleep variables by both Fitbit Charge 2™, which couples body movement (accelerometry) and heart rate variability (HRV) in combination with its proprietary interpretative algorithm (IA), and standard actigraphy (Motionlogger{\textregistered} Micro Watch Actigraph: MMWA), which relies solely on accelerometry in combination with its best performing ‘Sadeh' IA, to electroencephalography (EEG: Zmachine{\textregistered} Insight+ and its proprietary IA) used as reference. We conducted home sleep studies on 35 healthy adults, 33 of whom provided complete datasets of the three simultaneously assessed technologies. Relative to the Zmachine EEG method, Fitbit showed an overall Kappa agreement of 54{\%} in distinguishing wake/sleep epochs and sensitivity of 95{\%} and specificity of 57{\%} in detecting sleep epochs. Fitbit, relative to EEG, underestimated sleep onset latency (SOL) by {\~{}}11 min and overestimated sleep efficiency (SE) by {\~{}}4{\%}. There was no statistically significant difference between Fitbit and EEG methods in measuring wake after sleep onset (WASO) and total sleep time (TST). Fitbit showed substantial agreement with EEG in detecting rapid eye movement and deep sleep, but only moderate agreement in detecting light sleep. The MMWA method showed 51{\%} overall Kappa agreement with the EEG one in detecting wake/sleep epochs, with sensitivity of 94{\%} and specificity of 53{\%} in detecting sleep epochs. MMWA, relative to EEG, underestimated SOL by {\~{}}10 min. There was no significant difference between Fitbit and MMWA methods in amount of bias in estimating SOL, WASO, TST, and SE; however, the minimum detectable change (MDC) per sleep variable with Fitbit was better (smaller) than with MMWA, respectively, by {\~{}}10 min, {\~{}}16 min, {\~{}}22 min, and {\~{}}8{\%}. Overall, performance of Fitbit accelerometry and HRV technology in conjunction with its proprietary IA to detect sleep vs. wake episodes is slightly better than wrist actigraphy that relies solely on accelerometry and best performing Sadeh IA. Moreover, the smaller MDC of Fitbit technology in deriving sleep parameters in comparison to wrist actigraphy makes it a suitable option for assessing changes in sleep quality over time, longitudinally, and/or in response to interventions.

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The Physical Activity Wearables in the Police Force (PAW-Force) study: acceptability and impact (2020)

BMC Public Health

Authors: Buckingham, Sarah Ann; Morrissey, Karyn; Williams, Andrew James; Price, Lisa; Harrison, John

Abstract

Background: Policing is a highly stressful and increasingly sedentary occupation. The study aim was to assess the acceptability and impact of a mobile health (mHealth) technology intervention (Fitbit{\textregistered} activity monitor and ‘Bupa Boost' smartphone app) to promote physical activity (PA) and reduce sedentary time in the police force. Methods: Single-group, pre-post, mixed methods pilot study. Police officers and staff (n = 180) were recruited from two police forces in South West England. Participants used the technology for 12 weeks (an ‘individual' then ‘social' phase) followed by 5 months of optional use. Data sources included Fitbit{\textregistered}-recorded objective step count, questionnaire surveys and semi-structured interviews (n = 32). Outcome assessment points were baseline (week 0), mid-intervention (week 6), post-intervention (week 12) and follow-up (month 8). Paired t-tests were used to investigate changes in quantitative outcomes. Qualitative analysis involved framework and thematic analysis. Results: Changes in mean daily step count were non-significant (p {\textgreater} 0.05), but self-reported PA increased in the short term (e.g. + 465.4 MET-minutes/week total PA baseline to week 12, p = 0.011) and longer term (e.g. + 420.5 MET-minutes/week moderate-to-vigorous PA baseline to month 8, p = 0.024). The greatest impact on behaviour was perceived by less active officers and staff. There were no significant changes in sedentary time; the qualitative findings highlighted the importance of context and external influences on behaviour. There were no statistically significant changes (all p-values {\textgreater} 0.05) in any secondary outcomes (physical and mental health-related quality of life, perceived stress and perceived productivity), with the exception of an improvement in mental health-related quality of life (SF-12 mental component score + 1.75 points, p = 0.020) from baseline to month 8. Engagement with and perceived acceptability of the intervention was high overall, but a small number of participants reported negative physical (skin irritation) and psychological (feelings of guilt and anxiety) consequences of technology use. Individual app features (such as goal-setting and self-monitoring) were generally preferred to social components (social comparison, competitions and support). Conclusions: mHealth technology is an acceptable and potentially impactful intervention for increasing PA in the police force. The intervention was less useful for reducing sedentary time and the impact on secondary outcomes is unclear. Trial registration: NCT03169179 (registered 30th May 2017).

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Twitter-Based Social Support Added to Fitbit Self-Monitoring for Decreasing Sedentary Behavior: Protocol for a Randomized Controlled Pilot Trial With Female Patients From a Women's Heart Clinic (2020)

JMIR Research Protocols

Authors: Oppezzo, Marily; Tremmel, Jennifer; Desai, Manisha; Baiocchi, Michael; Ramo, Danielle; Cullen, Mark; Prochaska, Judith J.

Abstract

Background: Prolonged sitting is an independent risk behavior for the development of chronic disease. With most interventions focusing on physical activity and exercise, there is a separate need for investigation into innovative and accessible interventions to decrease sedentary behavior throughout the day. Twitter is a social media platform with application for health communications and fostering of social support for health behavior change. Objective: This pilot study aims to test the feasibility, acceptability, and preliminary efficacy of delivering daily behavior change strategies within private Twitter groups to foster peer-to-peer support and decrease sedentary behavior throughout the day in women. The Twitter group was combined with a Fitbit for self-monitoring activity and compared to a Fitbit-only control group. Methods: In a 2-group design, participants were randomized to a Twitter + Fitbit treatment group or a Fitbit-only control group. Participants were recruited via the Stanford Research Repository System, screened for eligibility, and then invited to an orientation session. After providing informed consent, they were randomized. All participants received 13 weeks of tailored weekly step goals and a Fitbit. The treatment group participants, placed in a private Twitter support group, received daily automated behavior change “tweets” informed by theory and regular automated encouragement via text to communicate with the group. Fitbit data were collected daily throughout the treatment and follow-up period. Web-based surveys and accelerometer data were collected at baseline, treatment end (13 weeks), and at 8.5 weeks after the treatment. Results: The initial study design funding was obtained from the Women's Heart Clinic and the Stanford Clayman Institute. Funding to run this pilot study was received from the National Institutes of Health's National Heart, Lung, and Blood Institute under Award Number K01HL136702. All procedures were approved by Stanford University's Institutional Review Board, {\#}32127 in 2018, prior to beginning data collection. Recruitment for this study was conducted in May 2019. Of the 858 people screened, 113 met the eligibility criteria, 68 came to an information session, and 45 consented to participate in this pilot study. One participant dropped out of the intervention, and complete follow-up data were obtained from 39 of the 45 participants (87{\%} of the sample). Data were collected over 6 months from June to December 2019. Feasibility, acceptability, and preliminary efficacy results are being analyzed and will be reported in the winter of 2021. Conclusions: This pilot study is assessing the feasibility, acceptability, and preliminary efficacy of delivering behavior change strategies in a Twitter social support group to decrease sedentary behavior in women. These findings will inform a larger evaluation. With an accessible, tailorable, and flexible platform, Twitter-delivered interventions offer potential for many treatment variations and titrations, thereby testing the effects of different behavior change strategies, peer-group makeups, and health behaviors of interest.

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Wrist-Worn Wearables for Monitoring Heart Rate and Energy Expenditure While Sitting or Performing Light-to-Vigorous Physical Activity: Validation Study (2020)

JMIR mHealth and uHealth

Authors: Duking Peter; Giessing Laura; Frenkel Marie Ottilie; Koehler Karsten; Holmberg Hans Christer; Sperlich Billy

Abstract

Background: Physical activity reduces the incidences of noncommunicable diseases, obesity, and mortality, but an inactive lifestyle is becoming increasingly common. Innovative approaches to monitor and promote physical activity are warranted. While individual monitoring of physical activity aids in the design of effective interventions to enhance physical activity, a basic prerequisite is that the monitoring devices exhibit high validity. Objective: Our goal was to assess the validity of monitoring heart rate (HR) and energy expenditure (EE) while sitting or performing light-to-vigorous physical activity with 4 popular wrist-worn wearables (Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa). Methods: While wearing the 4 different wearables, 25 individuals performed 5 minutes each of sitting, walking, and running at different velocities (ie, 1.1 m/s, 1.9 m/s, 2.7 m/s, 3.6 m/s, and 4.1 m/s), as well as intermittent sprints. HR and EE were compared to common criterion measures: Polar-H7 chest belt for HR and indirect calorimetry for EE. Results: While monitoring HR at different exercise intensities, the standardized typical errors of the estimates were 0.09-0.62, 0.13-0.88, 0.62-1.24, and 0.47-1.94 for the Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, respectively. Depending on exercise intensity, the corresponding coefficients of variation were 0.9%-4.3%, 2.2%-6.7%, 2.9%-9.2%, and 4.1%-19.1%, respectively, for the 4 wearables. While monitoring EE at different exercise intensities, the standardized typical errors of the estimates were 0.34-1.84, 0.32-1.33, 0.46-4.86, and 0.41-1.65 for the Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, respectively. Depending on exercise intensity, the corresponding coefficients of variation were 13.5%-27.1%, 16.3%-28.0%, 15.9%-34.5%, and 8.0%-32.3%, respectively. Conclusions: The Apple Watch Series 4 provides the highest validity (ie, smallest error rates) when measuring HR while sitting or performing light-to-vigorous physical activity, followed by the Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, in that order. The Apple Watch Series 4 and Polar Vantage V are suitable for valid HR measurements at the intensities tested, but HR data provided by the Garmin Fenix 5 and Fitbit Versa should be interpreted with caution due to higher error rates at certain intensities. None of the 4 wrist-worn wearables should be employed to monitor EE at the intensities and durations tested.

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Accuracy of fitbit wristbands in measuring sleep stage transitions and the effect of user-specific factors (2019)

Journal of Medical Internet Research

Authors: Liang, Zilu; Chapa-Martell, Mario Alberto

Abstract

Background: It has become possible for the new generation of consumer wristbands to classify sleep stages based on multisensory data. Several studies have validated the accuracy of one of the latest models, that is, Fitbit Charge 2, in measuring polysomnographic parameters, including total sleep time, wake time, sleep efficiency (SE), and the ratio of each sleep stage. Nevertheless, its accuracy in measuring sleep stage transitions remains unknown. Objective: This study aimed to examine the accuracy of Fitbit Charge 2 in measuring transition probabilities among wake, light sleep, deep sleep, and rapid eye movement (REM) sleep under free-living conditions. The secondary goal was to investigate the effect of user-specific factors, including demographic information and sleep pattern on measurement accuracy. Methods: A Fitbit Charge 2 and a medical device were used concurrently to measure a whole night's sleep in participants' homes. Sleep stage transition probabilities were derived from sleep hypnograms. Measurement errors were obtained by comparing the data obtained by Fitbit with those obtained by the medical device. Paired 2-tailed t test and Bland-Altman plots were used to examine the agreement of Fitbit to the medical device. Wilcoxon signed-rank test was performed to investigate the effect of user-specific factors. Results: Sleep data were collected from 23 participants. Sleep stage transition probabilities measured by Fitbit Charge 2 significantly deviated from those measured by the medical device, except for the transition probability from deep sleep to wake, from light sleep to REM sleep, and the probability of staying in REM sleep. Bland-Altman plots demonstrated that systematic bias ranged from 0{\%} to 60{\%}. Fitbit had the tendency of overestimating the probability of staying in a sleep stage while underestimating the probability of transiting to another stage. SE{\textgreater}90{\%} (P=.047) was associated with significant increase in measurement error. Pittsburgh sleep quality index (PSQI){\textless}5 and wake after sleep onset (WASO){\textless}30 min could be associated to significantly decreased or increased errors, depending on the outcome sleep metrics. Conclusions: Our analysis shows that Fitbit Charge 2 underestimated sleep stage transition dynamics compared with the medical device. Device accuracy may be significantly affected by perceived sleep quality (PSQI), WASO, and SE.

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Accuracy of wristband fitbit models in assessing sleep: Systematic review and meta-analysis (2019)

Journal of Medical Internet Research

Authors: Haghayegh, Shahab; Khoshnevis, Sepideh; Smolensky, Michael H.; Diller, Kenneth R.; Castriotta, Richard J.

Abstract

Background: Wearable sleep monitors are of high interest to consumers and researchers because of their ability to provide estimation of sleep patterns in free-living conditions in a cost-efficient way. Objective: We conducted a systematic review of publications reporting on the performance of wristband Fitbit models in assessing sleep parameters and stages. Methods: In adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we comprehensively searched the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane, Embase, MEDLINE, PubMed, PsycINFO, and Web of Science databases using the keyword Fitbit to identify relevant publications meeting predefined inclusion and exclusion criteria. Results: The search yielded 3085 candidate articles. After eliminating duplicates and in compliance with inclusion and exclusion criteria, 22 articles qualified for systematic review, with 8 providing quantitative data for meta-analysis. In reference to polysomnography (PSG), nonsleep-staging Fitbit models tended to overestimate total sleep time (TST; range from approximately 7 to 67 mins; effect size=-0.51, P{\textless}.001; heterogenicity: I2=8.8{\%}, P=.36) and sleep efficiency (SE; range from approximately 2{\%} to 15{\%}; effect size=-0.74, P{\textless}.001; heterogenicity: I2=24.0{\%}, P=.25), and underestimate wake after sleep onset (WASO; range from approximately 6 to 44 mins; effect size=0.60, P{\textless}.001; heterogenicity: I2=0{\%}, P=.92) and there was no significant difference in sleep onset latency (SOL; P=.37; heterogenicity: I2=0{\%}, P=.92). In reference to PSG, nonsleep-staging Fitbit models correctly identified sleep epochs with accuracy values between 0.81 and 0.91, sensitivity values between 0.87 and 0.99, and specificity values between 0.10 and 0.52. Recent-generation Fitbit models that collectively utilize heart rate variability and body movement to assess sleep stages performed better than early-generation nonsleep-staging ones that utilize only body movement. Sleep-staging Fitbit models, in comparison to PSG, showed no significant difference in measured values of WASO (P=.25; heterogenicity: I2=0{\%}, P=.92), TST (P=.29; heterogenicity: I2=0{\%}, P=.98), and SE (P=.19) but they underestimated SOL (P=.03; heterogenicity: I2=0{\%}, P=.66). Sleep-staging Fitbit models showed higher sensitivity (0.95-0.96) and specificity (0.58-0.69) values in detecting sleep epochs than nonsleep-staging models and those reported in the literature for regular wrist actigraphy. Conclusions: Sleep-staging Fitbit models showed promising performance, especially in differentiating wake from sleep. However, although these models are a convenient and economical means for consumers to obtain gross estimates of sleep parameters and time spent in sleep stages, they are of limited specificity and are not a substitute for PSG.

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Concurrent validity of the Fitbit for assessing sedentary behavior and moderate-to-vigorous physical activity (2019)

BMC Medical Research Methodology

Authors: Redenius, Nicklaus; Kim, Youngwon; Byun, Wonwoo

Abstract

Background: Recent advances in sensor technologies have promoted the use of consumer-based accelerometers such as Fitbit Flex in epidemiological and clinical research; however, the validity of the Fitbit Flex in measuring sedentary behavior (SED) and physical activity (PA) has not been fully determined against previously validated research-grade accelerometers such as ActiGraph GT3X+. Therefore, the purpose of this study was to examine the concurrent validity of the Fitbit Flex against ActiGraph GT3X+ in a free-living condition. Methods: A total of 65 participants (age: M = 42, SD = 14 years, female: 72{\%}) each wore a Fitbit Flex and GT3X+ for seven consecutive days. After excluding sleep and non-wear time, time spent (min/day) in SED and moderate-to-vigorous PA (MVPA) were estimated using various cut-points for GT3X+ and brand-specific algorithms for Fitbit, respectively. Repeated measures one-way ANOVA and mean absolute percent errors (MAPE) served to examine differences and measurement errors in SED and MVPA estimates between Fitbit Flex and GT3X+, respectively. Pearson and Spearman correlations and Bland-Altman (BA) plots were used to evaluate the association and potential systematic bias between Fitbit Flex and GT3X+. PROC MIXED procedure in SAS was used to examine the equivalence (i.e., the 90{\%} confidence interval with ±10{\%} equivalence zone) between the devices. Results: Fitbit Flex produced similar SED and low MAPE (mean difference [MD] = 37 min/day, P =.21, MAPE = 6.8{\%}), but significantly higher MVPA and relatively large MAPE (MD = 59-77 min/day, P {\textless}.0001, MAPE = 56.6-74.3{\%}) compared with the estimates from GT3X+ using three different cut-points. The correlations between Fitbit Flex and GT3X+ were consistently higher for SED (r = 0.90, $\rho$ = 0.86, P {\textless}.01), but weaker for MVPA (r = 0.65-0.76, $\rho$ = 0.69-0.79, P {\textless}.01). BA plots revealed that there is no apparent bias in estimating SED. Conclusion: In comparison with the GT3X+ accelerometer, the Fitbit Flex provided comparatively accurate estimates of SED, but the Fitbit Flex overestimated MVPA under free-living conditions. Future investigations using the Fitbit Flex should be aware of present findings.

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Goal-directed versus outcome-based financial incentives for weight loss among low-income patients with obesity: Rationale and design of the Financial Incentives for Weight Reduction (FIReWoRk) randomised controlled trial (2019)

BMJ Open

Authors: Jay, Melanie; Orstad, Stephanie L.; Wali, Soma; Wylie-Rosett, Judith; Tseng, Chi Hong; Sweat, Victoria; Wittleder, Sandra; Shu, Suzanne B.; Goldstein, Noah J.; Ladapo, Joseph A.

Abstract

Introduction Obesity is a major public health challenge and exacerbates economic disparities through employment discrimination and increased personal health expenditures. Financial incentives for weight management may intensify individuals' utilisation of evidence-based behavioural strategies while addressing obesity-related economic disparities in low-income populations. Trials have focused on testing incentives contingent on achieving weight loss outcomes. However, based on social cognitive and self-determination theories, providing incentives for achieving intermediate behavioural goals may be more sustainable than incentivising outcomes if they enhance an individual's skills and self-efficacy for maintaining long-Term weight loss. The objective of this paper is to describe the rationale and design of the Financial Incentives foR Weight Reduction study, a randomised controlled trial to test the comparative effectiveness and cost-effectiveness of two financial incentive strategies for weight loss (goal directed vs outcome based) among low-income adults with obesity, as well as compared with the provision of health behaviour change resources alone. Methods and analysis We are recruiting 795 adults, aged 18-70 years with a body mass index ≥30 kg/m 2, from three primary care clinics serving residents of socioeconomically disadvantaged neighbourhoods in New York City and Los Angeles. All participants receive a 1-year commercial weight loss programme membership, self-monitoring tools (bathroom scale, food journal and Fitbit Alta HR), health education and monthly check-in visits. In addition to these resources, those in the two intervention groups can earn up to 750 over 6 months for: (1) participating in an intensive weight management programme, self-monitoring weight and diet and meeting physical activity guidelines (goal-directed arm); or (2) a ≥1.5{\%} to ≥5{\%} reduction in baseline weight (outcome-based arm). To maximise incentive efficacy, we incorporate concepts from behavioural economics, including immediacy of payments and framing feedback to elicit regret aversion. We will use generalised mixed effect models for repeated measures to examine intervention effects on weight at 6, 9 and 12 months. Ethics and dissemination Human research protection committees at New York University School of Medicine, University of California Los Angeles (UCLA) David Geffen School of Medicine and Olive-View-UCLA Medical Center granted ethics approval. We will disseminate the results of this research via peer-reviewed publications, conference presentations and meetings with stakeholders. Trial registration number NCT03157713.

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Identifying behavioral phenotypes of loneliness and social isolation with passive sensing: Statistical analysis, data mining and machine learning of smartphone and fitbit data (2019)

JMIR mHealth and uHealth

Authors: Doryab, Afsaneh; Villalba, Daniella K.; Chikersal, Prerna; Dutcher, Janine M.; Tumminia, Michael; Liu, Xinwen; Cohen, Sheldon; Creswell, Kasey; Mankoff, Jennifer; Creswell, John D.; Dey, Anind K.

Abstract

Background: Feelings of loneliness are associated with poor physical and mental health. Detection of loneliness through passive sensing on personal devices can lead to the development of interventions aimed at decreasing rates of loneliness. Objective: The aim of this study was to explore the potential of using passive sensing to infer levels of loneliness and to identify the corresponding behavioral patterns. Methods: Data were collected from smartphones and Fitbits (Flex 2) of 160 college students over a semester. The participants completed the University of California, Los Angeles (UCLA) loneliness questionnaire at the beginning and end of the semester. For a classification purpose, the scores were categorized into high (questionnaire score{\textgreater}40) and low (≤40) levels of loneliness. Daily features were extracted from both devices to capture activity and mobility, communication and phone usage, and sleep behaviors. The features were then averaged to generate semester-level features. We used 3 analytic methods: (1) statistical analysis to provide an overview of loneliness in college students, (2) data mining using the Apriori algorithm to extract behavior patterns associated with loneliness, and (3) machine learning classification to infer the level of loneliness and the change in levels of loneliness using an ensemble of gradient boosting and logistic regression algorithms with feature selection in a leave-one-student-out cross-validation manner. Results: The average loneliness score from the presurveys and postsurveys was above 43 (presurvey SD 9.4 and postsurvey SD 10.4), and the majority of participants fell into the high loneliness category (scores above 40) with 63.8{\%} (102/160) in the presurvey and 58.8{\%} (94/160) in the postsurvey. Scores greater than 1 standard deviation above the mean were observed in 12.5{\%} (20/160) of the participants in both pre- and postsurvey scores. The majority of scores, however, fell between 1 standard deviation below and above the mean (pre=66.9{\%} [107/160] and post=73.1{\%} [117/160]). Our machine learning pipeline achieved an accuracy of 80.2{\%} in detecting the binary level of loneliness and an 88.4{\%} accuracy in detecting change in the loneliness level. The mining of associations between classifier-selected behavioral features and loneliness indicated that compared with students with low loneliness, students with high levels of loneliness were spending less time outside of campus during evening hours on weekends and spending less time in places for social events in the evening on weekdays (support=17{\%} and confidence=92{\%}). The analysis also indicated that more activity and less sedentary behavior, especially in the evening, was associated with a decrease in levels of loneliness from the beginning of the semester to the end of it (support=31{\%} and confidence=92{\%}). Conclusions: Passive sensing has the potential for detecting loneliness in college students and identifying the associated behavioral patterns. These findings highlight intervention opportunities through mobile technology to reduce the impact of loneliness on individuals' health and well-being.

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Validity Evaluation of the Fitbit Charge2 and the Garmin vivosmart HR+ in Free-Living Environments in an Older Adult Cohort (2019)

JMIR mHealth and uHealth

Authors: Tedesco, S.; Sica, M.; Ancillao, A.; Timmons, S.; Barton, J.; O'Flynn, B.

Abstract

Background: Few studies have investigated the validity of mainstream wrist-based activity trackers in healthy older adults in real life, as opposed to laboratory settings. Objective: This study explored the performance of two wrist-worn trackers (Fitbit Charge 2 and Garmin vivosmart HR+) in estimating steps, energy expenditure, moderate-to-vigorous physical activity (MVPA) levels, and sleep parameters (total sleep time [TST] and wake after sleep onset [WASO]) against gold-standard technologies in a cohort of healthy older adults in a free-living environment. Methods: Overall, 20 participants (>65 years) took part in the study. The devices were worn by the participants for 24 hours, and the results were compared against validated technology (ActiGraph and New-Lifestyles NL-2000i). Mean error, mean percentage error (MPE), mean absolute percentage error (MAPE), intraclass correlation (ICC), and Bland-Altman plots were computed for all the parameters considered. Results: For step counting, all trackers were highly correlated with one another (ICCs>0.89). Although the Fitbit tended to overcount steps (MPE=12.36%), the Garmin and ActiGraph undercounted (MPE 9.36% and 11.53%, respectively). The Garmin had poor ICC values when energy expenditure was compared against the criterion. The Fitbit had moderate-to-good ICCs in comparison to the other activity trackers, and showed the best results (MAPE=12.25%), although it underestimated calories burned. For MVPA levels estimation, the wristband trackers were highly correlated (ICC=0.96); however, they were moderately correlated against the criterion and they overestimated MVPA activity minutes. For the sleep parameters, the ICCs were poor for all cases, except when comparing the Fitbit with the criterion, which showed moderate agreement. The TST was slightly overestimated with the Fitbit, although it provided good results with an average MAPE equal to 10.13%. Conversely, WASO estimation was poorer and was overestimated by the Fitbit but underestimated by the Garmin. Again, the Fitbit was the most accurate, with an average MAPE of 49.7%. Conclusions: The tested well-known devices could be adopted to estimate steps, energy expenditure, and sleep duration with an acceptable level of accuracy in the population of interest, although clinicians should be cautious in considering other parameters for clinical and research purposes.

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Validity Evaluation of the Fitbit Charge2 and the Garmin vivosmart HR+ in Free-Living Environments in an Older Adult Cohort. (2019)

JMIR mHealth and uHealth

Authors: Tedesco, Salvatore; Sica, Marco; Ancillao, Andrea; Timmons, Suzanne; Barton, John; O'Flynn, Brendan

Abstract

BACKGROUND Few studies have investigated the validity of mainstream wrist-based activity trackers in healthy older adults in real life, as opposed to laboratory settings. OBJECTIVE This study explored the performance of two wrist-worn trackers (Fitbit Charge 2 and Garmin vivosmart HR+) in estimating steps, energy expenditure, moderate-to-vigorous physical activity (MVPA) levels, and sleep parameters (total sleep time [TST] and wake after sleep onset [WASO]) against gold-standard technologies in a cohort of healthy older adults in a free-living environment. METHODS Overall, 20 participants ({\textgreater}65 years) took part in the study. The devices were worn by the participants for 24 hours, and the results were compared against validated technology (ActiGraph and New-Lifestyles NL-2000i). Mean error, mean percentage error (MPE), mean absolute percentage error (MAPE), intraclass correlation (ICC), and Bland-Altman plots were computed for all the parameters considered. RESULTS For step counting, all trackers were highly correlated with one another (ICCs{\textgreater}0.89). Although the Fitbit tended to overcount steps (MPE=12.36{\%}), the Garmin and ActiGraph undercounted (MPE 9.36{\%} and 11.53{\%}, respectively). The Garmin had poor ICC values when energy expenditure was compared against the criterion. The Fitbit had moderate-to-good ICCs in comparison to the other activity trackers, and showed the best results (MAPE=12.25{\%}), although it underestimated calories burned. For MVPA levels estimation, the wristband trackers were highly correlated (ICC=0.96); however, they were moderately correlated against the criterion and they overestimated MVPA activity minutes. For the sleep parameters, the ICCs were poor for all cases, except when comparing the Fitbit with the criterion, which showed moderate agreement. The TST was slightly overestimated with the Fitbit, although it provided good results with an average MAPE equal to 10.13{\%}. Conversely, WASO estimation was poorer and was overestimated by the Fitbit but underestimated by the Garmin. Again, the Fitbit was the most accurate, with an average MAPE of 49.7{\%}. CONCLUSIONS The tested well-known devices could be adopted to estimate steps, energy expenditure, and sleep duration with an acceptable level of accuracy in the population of interest, although clinicians should be cautious in considering other parameters for clinical and research purposes.

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A Latino Patient-Centered, Evidence-Based Approach to Diabetes Prevention. (2018)

Journal of the American Board of Family Medicine : JABFM

Authors: Rosas, L.G., Lv, N., Lewis, M.A., Venditti, E.M., Zavella, P., Luna, V. and Ma, J.

Abstract

INTRODUCTION Cultural tailoring of evidence-based diabetes prevention program (DPP) interventions is needed to effectively address obesity and its related chronic diseases among Latinos in primary care. This article describes the patient-centered process used to adapt the DPP and reports cultural adaptations. METHODS We used a 2-stage formative research process to culturally adapt an evidence-based DPP intervention in the context of primary care. The first stage involved 5 focus groups of Latino patients and interviews with 5 stakeholders (3 with primary care physicians and 2 with medical directors) to inform a first round of adaptations. The second stage included pretesting the stage I-adapted intervention with a Latino patient advisory board to complete a second round of adaptations. RESULTS Key stakeholders involved in this 2-stage adaptation process included 34 Latino patients who participated in 5 focus groups and 5 physicians and medical directors who participated in key informant interviews during stage I and 11 patients who attended the 16 advisory board meetings and their family members who attended 1 of the meetings during stage II. Using this patient-centered stakeholder-engaged approach, we found the original intervention was largely congruent with the cultural values of the study population. To further strengthen the cultural relevance of the intervention, salient cultural values emphasized by patients and stakeholders underscored the importance of family and community support for behavior change. Accordingly, key adaptations were made to (1) invite family members to the orientation session and at 2 other key timepoints to facilitate family support, (2) provide participants support from the coach and each other via smartphone applications, and (3) provide healthy, easy, low-cost culturally appropriate meals at each group session. CONCLUSIONS The 2-stage approach actively engaging patients, family members, providers, and health care system leaders reinforced the cultural congruence of the existing intervention while further strengthening it with adaptations promoting Latino family and community support.

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A Mobile Health Intervention to Reduce Pain and Improve Health (MORPH) in Older Adults With Obesity: Protocol for the MORPH Trial. (2018)

JMIR research protocols

Authors: Fanning, J., Brooks, A.K., Ip, E., Nicklas, B.J. and Rejeski, W.J.

Abstract

BACKGROUND Chronic pain is a complex, age-related health issue that affects both physical functioning and quality of life. Because the impact of chronic pain is worsened by obesity and inactivity, nonpharmacological interventions that promote movement, reduce sitting, and aid in weight loss are needed to help manage pain symptoms among older adults with chronic pain. OBJECTIVE The Mobile Intervention to Reduce Pain and Improve Health (MORPH) pilot trial aims to develop and test the feasibility and acceptability of a novel, patient-centered intervention to reduce chronic pain and improve physical functioning in older adults, leveraging the combination of telecoaching and individually adaptive mHealth tools to decrease both body mass and sedentary behavior. METHODS MORPH comprises 2 phases, including a 1-year iterative development phase, and a 1-year pilot randomized controlled trial (RCT). During the development phase, representative participants will engage in one-on-one structured interviews and a 1-week field test. The resulting feedback will be used to guide the development of the finalized MORPH intervention package. During the second phase, the finalized intervention will be tested in a pilot RCT (N=30) in which older adult participants with chronic pain and obesity will be assigned to receive the 12-week MORPH intervention or to a waitlist control. Primary outcomes include self-reported pain symptoms and physical function. RESULTS Phase 1 recruitment is ongoing as of December 2017. CONCLUSIONS The MORPH intervention brings together a strong body of evidence using group-based behavioral intervention designs with contemporary mHealth principles, allowing for intervention when and where it matters the most. Given the ubiquity of smartphone devices and the popularity of consumer activity and weight monitors, the results of this study may serve to inform the development of scalable, socially driven behavioral pain management interventions. TRIAL REGISTRATION ClinicalTrials.gov NCT03377634; https://clinicaltrials.gov/ct2/show/NCT03377634 (Archived by WebCite at http://www.webcitation.org/6yj0J5Pan). REGISTERED REPORT IDENTIFIER RR1-10.2196/9712.

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A mobile phone-based program to promote healthy behaviors among adults with prediabetes: study protocol for a pilot randomized controlled trial (2018)

Pilot and Feasibility Studies

Authors: Griauzde, D.H., Kullgren, J.T., Liestenfeltz, B., Richardson, C. and Heisler, M.

Abstract

Rates of participation in Diabetes Prevention Programs (DPPs) are low. This may be due, in part, to low levels of autonomous motivation (i.e., motivation that arises from internal sources and sustains healthy behaviors over time) to prevent type 2 diabetes (T2DM) among many individuals with prediabetes. Mobile health (mHealth) technologies that incorporate principles from the Self-Determination Theory offer an effective and scalable approach to increase autonomous motivation levels. One promising mobile phone-based application is JOOL Health, which aims to help users connect certain health behaviors (e.g., sleep and diet) with personal values in specific life domains (e.g., family and work). The first aim of this study is to estimate whether JOOL Health can increase autonomous motivation to prevent T2DM among individuals with prediabetes who declined DPP participation. The second aim of this pilot study is to examine the intervention's feasibility and acceptability. This is a 12-week, three-arm pilot randomized controlled trial. We will recruit 105 individuals with prediabetes who did not engage in a DPP despite invitation from their health plan to participate in face-to-face or web-based programs at no out-of-pocket-cost. Participants will be randomized to one of three study arms: (1) a group that receives information on prediabetes, evidence-based strategies to decrease progression to T2DM, and a list of resources for mHealth tools for monitoring diet, physical activity, and weight (comparison group); (2) a group that receives the JOOL Health application; and (3) a group that receives the JOOL Health application as well as a Fitbit activity tracker and wireless-enabled scale. Our primary outcome is change in autonomous motivation to prevent T2DM (measured using the Treatment Self-Regulation Questionnaire). We will also collect data related to the intervention's feasibility (recruitment and retention rates) and acceptability (adherence and qualitative experience) as well as changes in psychosocial outcomes, hemoglobin A1c, and weight. To our knowledge, this is the first study that aims to promote positive health behaviors among individuals with prediabetes who previously declined to participate in a DPP. Our results will inform a larger trial to test the effect of JOOL Health on clinically relevant outcomes, including weight loss, physical activity, and DPP engagement.

A Smartphone App to Promote an Active Lifestyle in Lower-Educated Working Young Adults: Development, Usability, Acceptability, and Feasibility Study. (2018)

JMIR mHealth and uHealth

Authors: Simons, D., De Bourdeaudhuij, I., Clarys, P., De Cocker, K., Vandelanotte, C. and Deforche, B.

Abstract

BACKGROUND Physical activity (PA) levels are problematic in lower-educated working young adults (18-26 years). To promote PA, smartphone apps have great potential, but there is no evidence for their effectiveness in this population. To increase the likelihood that a newly developed app will be effective, formative research and user testing are required. OBJECTIVE The aim of this study was to describe the development, usability, acceptability, and feasibility of a new theory- and evidence-based smartphone app to promote an active lifestyle in lower-educated working young adults. METHODS The new app was developed by applying 4 steps. First, determinants important to promote an active lifestyle in this population were selected. Second, evidence-based behavior change techniques were selected to convert the determinants into practical applications. Third, a new smartphone app was developed. Fourth, volunteers (n=11, both lower and higher educated) tested the app on usability, and lower-educated working young adults (n=16) tested its acceptability and feasibility via (think aloud) interviews, a questionnaire, and Google Analytics. The app was accordingly adapted for the final version. RESULTS A new Android app, Active Coach, was developed that focused on knowledge, attitude, social support, and self-efficacy (based on outcomes from step 1), and that applied self-regulation techniques (based on outcomes from step 2). The app consists of a 9-week program with personal goals, practical tips, and scientific facts to encourage an active lifestyle. To ensure all-day and automatic self-monitoring of the activity behavior, the Active Coach app works in combination with a wearable activity tracker, the Fitbit Charge. Issues detected by the usability test (eg, text errors, wrong messages) were all fixed. The acceptability and feasibility test showed that participants found the app clear, understandable, and motivating, although some aspects needed to be more personal. CONCLUSIONS By applying a stepwise, user-centered approach that regularly consulted the target group, the new app is adapted to their specific needs and preferences. The Active Coach app was overall positively evaluated by the lower-educated working young adults at the end of the development process.

Bouldering psychotherapy reduces depressive symptoms even when general physical activity is controlled for: A randomized controlled trial (2018)

Heliyon

Authors: Stelzer, E.-M., Book, S., Graessel, E., Hofner, B., Kornhuber, J. and Luttenberger, K.

Abstract

Background Bouldering psychotherapy (BPT) combines psychotherapeutic elements with physical activity (PA). It might be effective for reducing symptoms of depression, but so far, no study has assessed individuals' levels of PA to control for whether positive effects on depression can also be found when adjusting for participants' levels of PA. This is important because PA itself has been proven effective in reducing depression and therefore might be an important variable to account for – especially in therapies using sport as one therapeutic mechanism. Methods Using a waitlist control group design, outpatients with depression were assessed at baseline and after eight, 16, and 24 weeks. The intervention group took part in an eight-week bouldering psychotherapy which met once a week for three hours. Self-report measures before and after the intervention included the Symptom Checklist-90-R (SCL-90-R), the Beck Depression Inventory (BDI-II), and the questionnaire on resources and self-management skills (FERUS). PA was assessed during the first 16-week period via FitBit Zip accelerometers. Results Altogether, 47 complete cases (20 men and 27 women) were included in the final analyses. Depression scores dropped by up to 6.74 (CI 2.80–10.67) points on the SCL-90-R depression scale and by up to 8.26 (CI 4.21–12.31) points on the BDI-II during the BPT intervention, the control group remained stable (SCL-90-R Cohen's d = 0.60; BDI-II: Cohen's d = .50). All Participants accrued an average of 6,515 steps per day, which is considered “low-active.” Participants of the BPT intervention were significantly more likely to reduce their depressive symptoms (p = .025) than participants of the control group, even when PA was controlled for in a regression analysis. Limitations Limitations of the study are the relatively small number of patients and the assessment of outcome scores via self-report. Conclusions This study provides evidence that short-term BPT can be effective for reducing symptoms of depression even if controlled for other therapeutically active confounders including antidepressant medication, psychotherapy and general level of PA.

Buying time: a proof-of-concept randomized controlled trial to improve sleep quality and cognitive function among older adults with mild cognitive impairment (2018)

Trials

Authors: Falck, R.S., Davis, J.C., Best, J.R., Li, L.C., Chan, P.C.Y., Wyrough, A.B., Landry, G.J. and Liu-Ambrose, T.

Abstract

Current evidence suggests that good quality sleep is associated with preserved cognitive function and reduced dementia risk in older adults. Sleep complaints are especially common among older adults with mild cognitive impairment (MCI), and this may contribute to their increased risk for progression to dementia. Thus, improving their sleep may be important for maintaining their cognitive health. Chronotherapy is a set of intervention strategies that can improve sleep quality through strengthening the entrainment of the biological clock to the solar light-dark cycle, and includes strategies such as (1) bright light therapy (BLT); (2) physical activity (PA); and (3) good sleep hygiene. Of these strategies, BLT is the most potent and is based on providing individualized timing to entrain circadian rhythms. Thus, a personalized chronotherapy intervention of individually timed BLT and individually tailored PA promotion, in conjunction with general sleep hygiene education may promote older adult sleep quality. We therefore aim to carry out a proof-of-concept randomized controlled trial (RCT) to examine the efficacy of such a personalized chronotherapy intervention to improve sleep quality among older adults with MCI. This was a 24-week RCT of a personalized chronotherapy intervention aimed to primarily improve sleep quality as measured by the MotionWatch8©. Participants in the personalized chronotherapy group (INT) will receive four once-weekly, general sleep hygiene education classes, followed by 20 weeks of (1) individually timed BLT and (2) bi-weekly, individually tailored PA counseling phone calls in conjunction with receiving a consumer-available PA tracker--the Fitbit® Flex™. Ninety-six adults (aged 65-85 years) classified as having MCI (i.e., Mini-Mental State Exam (MMSE) ≥ 24; Montreal Cognitive Assessment (MoCA) ≤ 26; without dementia or significant functional impairment) will be randomized to either INT or a waitlist control group (CON). The results of this trial will help determine if a personalized chronotherapy intervention that includes individually timed BLT and individually tailored PA promotion, along with general sleep hygiene education can promote sleep quality among older adults at increased risk for dementia. Our results will help inform best practices for promoting sleep quality among older adults with MCI. ClinicalTrials.gov , NCT02926157 . Registered on 6 October 2016.

Comparison Of Daily Energy Expenditure And Weekly Physical Activity Exposure Estimated Using Consumer And Research-grade Physical Activity Monitors During Officer Cadet Initial Military Training (2018)

Medicine & Science in Sports & Exercise

Authors: Powell, S.D., Siddall, A.G., S Thompson, J.E., Edwards, V.C., Jackson, S., Greeves, J.P., Wardle, S., Blacker, S.D. and Myers, S.D.

Abstract

PURPOSE: Wearable physical activity monitors provide the capability to estimate the physical demands of military training and to potentially inform training practices. This study aimed to compare both the daily energy expenditure (EE) and weekly physical activity (PA) measured from two wrist-worn activity monitoring devices in Officer Cadets (OC) during initial military training. METHODS: Forty (26 male, 14 female) OC’s (mean ± SD: age 24 ± 2, height 1.76 ± 0.08 m, body mass 79.21 ± 9.97 kg) wore a consumer (“CN”; Fitbit Surge, San Francisco, USA) and a research-grade (“RG”; GENEActiv Original, Activinsights, Cambridge, UK) activity monitor during the second 14-week term of British Army OC training. A filtering process was implemented to exclude training days that did not fulfil wear-time criteria. Bivariate Pearsons correlations and limits of agreement (LoA) were used to compare EE measurement and duration of sedentary, light, moderate and vigorous PA between devices. RESULTS: Mean daily estimated EE from the CN and RG were 13.9 ± 2.5 and 15.7 ± 1.8 MJ.day-1, respectively. Estimated daily EE ranged from 8.6 ± 2.8 (day 35) to 22.4 ± 6.7 MJ.day-1 (day 49) in CN and from 10.7 ± 4.5 (day 55) to 21.3 ± 8.1 MJ.day-1 (day 49) in RG. There was a strong correlation between EE in CN and RG over 14 weeks (r = 0.761, p<0.001). However, the LoA indicated that CN underestimated EE (mean bias [95% CI] by -1.4 [-16 - 3.2] MJ.day-1, p<0.001) compared to the RG. Mean daily estimates from CN were 1069 ± 86 sedentary minutes, 221 ± 44 light minutes, 40 ± 14 moderate minutes and 56 ± 16 vigorous minutes. RG estimated 543 ± 53 sedentary minutes, 90 ± 16 light minutes, 249 ± 52 moderate minutes and 33 ± 14 vigorous minutes. All intensities were significantly different between CN and RG (p<0.05). The CN overestimated on sedentary minutes (526 mins.day-1 [319 - 734] mins.day-1), light minutes (131 [39 - 224] mins.day-1) and vigorous minutes (24 [-15 - 62] mins.day-1), but underestimated moderate minutes -208 [-295 - -122] mins.day-1). CONCLUSION: Consumer grade physical activity monitors provide an easily accessible tool for monitoring military training but more research is required to improve their accuracy before they can be used to inform training practices.

Comparison of Research- and Consumer-grade Energy Expenditure Estimation Methods during 10 Days of Military Training (2018)

Medicine & Science in Sports & Exercise

Authors: Siddall, A.G., Thompson, J.E.S., Powell, S.D., Edwards, V.C., Kefyalew, S.S., Singh, P.A., Orford, E.R., Venables, M.C., Jackson, S., Greeves, J.P., Blacker, S.D. and Myers, S.D.

Abstract

PURPOSE: Wearable physical activity monitoring devices have improved the ability to estimate free-living total energy expenditure (TEE) but their application during arduous military training alongside more well-established techniques has not been widely documented. This study aimed to assess the validity of two wrist-worn activity monitors to estimate TEE by evaluating performance against doubly labelled water (DLW) during British Army Officer Cadet (OC) training. METHODS: Twenty (10 male and 10 female) OCs (mean ± SD: age 22 ± 1 years, height 1.73 ± 0.08 m, body mass 77.0 ± 9.3 kg) wore one research-grade accelerometer (GENEActiv, Cambridge, UK; “RES”) on the dominant wrist and one commercially available (FITBIT SURGE, USA; “COM”) monitor on the non-dominant wrist for 10 days of training. Immediately prior to this 10-day period, participants consumed a bolus of DLW and provided daily urine samples, which were analysed by mass spectrometry to determine TEE. Bivariate correlations and limits of agreement were calculated to compare the 10-day mean TEE from DLW with both activity monitors to evaluate device performance. RESULTS: TEE (mean ± SD) from DLW, RES and COM were 17.2 ± 2.7 MJ.day-1 (4112 ± 652 kcal.day-1), 17.3 ± 2.8 MJ.day-1 (4129 ± 677 kcal.day-1) and 15.1 ± 3.7 MJ.day-1 (3607 ± 888 kcal.day-1), respectively. TEE from DLW was linearly correlated with both RES (r=0.786, p<0.001) and COM (r=0.888, p<0.001). Despite a stronger association with DLW however, COM tended to underestimate TEE (mean bias [95% CI]) by -2.1 [-5.6-1.4] MJ.day-1 (-505 [-1348-339] kcal.day-1; p<0.05). In contrast, mean TEE from RES was similar to DLW (-0.05 [-3.6-3.5] MJ.day-1; -11 [-867-845] kcal.day-1; p>0.05). CONCLUSION: Wearable physical activity monitors provides a cheaper and more practical method for estimating free-living TEE than DLW, and could be useful for military populations. However, this study suggests a consumer monitor may underperform, by underestimating TEE, during physically demanding training in comparison to a research- grade device.

Development of a Just-in-Time Adaptive mHealth Intervention for Insomnia: Usability Study (2018)

JMIR Human Factors

Authors: Pulantara, I.W., Parmanto, B. and Germain, A.

Abstract

Background: Healthy sleep is a fundamental component of physical and brain health. Insomnia, however, is a prevalent sleep disorder that compromises functioning, productivity, and health. Therefore, developing efficient treatment delivery methods for insomnia can have significant societal and personal health impacts. Cognitive behavioral therapy for insomnia (CBTI) is the recommended first-line treatment of insomnia but access is currently limited for patients, since treatment must occur in specialty sleep clinics, which suffer from an insufficient number of trained clinicians. Smartphone-based interventions offer a promising means for improving the delivery of CBTI. Furthermore, novel features such as real-time monitoring and assessment, personalization, dynamic adaptations of the intervention, and context awareness can enhance treatment personalization and effectiveness, and reduce associated costs. Ultimately, this “Just in Time Adaptive Intervention” for insomnia--an intervention approach that is acceptable to patients and clinicians, and is based on mobile health (mHealth) platform and tools--can significantly improve patient access and clinician delivery of evidence-based insomnia treatments. Objective: This study aims to develop and assess the usability of a Just in Time Adaptive Intervention application platform called iREST (“interactive Resilience Enhancing Sleep Tactics”) for use in behavioral insomnia interventions. iREST can be used by both patients and clinicians. Methods: The development of iREST was based on the Iterative and Incremental Development software development model. Requirement analysis was based on the case study’s description, workflow and needs, clinician inputs, and a previously conducted BBTI military study/implementation of the Just in Time Adaptive Intervention architecture. To evaluate the usability of the iREST mHealth tool, a pilot usability study was conducted. Additionally, this study explores the feasibility of using an off-the-shelf wearable device to supplement the subjective assessment of patient sleep patterns. Results: The iREST app was developed from the mobile logical architecture of Just in Time Adaptive Intervention. It consists of a cross-platform smartphone app, a clinician portal, and secure 2-way communications platform between the app and the portal. The usability study comprised 19 Active Duty Service Members and Veterans between the ages of 18 and 60. Descriptive statistics based on in-app questionnaires indicate that on average, 12 (mean 12.23, SD 8.96) unique devices accessed the clinician portal per day for more than two years, while the app was rated as “highly usable”, achieving a mean System Usability Score score of 85.74 (SD 12.37), which translates to an adjective rating of “Excellent”. The participants also gave high scores on “ease of use and learnability” with an average score of 4.33 (SD 0.65) on a scale of 1 to 5. Conclusions: iREST provides a feasible platform for the implementation of Just in Time Adaptive Intervention in mHealth-based and remote intervention settings. The system was rated highly usable and its cross-platformness made it readily implemented within the heavily segregated smartphone market. The use of wearables to track sleep is promising; yet the accuracy of this technology needs further improvement. Ultimately, iREST demonstrates that mHealth-based Just in Time Adaptive Intervention is not only feasible, but also works effectively. [JMIR Hum Factors 2018;5(2):e21]

URL

Effect of a Home-Based Exercise Intervention of Wearable Technology and Telephone Coaching on Walking Performance in Peripheral Artery Disease (2018)

JAMA

Authors: McDermott, M.M., Spring, B., Berger, J.S., Treat-Jacobson, D., Conte, M.S., Creager, M.A., Criqui, M.H., Ferrucci, L., Gornik, H.L., Guralnik, J.M., Hahn, E.A., Henke, P., Kibbe, M.R., Kohlman-Trighoff, D., Li, L., Lloyd-Jones, D., McCarthy, W., Polonsky, T.S., Skelly, C., Tian, L., Zhao, L., Zhang, D. and Rejeski, W.J.

Abstract

Importance Clinical practice guidelines support home-based exercise for patients with peripheral artery disease (PAD), but no randomized trials have tested whether an exercise intervention without periodic medical center visits improves walking performance. Objective To determine whether a home-based exercise intervention consisting of a wearable activity monitor and telephone coaching improves walking ability over 9 months in patients with PAD. Design, Setting, and Participants Randomized clinical trial conducted at 3 US medical centers. Patients with PAD were randomized between June 18, 2015, and April 4, 2017, to home-based exercise vs usual care for 9 months. Final follow-up was on December 5, 2017. Interventions The exercise intervention group (n = 99) received 4 weekly medical center visits during the first month followed by 8 months of a wearable activity monitor and telephone coaching. The usual care group (n = 101) received no onsite sessions, active exercise, or coaching intervention. Main Outcomes and Measures The primary outcome was change in 6-minute walk distance at 9-month follow-up (minimal clinically important difference [MCID], 20 m). Secondary outcomes included 9-month change in subcomponents of the Walking Impairment Questionnaire (WIQ) (0-100 score; 100, best), SF-36 physical functioning score, Patient-Reported Outcomes Measurement Information System (PROMIS) mobility questionnaire (higher = better; MCID, 2 points), PROMIS satisfaction with social roles questionnaire, PROMIS pain interference questionnaire (lower = better; MCID range, 3.5-4.5 points), and objectively measured physical activity. Results Among 200 randomized participants (mean [SD] age, 70.2 [10.4] years; 105 [52.5%] women), 182 (91%) completed 9-month follow-up. The mean change from baseline to 9-month follow-up in the 6-minute walk distance was 5.5 m in the intervention group vs 14.4 m in the usual care group (difference, −8.9 m; 95% CI, −26.0 to 8.2 m; P = .31). The exercise intervention worsened the PROMIS pain interference score, mean change from baseline to 9 months was 0.7 in the intervention group vs −2.8 in the usual care group (difference, 3.5; 95% CI, 1.3 to 5.8; P = .002). There were no significant between-group differences in the WIQ score, the SF-36 physical functioning score, or the PROMIS mobility or satisfaction with social roles scores. Conclusions and Relevance Among patients with PAD, a home-based exercise intervention consisting of a wearable activity monitor and telephone coaching, compared with usual care, did not improve walking performance at 9-month follow-up. These results do not support home-based exercise interventions of wearable devices and telephone counseling without periodic onsite visits to improve walking performance in patients with PAD. Trial Registration clinicaltrials.gov Identifier: NCT02462824

Effect of physical activity trackers and daily text messages on quality-of-life in colorectal survivors (Smart Pace): A pilot randomized controlled trial. (2018)

JCO

Authors: Chan, H., Van Loon, K., Kenfield, S.A., Chan, J.M., Mitchell, E., Zhang, L., Paciorek, A., Joseph, G., Laffan, A., Fukuoka, Y., Miaskowski, C., Meyerhardt, J.A., Venook, A.P. and Van Blarigan, E.

Abstract

559Background: There are over 1.3 million colorectal cancer (CRC) survivors in the United States, and many of whom suffer from lower health-related quality-of-life (HRQoL) years after diagnosis and treatment. Physical activity may improve survival outcomes and HRQoL for CRC survivors. Feasible interventions to support physical activity after CRC diagnosis are needed. Methods: We conducted a two-arm randomized controlled trial of 41 men and women who had completed treatment for CRC. Participants in the intervention arm were given a Fitbit Flex? and received daily text messages for 12 weeks. HRQoL was assessed in both arms at baseline and 12 weeks using the RAND Short Form Survey (SF-36) and the Functional Assessment of Cancer Therapy ? Colorectal (FACT-C). Survey score changes from baseline to 12 weeks were compared between the two arms using independent t-tests, and scores at baseline and 12 weeks were compared using paired t-tests. SAS was used for analysis, and statistical significance was declared at p < 0.05. Results: We observed a statistically significant increase in the FACT-C functional well-being sub-scale in individuals in the intervention arm pre- and post- intervention (mean ? 1.81 ± 2.76; p: 0.02). There was no change in functional well-being in the control arm (mean ? -0.35 ± 4.12; p: 0.71). The between-arm comparison of change from baseline to 12 weeks was not statistically significantly (p: 0.08). There was a statistically significant increase in the FACT-C emotional well-being sub-scale in the control arm (mean ? 1.20 ± 2.48; p: 0.04) and in the SF-36 role physical sub-scale in the control arm (mean ? 22.5 ± 38.8; p: 0.02). No other measures of HRQoL were statistically significantly different within groups, across time points, or between groups. Conclusions: A 12-week physical activity intervention using a Fitbit Flex? and daily text messages may improve functional well-being among CRC survivors. Larger randomized studies are needed to definitively determine if a digital physical activity intervention improves functional well-being among CRC survivors, and if the improvement can be sustained over time. Clinical trial information: NCT02966054. 559Background: There are over 1.3 million colorectal cancer (CRC) survivors in the United States, and many of whom suffer from lower health-related quality-of-life (HRQoL) years after diagnosis and treatment. Physical activity may improve survival outcomes and HRQoL for CRC survivors. Feasible interventions to support physical activity after CRC diagnosis are needed. Methods: We conducted a two-arm randomized controlled trial of 41 men and women who had completed treatment for CRC. Participants in the intervention arm were given a Fitbit Flex? and received daily text messages for 12 weeks. HRQoL was assessed in both arms at baseline and 12 weeks using the RAND Short Form Survey (SF-36) and the Functional Assessment of Cancer Therapy ? Colorectal (FACT-C). Survey score changes from baseline to 12 weeks were compared between the two arms using independent t-tests, and scores at baseline and 12 weeks were compared using paired t-tests. SAS was used for analysis, and statistical significance was declared at p < 0.05. Results: We observed a statistically significant increase in the FACT-C functional well-being sub-scale in individuals in the intervention arm pre- and post- intervention (mean ? 1.81 ± 2.76; p: 0.02). There was no change in functional well-being in the control arm (mean ? -0.35 ± 4.12; p: 0.71). The between-arm comparison of change from baseline to 12 weeks was not statistically significantly (p: 0.08). There was a statistically significant increase in the FACT-C emotional well-being sub-scale in the control arm (mean ? 1.20 ± 2.48; p: 0.04) and in the SF-36 role physical sub-scale in the control arm (mean ? 22.5 ± 38.8; p: 0.02). No other measures of HRQoL were statistically significantly different within groups, across time points, or between groups. Conclusions: A 12-week physical activity intervention using a Fitbit Flex? and daily text messages may improve functional well-being among CRC survivors. Larger randomized studies are needed to definitively determine if a digital physical activity intervention improves functional well-being among CRC survivors, and if the improvement can be sustained over time. Clinical trial information: NCT02966054.

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Efficacy of a Community-Based Technology-Enabled Physical Activity Counseling Program for People With Knee Osteoarthritis: Proof-of-Concept Study (2018)

Journal of Medical Internet Research

Authors: Li, L.C., Sayre, E.C., Xie, H., Falck, R.S., Best, J.R., Liu-Ambrose, T., Grewal, N., Hoens, A.M., Noonan, G. and Feehan, L.M.

Abstract

Background: Current practice guidelines emphasize the use of physical activity as the first-line treatment of knee osteoarthritis; however, up to 90% of people with osteoarthritis are inactive. Objective: We aimed to assess the efficacy of a technology-enabled counseling intervention for improving physical activity in people with either a physician-confirmed diagnosis of knee osteoarthritis or having passed two validated criteria for early osteoarthritis. Methods: We conducted a proof-of-concept randomized controlled trial. The immediate group received a brief education session by a physical therapist, a Fitbit Flex, and four biweekly phone calls for activity counseling. The delayed group received the same intervention 2 months later. Participants were assessed at baseline (T0) and at the end of 2 months (T1), 4 months (T2), and 6 months (T3). Outcomes included (1) mean time on moderate-to-vigorous physical activity (MVPA ≥3 metabolic equivalents [METs], primary outcome), (2) mean time on MVPA ≥4 METs, (3) mean daily steps, (4) mean time on sedentary activities, (5) Knee Injury and Osteoarthritis Outcome Score (KOOS), and (6) Partners in Health scale. Mixed-effects repeated measures analysis of variance was used to assess five planned contrasts of changes in outcome measures over measurement periods. The five contrasts were (1) immediate T1-T0 vs delayed T1-T0, (2) delayed T2-T1 vs delayed T1-T0, (3) mean of contrast 1 and contrast 2, (4) immediate T1-T0 vs delayed T2-T1, and (5) mean of immediate T2-T1 and delayed T3-T2. The first three contrasts estimate the between-group effects. The latter two contrasts estimate the effect of the 2-month intervention delay on outcomes. Results: We recruited 61 participants (immediate: n=30; delayed: n=31). Both groups were similar in age (immediate: mean 61.3, SD 9.4 years; delayed: mean 62.1, SD 8.5 years) and body mass index (immediate: mean 29.2, SD 5.5 kg/m2; delayed: mean 29.2, SD 4.8 kg/m2). Contrast analyses revealed significant between-group effects in MVPA ≥3 METs (contrast 1 coefficient: 26.6, 95% CI 4.0-49.1, P=.02; contrast 3 coefficient: 26.0, 95% CI 3.1-49.0, P=.03), daily steps (contrast 1 coefficient: 1699.2, 95% CI 349.0-3049.4, P=.02; contrast 2 coefficient: 1601.8, 95% CI 38.7-3164.9, P=.045; contrast 3 coefficient: 1650.5, 95% CI 332.3-2968.7; P=.02), KOOS activity of daily living subscale (contrast 1 coefficient: 6.9, 95% CI 0.1-13.7, P=.047; contrast 3 coefficient: 7.2, 95% CI 0.8-13.6, P=.03), and KOOS quality of life subscale (contrast 1 coefficient: 7.4, 95% CI 0.0-14.7, P=.049; contrast 3 coefficient: 7.3, 95% CI 0.1-14.6, P=.048). We found no significant effect in any outcome measures due to the 2-month delay of the intervention. Conclusions: Our counseling program improved MVPA ≥3 METs, daily steps, activity of daily living, and quality of life in people with knee osteoarthritis. These findings are important because an active lifestyle is an important component of successful self-management. Trial Registration: ClinicalTrials.gov NCT02315664; https://clinicaltrials.gov/ct2/show/NCT02315664 (Archived by WebCite at http://www.webcitation.org/6ynSgUyUC) [J Med Internet Res 2018;20(4):e159]

Engagement Strategies for Self-Monitoring Symptoms of Bipolar Disorder With Mobile and Wearable Technology: Protocol for a Randomized Controlled Trial (2018)

JMIR Research Protocols

Authors: Cochran, A., Belman-Wells, L. and McInnis, M.

Abstract

Background: Monitoring signs and symptoms in bipolar disorder (BP) is typically based on regular assessments from patient-clinician interactions. Mobile and wearable technology promises to make monitoring symptoms in BP easier, but little is known about how best to engage individuals with BP in monitoring symptoms. Objective: The objective of this study was to provide the rationale and protocol for a randomized controlled trial that investigates engagement strategies for monitoring symptoms of BP, including the strategies of using activity trackers compared with self-reports and reviewing recorded symptoms weekly with an interviewer. Methods: A total of 50 individuals with BP will be recruited from the Prechter Longitudinal Study of Bipolar Disorder at the University of Michigan to participate in a 6-week study. Participants will monitor their symptoms through an activity tracker (Fitbit Alta HR) and a mobile phone app designed for this study. In addition to monitoring symptoms, participants have a 50-50 chance of being assigned to an arm that reviews self-reports and activity information weekly. Statistical tests will be performed to test hypotheses that participants adhere to activity tracking significantly more than self-reporting, prefer activity tracking significantly more than self-reporting, and better adhere to both activity tracking and self-reporting when reviewing collected information weekly. Results: Recruitment commenced in November 2017. The first group of participants began the study in January 2018. Conclusions: This study aims to establish strategies to engage individuals with BP in monitoring their symptoms with mobile and wearable technology. Better engagement strategies are expected to aid current efforts in bipolar research and clinical care, from the development of new mobile phone apps to providing the right intervention to the right individual at the right moment. Trial Registration: ClinicalTrials.gov NCT03358238; https://clinicaltrials.gov/ct2/show/NCT03358238 (Archived by WebCite at http://www.webcitation.org/6yebuNfz5) Registered Report Identifier: RR1-10.2196/9899 [JMIR Res Protoc 2018;7(5):e130]

Evaluating the Validity of Current Mainstream Wearable Devices in Fitness Tracking Under Various Physical Activities: Comparative Study (2018)

JMIR Mhealth Uhealth

Authors: Xie, J., Wen, D., Liang, L., Jia, Y., Gao, L. and Lei, J.

Abstract

Background: Wearable devices have attracted much attention from the market in recent years for their fitness monitoring and other health-related metrics; however, the accuracy of fitness tracking results still plays a major role in health promotion. Objective: The aim of this study was to evaluate the accuracy of a host of latest wearable devices in measuring fitness-related indicators under various seminatural activities. Methods: A total of 44 healthy subjects were recruited, and each subject was asked to simultaneously wear 6 devices (Apple Watch 2, Samsung Gear S3, Jawbone Up3, Fitbit Surge, Huawei Talk Band B3, and Xiaomi Mi Band 2) and 2 smartphone apps (Dongdong and Ledongli) to measure five major health indicators (heart rate, number of steps, distance, energy consumption, and sleep duration) under various activity states (resting, walking, running, cycling, and sleeping), which were then compared with the gold standard (manual measurements of the heart rate, number of steps, distance, and sleep, and energy consumption through oxygen consumption) and calculated to determine their respective mean absolute percentage errors (MAPEs). Results: Wearable devices had a rather high measurement accuracy with respect to heart rate, number of steps, distance, and sleep duration, with a MAPE of approximately 0.10, whereas poor measurement accuracy was observed for energy consumption (calories), indicated by a MAPE of up to 0.44. The measurements varied for the same indicator measured by different fitness trackers. The variation in measurement of the number of steps was the highest (Apple Watch 2: 0.42; Dongdong: 0.01), whereas it was the lowest for heart rate (Samsung Gear S3: 0.34; Xiaomi Mi Band 2: 0.12). Measurements differed insignificantly for the same indicator measured under different states of activity; the MAPE of distance and energy measurements were in the range of 0.08 to 0.17 and 0.41 to 0.48, respectively. Overall, the Samsung Gear S3 performed the best for the measurement of heart rate under the resting state (MAPE of 0.04), whereas Dongdong performed the best for the measurement of the number of steps under the walking state (MAPE of 0.01). Fitbit Surge performed the best for distance measurement under the cycling state (MAPE of 0.04), and Huawei Talk Band B3 performed the best for energy consumption measurement under the walking state (MAPE of 0.17). Conclusions: At present, mainstream devices are able to reliably measure heart rate, number of steps, distance, and sleep duration, which can be used as effective health evaluation indicators, but the measurement accuracy of energy consumption is still inadequate. Fitness trackers of different brands vary with regard to measurement of indicators and are all affected by the activity state, which indicates that manufacturers of fitness trackers need to improve their algorithms for different activity states. [JMIR Mhealth Uhealth 2018;6(4):e94]

Exercise combined with Acceptance and Commitment Therapy (ExACT) compared to a supervised exercise programme for adults with chronic pain: study protocol for a randomised controlled trial (2018)

Trials

Authors: Casey, M.-B., Smart, K., Segurado, R., Hearty, C., Gopal, H., Lowry, D., Flanagan, D., McCracken, L. and Doody, C.

Abstract

Acceptance and Commitment Therapy (ACT) is a form of cognitive behavioural therapy, which may be beneficial for people with chronic pain. The approach aims to enhance daily functioning through increased psychological flexibility. Whilst the therapeutic model behind ACT appears well suited to chronic pain, there is a need for further research to test its effectiveness in clinical practice, particularly with regards to combining ACT with physical exercise. This prospective, two-armed, parallel-group, single-centre randomised controlled trial (RCT) will assess the effectiveness of a combined Exercise and ACT programme, in comparison to supervised exercise for chronic pain. One hundred and sixty patients, aged 18 years and over, who have been diagnosed with a chronic pain condition by a physician will be recruited to the trial. Participants will be individually randomised to one of two 8-week, group interventions. The combined group will take part in weekly psychology sessions based on the ACT approach, in addition to supervised exercise classes led by a physiotherapist. The control group will attend weekly supervised exercise classes but will not take part in an ACT programme. The primary outcome will be pain interference at 12-week follow-up, measured using the Brief Pain Inventory-Interference Scale. Secondary outcomes will include self-reported pain severity, self-perception of change, patient satisfaction, quality of life, depression, anxiety and healthcare utilisation. Treatment process measures will include self-efficacy, pain catastrophising, fear avoidance, pain acceptance and committed action. Physical activity will be measured using Fitbit ZipTM activity trackers. Both groups will be followed up post intervention and again after 12 weeks. Estimates of treatment effects at follow-up will be based on an intention-to-treat framework, implemented using a linear mixed-effects model. Individual and focus group qualitative interviews will be undertaken with a purposeful sample of participants to explore patient experiences of both treatments. To our knowledge, this will be the first RCT to examine whether combining exercise with ACT produces greater benefit for patients with chronic pain, compared to a standalone supervised exercise programme.

Free-Living Physical Activity Monitoring in Adult US Patients with Multiple Sclerosis Using a Consumer Wearable Device (2018)

Digital Biomarkers

Authors: DasMahapatra, P., Chiauzzi, E., Bhalerao, R. and Rhodes, J.

Abstract

Introduction: Wearable devices have been used to characterize physical activity in multiple sclerosis (MS). The objectives of this study were to advance the literature on the utility of free-living physical activity tracking from secondary analyses of a pilot study in MS patients. Method: The original observational study was conducted in participants with MS at PatientsLikeMe (www.PatientsLikeMe.com), an online network of patients with chronic diseases. Participants completed a baseline self-assessment, and received a Fitbit OneTM wearable device with instructions to upload data. Eligible participants (1) self-reported MS, (2) logged on to the PatientsLikeMe website 90 days prior to enrollment, and (3) consented to participate electronically. Participants (1) textless 18 years, (2) living outside the United States, and (3) requiring wheelchair assistance for most daily activities were excluded. The secondary analyses were limited to participants with complete data on MS type, disease duration, and Multiple Sclerosis Rating Scale (MSRS) and at least 7 days of wearable data. Step count was used as a measure of physical activity. Results: The analysis cohort of 114 participants uploaded a mean of 20.1 days of wearable data over the 23-day study (87% adherence); participants averaged 4,393 steps per day. The mean age of participants was 52 years, predominantly female (75%), relapsing-remitting type (79%), with mean disease duration of 16 years. Mean MSRS score within 30-day of baseline was 32; 72% reported mild-moderate walking disability. The reliability of step count measured by intraclass correlation was 0.55 for a single day, ≥0.7 for 2-day average, and ≥0.9 for 7-day average. After controlling for covariates, self-reported disease severity (MSRS quartile) was an independent predictor of step count (p textless 0.001). Least square means (LS means) for participants that were least disabled (lowest quartile) was 5,937 steps, which was significantly higher than participants in the second, third, and fourth quartiles (4,570, 3,490, and 3,272, respectively). Similarly, LS means of participants with no ambulatory disability (measured by MSRS walk component) was 6,931 steps, significantly higher than participants with greater disability (4,743, 4,394, 2,727 steps for symptomatic, mild, and moderate disability, respectively, p textless 0.001). Discussion: Using an interactive platform, this study captured free-living mobility data in MS patients. Important metrics such as the use of a minimum of 2-day estimates and self-reported disability were found to be robust indicators and correlates, respectively, of participant activity levels. Further triangulation of such metrics may reduce the burden on patients, clinicians, and researchers when monitoring clinical status.

Impact Of Placement Of Wrist-worn Activity Monitors During The Lab And Free-living Settings (2018)

Medicine & Science in Sports & Exercise

Authors: Kang, M., Lee, N.H., Jung, H.C., Jeon, S. and Lee, S.

Abstract

Wrist-worn activity monitors have been widely used to measure heart rates, step counts, and/or calories. While the versatility of altering the wearing locations (i.e., left vs. right; distal vs. proximal) may prove appealing, the influence of monitor placement on the outcome measurements needs to be examined. PURPOSE: This study was to examine the difference in measurements of heart rates, step counts, and calories estimated from the Fitbit monitors worn at different locations. METHODS: Thirty-two healthy male and female, aged 26.03 ± 6.59 years, participated in this study. Participants wore Fitbit monitors at four different locations [Right Proximal (RP), Right Distal (RD), Left Proximal (LP), Left Distal (LD)]. Lab testing consisted of four 5-min phases: slow and brisk walking and jogging at 53.6, 107.3, 160.9 m/min on a treadmill and a recovery. Free living activities involved ten 5-min activities with different intensity levels (e.g., stretching, climbing stairs, jogging). Heart rates, step counts, and calories were recorded during various activities. Repeated measures ANOVAs were performed with a monitor placement as a within-subjects factor on 14 lab and free-living activities for each outcome measurement. Bonferroni technique was used to adjust the alpha level of .004 (.05/14). The Greenhouse-Geisser (G-G) adjusted F and degrees of freedom were reported. RESULTS: Overall, there were no significant differences in measurements of heart rates, step counts, and calories estimated from the four Fitbit monitors during the lab activities. In free-living activities, step counts were significantly different during climbing stairs, F(2.86, 88.76) = 5.16, G-G p = .003 and sports, F(1.24, 38.40) = 27.93, G-G p < .001. Step counts estimated from LD (446 ± 49) were significantly higher than Fitbit monitors worn at RP (413 ± 61) and RD (417 ± 49) when climbing stairs. Fitbit monitors worn at LP (649 ± 64) and LD (642 ± 70) estimated significantly higher step counts than Fitbit monitors worn at RP (587 ± 75) and RD (565 ± 73) as participated in sports. CONCLUSION: This study revealed that monitor placement does not make a significant influence on the measurements of heart rates and calories during the lab and free- living settings. Further studies on the impact of monitor placement against criterion measures are warranted.

mActive-Smoke: A Prospective Observational Study Using Mobile Health Tools to Assess the Association of Physical Activity With Smoking Urges (2018)

JMIR mHealth and uHealth

Authors: Silverman-Lloyd, L.G., Kianoush, S., Blaha, M.J., Sabina, A.B., Graham, G.N. and Martin, S.S.

Abstract

Background: Evidence that physical activity can curb smoking urges is limited in scope to acute effects and largely reliant on retrospective self-reported measures. Mobile health technologies offer novel mechanisms for capturing real-time data of behaviors in the natural environment. Objective: This study aimed to explore this in a real-world longitudinal setting by leveraging mobile health tools to assess the association between objectively measured physical activity and concurrent smoking urges in a 12-week prospective observational study. Methods: We enrolled 60 active smokers (≥3 cigarettes per day) and recorded baseline demographics, physical activity, and smoking behaviors using a Web-based questionnaire. Step counts were measured continuously using the Fitbit Charge HR. Participants reported instantaneous smoking urges via text message using a Likert scale ranging from 1 to 9. On study completion, participants reported follow-up smoking behaviors in an online exit survey. Results: A total of 53 participants (aged 40 [SD 12] years, 57% [30/53] women, 49% [26/53] nonwhite) recorded at least 6 weeks of data and were thus included in the analysis. We recorded 15,365 urge messages throughout the study, with a mean of 290 (SD 62) messages per participant. Mean urge over the course of the study was positively associated with daily cigarette consumption at follow-up (Pearson r=.33; P=.02). No association existed between daily steps and mean daily urge (beta=−6.95×10−3 per 1000 steps; P=.30). Regression models of acute effects, however, did reveal modest inverse associations between steps within 30-, 60-, and 120-min time windows of a reported urge (beta=−.0191 per 100 steps, P<.001). Moreover, 6 individuals (approximately 10% of the study population) exhibited a stronger and consistent inverse association between steps and urge at both the day level (mean individualized beta=−.153 per 1000 steps) and 30-min level (mean individualized beta=−1.66 per 1000 steps). Conclusions: Although there was no association between objectively measured daily physical activity and concurrently self-reported smoking urges, there was a modest inverse relationship between recent step counts (30-120 min) and urge. Approximately 10% of the individuals appeared to have a stronger and consistent inverse association between physical activity and urge, a provocative finding warranting further study. [JMIR Mhealth Uhealth 2018;6(5):e121]

Modeling Individual Differences: A Case Study of the Application of System Identification for Personalizing a Physical Activity Intervention (2018)

Journal of Biomedical Informatics

Authors: Phatak, S.S., Freigoun, M.T., Martín, C.A., Rivera, D.E., Korinek, E.V., Adams, M.A., Buman, M.P., Klasnja, P. and Hekler, E.B.

Abstract

BACKGROUND Control systems engineering methods, particularly, system identification (system ID), offer an idiographic (i.e., person-specific) approach to develop dynamic models of physical activity (PA) that can be used to personalize interventions in a systematic, scalable way. The purpose of this work is to: 1) apply system ID to develop individual dynamical models of PA (steps/day measured using Fitbit Zip) in the context of a goal setting and positive reinforcement intervention informed by Social Cognitive Theory; and 2) compare insights on potential tailoring variables (i.e., predictors expected to influence steps and thus moderate the suggested step goal and points for goal achievement) selected using the idiographic models to those selected via a nomothetic (i.e., aggregated across individuals) approach. METHOD A personalized goal setting and positive reinforcement intervention was deployed for 14 weeks. Baseline PA measured in weeks 1-2 was used to inform personalized daily step goals delivered in weeks 3-14. Goals and expected reward points (granted upon goal achievement) were pseudo-randomly assigned using techniques from system ID, with goals ranging from their baseline median steps/day up to 2.5x baseline median steps/day, and points ranging from 100-500 (i.e., $0.20 - $1.00). Participants completed a series of daily self-report measures. Auto Regressive with eXogenous Input (ARX) modeling and multilevel modeling (MLM) were used as the idiographic and nomothetic approaches, respectively. RESULTS Participants (N=20, mean age = 47.25 ± 6.16 years, 90% female) were insufficiently active, overweight (mean BMI = 33.79 ± 6.82 kg/m2) adults. Results from ARX modeling suggest that individuals differ in the factors (e.g., perceived stress, weekday/weekend) that influence their observed steps/day. In contrast, the nomothetic model from MLM suggested that goals and weekday/weekend were the key variables that were predictive of steps. Assuming the ARX models are more personalized, the obtained nomothetic model would have led to the identification of the same predictors for 5 of the 20 participants, suggesting a mismatch of plausible tailoring variables to use for 75% of the sample. CONCLUSION The idiographic approach revealed person-specific predictors beyond traditional MLM analyses and unpacked the inherent complexity of PA; namely that people are different and context matters. System ID provides a feasible approach to develop personalized dynamical models of PA and inform person-specific tailoring variable selection for use in adaptive behavioral interventions.

Patterns of Fitbit Use and Activity Levels Throughout a Physical Activity Intervention: Exploratory Analysis from a Randomized Controlled Trial (2018)

JMIR mHealth and uHealth

Authors: Hartman, S.J., Nelson, S.H. and Weiner, L.S.

Abstract

BACKGROUND There has been a rapid increase in the use of technology-based activity trackers to promote behavior change. However, little is known about how individuals use these trackers on a day-to-day basis or how tracker use relates to increasing physical activity. OBJECTIVE The aims were to use minute level data collected from a Fitbit tracker throughout a physical activity intervention to examine patterns of Fitbit use and activity and their relationships with success in the intervention based on ActiGraph-measured moderate to vigorous physical activity (MVPA). METHODS Participants included 42 female breast cancer survivors randomized to the physical activity intervention arm of a 12-week randomized controlled trial. The Fitbit One was worn daily throughout the 12-week intervention. ActiGraph GT3X+ accelerometer was worn for 7 days at baseline (prerandomization) and end of intervention (week 12). Self-reported frequency of looking at activity data on the Fitbit tracker and app or website was collected at week 12. RESULTS Adherence to wearing the Fitbit was high and stable, with a mean of 88.13% of valid days over 12 weeks (SD 14.49%). Greater adherence to wearing the Fitbit was associated with greater increases in ActiGraph-measured MVPA (binteraction=0.35, Ptextless.001). Participants averaged 182.6 minutes/week (SD 143.9) of MVPA on the Fitbit, with significant variation in MVPA over the 12 weeks (F=1.91, P=.04). The majority (68%, 27/40) of participants reported looking at their tracker or looking at the Fitbit app or website once a day or more. Changes in Actigraph-measured MVPA were associated with frequency of looking at one's data on the tracker (b=-1.36, P=.07) but not significantly associated with frequency of looking at one's data on the app or website (P=.36). CONCLUSIONS This is one of the first studies to explore the relationship between use of a commercially available activity tracker and success in a physical activity intervention. A deeper understanding of how individuals engage with technology-based trackers may enable us to more effectively use these types of trackers to promote behavior change. TRIAL REGISTRATION ClinicalTrials.gov NCT02332876; https://clinicaltrials.gov/ct2/show/NCT02332876?term=NCT02332876 &rank=1 (Archived by WebCite at http://www.webcitation.org/6wplEeg8i).

Peer Coaching Through mHealth Targeting Physical Activity in People With Parkinson Disease: Feasibility Study. (2018)

JMIR mHealth and uHealth

Authors: Colón-Semenza, C., Latham, N.K., Quintiliani, L.M. and Ellis, T.D.

Abstract

BACKGROUND Long-term engagement in exercise and physical activity mitigates the progression of disability and increases quality of life in people with Parkinson disease (PD). Despite this, the vast majority of individuals with PD are sedentary. There is a critical need for a feasible, safe, acceptable, and effective method to assist those with PD to engage in active lifestyles. Peer coaching through mobile health (mHealth) may be a viable approach. OBJECTIVE The purpose of this study was to develop a PD-specific peer coach training program and a remote peer-mentored walking program using mHealth technology with the goal of increasing physical activity in persons with PD. We set out to examine the feasibility, safety, and acceptability of the programs along with preliminary evidence of individual-level changes in walking activity, self-efficacy, and disability in the peer mentees. METHODS A peer coach training program and a remote peer-mentored walking program using mHealth was developed and tested in 10 individuals with PD. We matched physically active persons with PD (peer coaches) with sedentary persons with PD (peer mentees), resulting in 5 dyads. Using both Web-based and in-person delivery methods, we trained the peer coaches in basic knowledge of PD, exercise, active listening, and motivational interviewing. Peer coaches and mentees wore FitBit Zip activity trackers and participated in daily walking over 8 weeks. Peer dyads interacted daily via the FitBit friends mobile app and weekly via telephone calls. Feasibility was determined by examining recruitment, participation, and retention rates. Safety was assessed by monitoring adverse events during the study period. Acceptability was assessed via satisfaction surveys. Individual-level changes in physical activity were examined relative to clinically important differences. RESULTS Four out of the 5 peer pairs used the FitBit activity tracker and friends function without difficulty. A total of 4 of the 5 pairs completed the 8 weekly phone conversations. There were no adverse events over the course of the study. All peer coaches were "satisfied" or "very satisfied" with the training program, and all participants were "satisfied" or "very satisfied" with the peer-mentored walking program. All participants would recommend this program to others with PD. Increases in average steps per day exceeding the clinically important difference occurred in 4 out of the 5 mentees. CONCLUSIONS Remote peer coaching using mHealth is feasible, safe, and acceptable for persons with PD. Peer coaching using mHealth technology may be a viable method to increase physical activity in individuals with PD. Larger controlled trials are necessary to examine the effectiveness of this approach.

Physical Activity during Pregnancy Alters Gene Expression in Neonatal Tissue (2018)

Medicine & Science in Sports & Exercise

Authors: Reynolds, L.J., Chavan, N.R., Rice, B.B., Maddox, H.F., Preston, J.D., DeHoff, L.B. and Pearson, K.J.

Abstract

Offspring born to mothers who exercise during pregnancy have been shown to have reduced birth weight and body weight during adolescence; however, mechanisms to explain this phenomenon are lacking. PURPOSE: This study examined whether male infants born to mothers with low levels of naturally occurring physical activity during pregnancy (<6,000 steps/day; <6K) had altered expression of genes related to glucose metabolism and adipogenesis compared to infants born to mothers with greater than 6,000 steps/day (>6K). METHODS: Physical activity levels were assessed via Fitbit Flex during the second and third trimester of pregnancy. The dartos layer of the foreskin was collected following circumcision in full term, singleton, male neonates (n = 6 per group). Tissue was homogenized, RNA isolated, and a NanoString code set run to quantify a panel of genes related to glucose metabolism and adipogenesis, as well as housekeeping genes. RESULTS: Peroxisome proliferator-activated receptor alpha (<6K: 86.4±9.2 vs. >6K: 59.4±5.0) and cAMP responsive element binding protein 1 (<6K: 285.7±36.8 vs. >6K: 197.4±12.1), genes encoding proteins that are involved in partially regulating adipogenesis, and DNA methyltransferase 1 (DNMT1) (<6K: 132.2±6.4 vs. >6K: 112.5±3.7), a gene coding an enzyme involved in the regulation of DNA methylation patterns, were significantly decreased in the infants born to mothers with higher levels of physical activity during pregnancy (p<0.05). Adiponectin receptor 1 (<6K: 490.1±38.1 vs. >6K: 743.3±99.7), a receptor that is downregulated in obese, insulin resistant populations, and glucose transporter 1 (<6K: 88.0±15.7 vs. >6K: 153.3±13.0), a glucose transporter responsible for basal levels of glucose uptake in most cells, were significantly increased in the tissue of neonates born to mothers with higher levels of physical activity (p<0.05). CONCLUSION: These preliminary data suggest that low levels of physical activity during pregnancy are associated with increased gene expression of markers of adipogenesis and decreased markers involved in insulin sensitivity and glucose uptake. Further, these adaptations or other gene expression changes may be epigenetically regulated as DNMT1 levels were significantly lower in the lower physical activity group.

Physical Activity in Patients With Type 2 Diabetes: The Case for Objective Measurement in Routine Clinical Care. (2018)

Diabetes Care

Authors: Oosterom, N., Gant, C.M., Ruiterkamp, N., van Beijnum, B.-J.F., Hermens, H., Bakker, S.J.L., Navis, G., Vollenbroek-Hutten, M.M.R. and Laverman, G.D.

Abstract

To perform at least 150 min of moderate-to-vigorous physical activity (MVPA) per week is a major aim in type 2 diabetes treatment (1), but actual measurements are not routinely performed in clinical practice. We questioned whether subjective assessment of physical activity is accurate to guide lifestyle advice. We compared the results of the Short Questionnaire to Assess Health–Enhancing Physical Activity (SQUASH) (2) and the Fitbit Flex accelerometer (3) in 50 patients with type 2 diabetes included in the DIAbetes and LifEstyle Cohort Twente (DIALECT) trial, which was approved by the local institutional review board METC-Twente (NL57219.044.16) (4). Patients wore the Fitbit for 7 consecutive days and were instructed to maintain their usual activities. Raw Fitbit data (steps/min) were organized into ready variables by an algorithm written in MATLAB (MathWorks, Natick, MA). MVPA was defined as ≥95 steps/min (5). Patients maintained a diary regarding activities not detected by the Fitbit (i.e., cycling, swimming, and fitness). Data are presented as median (interquartile range). The association between log-transformed measured minutes of MVPA was tested using linear regression analyses and the difference between MVPA with the Wilcoxon test for paired nonparametric data. Median age was 70 (63–76) years, median diabetes duration was 16 (10–21) years, 74% of the patients were male, 82% used insulin, and 84% had microvascular and 42% had macrovascular complications. According to SQUASH, patients had 165 (0–645) min of MVPA/week, and 20 participants (40%) adhered to the American Diabetes Association (ADA) recommendation of ≥150 min of MVPA/week (1) (Fig. 1). Fitbit data of >5 days were available in all patients. Median total steps per day were 4,277 (2,588–6,407), and 86% were able to reach ≥95 steps/min at some point during the measurement period. Based on the Fitbit data, patients had 23 (5–41) min of MVPA/week, and 1 (2%) participant adhered to the ADA guideline. When nonregistered activity was added, the figures increased to 31 (5–72) min of MVPA/week and 7 (14%) patients fulfilling the guideline. There was an association between SQUASH-assessed minutes of MVPA/week and Fitbit-assessed minutes of MVPA/week (β = 0.54, P < 0.001) (Fig. 1); however, the number of SQUASH-assessed minutes of MVPA/week was significantly and substantially higher (P < 0.001). Minutes of MVPA measured with SQUASH vs. minutes of MVPA measured with Fitbit. There was a correlation between measured minutes of MVPA between the two methods. However, in the majority of patients, the absolute number of weekly minutes of MVPA was substantially higher using the SQUASH results. Subjective assessment grossly overestimated weekly MVPA compared with objective assessment. When self-reporting, roughly half of the patients seem to meet the MVPA recommendations, whereas objective measurements indicate this number is 14%, at best. A limitation is that the Fitbit Flex, while validated for measuring steps, does not register other activities. Currently, several types of activity trackers with additional functionalities have become available, and future research should evaluate which tracker is most appropriate for clinical use. Although it has not been tested as to whether overestimation of activity occurs in a wider array of patients with diabetes, the findings presented here clearly point out the importance of using objective measurements of activity. We propose to incorporate objective measurements of physical activity in the standard care for patients with type 2 diabetes. Such measurements can not only identify individuals at risk but also increase patient awareness of physical inactivity and help to evaluate interventions.

Self-monitoring and reminder text messages to increase physical activity after colorectal cancer (CRC): A pilot randomized controlled trial. (2018)

JCO

Authors: Van Blarigan, E., Van Loon, K., Kenfield, S.A., Chan, J.M., Mitchell, E., Chan, H., Zhang, L., Paciorek, A., Joseph, G., Laffan, A., Fukuoka, Y., Miaskowski, C., Meyerhardt, J.A. and Venook, A.P.

Abstract

615Background: Over 1.3 million people in the US are living with CRC. Physical activity is associated with lower risk of CRC mortality. Interventions are needed to increase physical activity after CRC diagnosis. Methods: We conducted a pilot RCT to determine the feasibility (adherence, attrition) and acceptability of a 12-wk intervention using a Fitbit Flex? and daily text messages to increase physical activity after CRC. Eligible patients had to have colon or rectal cancer of any stage, be disease free or have stable disease, able to speak and read English, and access to Internet and a mobile phone. Individuals with contraindications to moderate-to-vigorous physical activity (MVPA) or exercising ≥30 min ≥5 d/wk were excluded. We explored the impact of the intervention (n = 20) vs. usual care (n = 21) on MVPA via ActiGraph GT3X+ accelerometers pre-/post-intervention. Results: The intervention was feasible and acceptable. On average, participants were 54 y, BMI 28 kg/m2 and enrolled 1.5 y after diagnosis; 59% were women, 73% were White, and 61% were stage III. The intervention arm wore their Fitbits a median of 74 d (89% of study days, IQR: 23-83 d) and responded to 74% (34) of the 46 text messages that asked for a reply (IQR: 28-82%). Older participants were more likely to wear the Fitbit (r: 0.72; p < 0.001). Married participants were more likely to wear the Fitbit and respond to texts compared to unmarried (96% vs. 32% wear time, p: 0.02 and 85% vs. 46% response rate, p: 0.006). Most patients (88%) reported that the intervention motivated them to exercise and that they were satisfied with their experience. On average, the intervention arm increased MVPA by 14 min/d, while the control arm increased by only 1 min/d, but there was no statistically significant difference in change in MVPA between groups (mean difference comparing change in MVPA in the intervention vs. control: 13 min/d; 95% CI: -14, 40; p: 0.33). Conclusions: A 12-wk physical activity intervention with a Fitbit and text messages is feasible and acceptable among CRC patients after treatment. Larger studies are needed to determine whether the intervention increases physical activity. Clinical trial information: NCT02966054.

URL

Sleep Tracking and Exercise in Patients With Type 2 Diabetes Mellitus (Step-D): Pilot Study to Determine Correlations Between Fitbit Data and Patient-Reported Outcomes. (2018)

JMIR mHealth and uHealth

Authors: Weatherall, J., Paprocki, Y., Meyer, T.M., Kudel, I. and Witt, E.A.

Abstract

BACKGROUND Few studies assessing the correlation between patient-reported outcomes and patient-generated health data from wearable devices exist. OBJECTIVE The aim of this study was to determine the direction and magnitude of associations between patient-generated health data (from the Fitbit Charge HR) and patient-reported outcomes for sleep patterns and physical activity in patients with type 2 diabetes mellitus (T2DM). METHODS This was a pilot study conducted with adults diagnosed with T2DM (n=86). All participants wore a Fitbit Charge HR for 14 consecutive days and completed internet-based surveys at 3 time points: day 1, day 7, and day 14. Patient-generated health data included minutes asleep and number of steps taken. Questionnaires assessed the number of days of exercise and nights of sleep problems per week. Means and SDs were calculated for all data, and Pearson correlations were used to examine associations between patient-reported outcomes and patient-generated health data. All respondents provided informed consent before participating. RESULTS The participants were predominantly middle-aged (mean 54.3, SD 13.3 years), white (80/86, 93%), and female (50/86, 58%). Use of oral T2DM medication correlated with the number of mean steps taken (r=.35, P=.001), whereas being unaware of the glycated hemoglobin level correlated with the number of minutes asleep (r=-.24, P=.04). On the basis of the Fitbit data, participants walked an average of 4955 steps and slept 6.7 hours per day. They self-reported an average of 2.0 days of exercise and 2.3 nights of sleep problems per week. The association between the number of days exercised and steps walked was strong (r=.60, P<.001), whereas the association between the number of troubled sleep nights and minutes asleep was weaker (r=.28, P=.02). CONCLUSIONS Fitbit and patient-reported data were positively associated for physical activity as well as sleep, with the former more strongly correlated than the latter. As extensive patient monitoring can guide clinical decisions regarding T2DM therapy, passive, objective data collection through wearables could potentially enhance patient care, resulting in better patient-reported outcomes.

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The efficacy of a multimodal physical activity intervention with supervised exercises, health coaching and an activity monitor on physical activity levels of patients with chronic, nonspecific low back pain (Physical Activity for Back Pain (PAyBACK) trial): study protocol for a randomised controlled trial (2018)

Trials

Authors: Oliveira, C.B., Franco, M.R., Maher, C.G., Tiedemann, A., Silva, F.G., Damato, T.M., Nicholas, M.K., Christofaro, D.G.D. and Pinto, R.Z.

Abstract

Physical activity plays an important role in the management of chronic low back pain (LBP). Engaging in an active lifestyle is associated with a better prognosis. Nevertheless, there is evidence to suggest that patients with chronic LBP are less likely to meet recommended physical activity levels. Furthermore, while exercise therapy has been endorsed by recent clinical practice guidelines, evidence from systematic reviews suggests that its effect on pain and disability are at best moderate and not sustained over time. A limitation of current exercises programmes for chronic LBP is that these programmes are not designed to change patients' behaviour toward an active lifestyle. Therefore, we will investigate the short- and long-term efficacy of a multimodal intervention, consisting of supervised exercises, health coaching and use of an activity monitor (i.e. Fitbit Flex) compared to supervised exercises plus sham coaching and a sham activity monitor on physical activity levels, pain intensity and disability, in patients with chronic, nonspecific LBP. This study will be a two-group, single-blind, randomised controlled trial. One hundred and sixty adults with chronic, nonspecific LBP will be recruited. Participants allocated to both groups will receive a group exercise programme. In addition, the intervention group will receive health coaching sessions (i.e. assisting the participants to achieve their physical activity goals) and an activity monitor (i.e. Fitbit Flex). The participants allocated to the control group will receive sham health coaching (i.e. encouraged to talk about their LBP or other problems, but without any therapeutic advice from the physiotherapist) and a sham activity monitor. Outcome measures will be assessed at baseline and at 3, 6 and 12 months post randomisation. The primary outcomes will be physical activity, measured objectively with an accelerometer, as well as pain intensity and disability at 3 months post randomisation. Secondary outcomes will be physical activity, pain intensity and disability at 6 and 12 months post randomisation as well as other self-report measures of physical activity and sedentary behaviour, depression, quality of life, pain self-efficacy and weight-related outcomes at 3, 6, and 12 months post randomisation. This study is significant as it will be the first study to investigate whether a multimodal intervention designed to increase physical activity levels reduces pain and disability, and increases physical activity levels compared to a control intervention in patients with chronic LBP.

The Feasibility of a Gender- and Culturally-Sensitive Weight Loss Intervention Plus Mobile Health Technology for Hispanic Males (2018)

Medicine & Science in Sports & Exercise

Authors: Garcia, D.O., Valdez, L.A., Aceves, B., Campas, D., Loya, J., Hingle, M., Humphrey, K., Bell, M.L., McEwen, M. and Hooker, S.P.

Abstract

BACKGROUND: Hispanic males suffer disproportionate rates of overweight and obesity compared to other racial/ethnic groups. However, few weight loss interventions have been developed for this high-risk group. Further, the use of mobile health (mHealth) technologies to support lifestyle behavior changes in weight loss interventions for Hispanic men are untested. PURPOSE: This pilot study examined the feasibility and acceptability of integrating mHealth technology into a 12-week gender- and culturally- sensitive weight loss intervention (GCSWLI) for sedentary, overweight/obese Hispanic males. METHODS: Eighteen Hispanic males (age: 38 ± 11 years; BMI: 34 ± 5 kg/m2; 56% Spanish monolingual) received a GCSWLI including weekly in-person individual sessions, a daily calorie goal, and prescription of ≥225 minutes of moderate-intensity physical activity/week. mHealth technology support included tailored text messaging and behavior and weight self-monitoring support using the Fitbit Charge 2, a consumer- wearable physical activity tracker, and a Fitbit Aria Wi-Fi Smart Scale. Participants were encouraged to use the Fitbit tracker during all waking hours and weigh themselves daily using the provided scale. Participants received biweekly SMS customized to address self-reported barriers to behavior change and in response to objective data collected via tracking tools. Changes in weight from baseline to 12-weeks were estimated using a paired t-test. Descriptive analyses characterized use of the Fitbit and the smart scale. RESULTS: Sixteen of 18 participants completed 12-week assessments; overall attrition rate was 11.1%. Mean weight loss at week 12 was 4.7 kg (95% CI [-7.1, -2.3], p < 0.001). Participants wore the Fitbit 71.6% of intervention days and logged body weight using the smart scale 30.5% of intervention days. Participants identified barriers for use of the technology, including strenuous work activities prohibiting them from wearing the Fitbit. In addition, reliable internet access was cited as a barrier to using the smart scale. CONCLUSIONS: While significant weight loss was achieved integrating mHealth technology into a GCSWLI, the use of technology was modest. Addressing barriers identified in our work may help to refine an mHealth intervention approach for Hispanic men.

The Influence Of Non-exercise Physical Activity During Aerobic Exercise On Cardiometabolic Risk Factors (2018)

Medicine & Science in Sports & Exercise

Authors: Swift, D.L., McGee, J.E., Barefoot, S.G., Brophy, P., Solar, C.A., Houmard, J.A. and Lutes, L.D.

Abstract

PURPOSE: To determine the impact of changes in non-exercise physical activity on changes in cardiometabolic risk factors in participants performing aerobic exercise training. METHODS: Obese adults (N=25) were randomized to an aerobic training group or an aerobic training and increasing non-exercise physical activity group. Both groups performed supervised aerobic training (50%-75% VO2 max) for 24 weeks at a dose of 12 kcals per kg per week. Non-exercise physical activity (total steps, minutes in low, moderate to vigorous [MVPA] physical activity) was quantified during the entire intervention using Fitbit One accelerometers (removed during supervised exercise sessions). Cardiometabolic assessments included lipids, glucose, insulin, 2-hour glucose/insulin from an oral glucose tolerance test, fitness, and body composition measures (% body fat, weight, and waist circumference). Linear regression models were run with change in the cardiometabolic variable as the dependent variable and baseline value, age, race, sex, supervised exercise time, adherence to exercise dose, change in non-exercise physical activity variables (change in total steps, minutes in light intensity and minutes in MVPA) as predictor variables. RESULTS: Change in total steps was a significant predictor for change in weight (r2= 0.17, p=0.04), percent weight loss (r2= 0.18, p=0.03, waist circumference (r2=0.31, p=0.004), triglycerides (r2= 0.30, p=0.01) and relative fitness (r2= 0.19, p=0.03). Change in total steps approached significance as a predictor for absolute fitness (p=0.052) and body fat (p=0.059). Change in minutes in low intensity was a significant predictor of the change in 2-hour glucose (r2= 0.20, p=0.03). Change in MVPA was not associated with change in any cardiometabolic variables (all ps>0.05). Change in non-exercise physical activity did not predict changes in glucose, insulin, 2-hour insulin, low density lipoprotein, high density lipoprotein, total cholesterol, or lean mass levels (all ps>0.05). CONCLUSIONS: Change in non-exercise physical activity outside of aerobic training was associated with changes in several cardiometabolic variables. Increasing total steps or minutes in low intensity may represent a clinical target to maximize the health benefits of aerobic exercise training in obese adults.

The Wearable Technological Device as a Means of Physical Activity Monitoring (2018)

Medicine & Science in Sports & Exercise

Authors: Underhill, A.

Abstract

PURPOSE: To assess the use of a wearable technological device for the increase in attainment of physical activity (PA) with the goal of preventing Type II Diabetes Mellitus (T2DM) through weight loss. The Fitbit offers an advantage to other activity trackers when used for study purposes, in that it can provide continuous measurement of PA across the entire study period. METHODS: Men and women over the age of 40, and at risk for prediabetes, were recruited. The study period was four months in length, with an initial four weeks of baseline PA testing, followed by 12 weeks of lifestyle intervention. Individualized PA goals were set. PA monitoring was very successful. Participants averaged 72 days of PA tracking with 46% of participants reaching the maximal number of days (77). The Fitbit Flex measures steps, minutes sedentary, minutes lightly active, minutes fairly active, minutes very active, and total active minutes. RESULTS: Participants (N = 13) were aged 65.03 (SD = 8.3) years. At baseline, participants were performing 220.8 (SD = 249.0) minutes per week of moderate intensity PA. Participants increased moderate intensity PA to 243.3 (SD = 198.8) minutes per week. At baseline, participants were accumulating 7511.6 steps/day (SD = 3271.2) increasing to 8177.6 steps/day (SD = 3078.9) taken during the three month intervention. No statistical significance was found. A Pearson CC (0.598) showed there was a positive trend with minutes of moderate-to-vigorous activity and weight loss. 36% of the variants of weight loss was influenced by minutes of PA. Compliance to wearing the Fitbit was very good with 93.1% of the weeks having data tracked for at least ≥ 6 days/week. Wear time was corroborated by Fitbit data, which showed of the 1415 tracked days, only 9.3% days recorded were of less than 2000 steps. Barriers to technology were low and 100% of participants strongly agreed that continuous monitoring of weight and PA encouraged them to make healthy lifestyle changes. CONCLUSIONS: Of particular importance was that 46% of participants initially self-reported that they were physically active for more than 150 minutes per week, which shows many people underestimate their actual PA. Continuous monitoring of PA through wearable technology can be a useful modality aiding in weight loss.

Using financial incentives to promote physical activity in American Indian adolescents: A randomized controlled trial (2018)

PLOS ONE

Authors: Short, K.R., Chadwick, J.Q., Cannady, T.K., Branam, D.E., Wharton, D.F., Tullier, M.A., Thompson, D.M. and Copeland, K.C.

Abstract

American Indians (AI) have high prevalence of diabetes in youth and may benefit from increasing physical activity as a strategy to improve metabolic health. We tested whether financial incentives would elicit greater frequency and/or duration of exercise in AI youth at high risk for developing diabetes. Overweight/obese AI boys and girls, 11-20 years old, were instructed to exercise on 3 days/week for 48 weeks at a tribal wellness center. The program was divided into three, 16-week-long phases to test different financial incentive strategies. Within each phase participants were randomly assigned to one of two groups that received different payments for exercise. Phase 1 was designed to test whether the size of the incentive would affect exercise frequency. In Phase 1, the number of exercise sessions did not differ between the group receiving a modest fixed-value payment per exercise session and the group receiving enhanced incentives to exercise more frequently (26 ± 3 versus 28 ± 2 sessions, respectively, p = 0.568). In Phase 2, the provision of an enhanced financial incentive to increase exercise duration resulted longer sessions, as the incentivized and standard payment groups exercised 38 ± 2 versus 29 ± 1 minutes per session (p = 0.002), respectively. In Phase 3, the effect of reducing the incentives on maintenance of exercise behaviors was inconclusive due to high participant withdrawal. Aerobic fitness increased 10% during Phase 1 but was unchanged thereafter. Insulin sensitivity and body composition were unchanged during the study. In conclusion, enhanced financial incentives increased the duration of exercise sessions, but had minimal effects on exercise participation. These results indicate that financial incentives hold promise in motivating previously sedentary, overweight/obese adolescents to exercise longer, but motivating them to sustain an exercise program remains the major challenge. Trial Registration: ClinicalTrials.gov NCT01848353.

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Using Fitness Trackers and Smartwatches to Measure Physical Activity in Research: Analysis of Consumer Wrist-Worn Wearables. (2018)

Journal of Medical Internet Research

Authors: Henriksen, A., Haugen Mikalsen, M., Woldaregay, A.Z., Muzny, M., Hartvigsen, G., Hopstock, L.A. and Grimsgaard, S.

Abstract

BACKGROUND New fitness trackers and smartwatches are released to the consumer market every year. These devices are equipped with different sensors, algorithms, and accompanying mobile apps. With recent advances in mobile sensor technology, privately collected physical activity data can be used as an addition to existing methods for health data collection in research. Furthermore, data collected from these devices have possible applications in patient diagnostics and treatment. With an increasing number of diverse brands, there is a need for an overview of device sensor support, as well as device applicability in research projects. OBJECTIVE The objective of this study was to examine the availability of wrist-worn fitness wearables and analyze availability of relevant fitness sensors from 2011 to 2017. Furthermore, the study was designed to assess brand usage in research projects, compare common brands in terms of developer access to collected health data, and features to consider when deciding which brand to use in future research. METHODS We searched for devices and brand names in six wearable device databases. For each brand, we identified additional devices on official brand websites. The search was limited to wrist-worn fitness wearables with accelerometers, for which we mapped brand, release year, and supported sensors relevant for fitness tracking. In addition, we conducted a Medical Literature Analysis and Retrieval System Online (MEDLINE) and ClinicalTrials search to determine brand usage in research projects. Finally, we investigated developer accessibility to the health data collected by identified brands. RESULTS We identified 423 unique devices from 132 different brands. Forty-seven percent of brands released only one device. Introduction of new brands peaked in 2014, and the highest number of new devices was introduced in 2015. Sensor support increased every year, and in addition to the accelerometer, a photoplethysmograph, for estimating heart rate, was the most common sensor. Out of the brands currently available, the five most often used in research projects are Fitbit, Garmin, Misfit, Apple, and Polar. Fitbit is used in twice as many validation studies as any other brands and is registered in ClinicalTrials studies 10 times as often as other brands. CONCLUSIONS The wearable landscape is in constant change. New devices and brands are released every year, promising improved measurements and user experience. At the same time, other brands disappear from the consumer market for various reasons. Advances in device quality offer new opportunities for research. However, only a few well-established brands are frequently used in research projects, and even less are thoroughly validated.

Using the Habit App for Weight Loss Problem Solving: Development and Feasibility Study (2018)

JMIR mHealth and uHealth

Authors: Pagoto, S., Tulu, B., Agu, E., Waring, M.E., Oleski, J.L. and Jake-Schoffman, D.E.

Abstract

Background: Reviews of weight loss mobile apps have revealed they include very few evidence-based features, relying mostly on self-monitoring. Unfortunately, adherence to self-monitoring is often low, especially among patients with motivational challenges. One behavioral strategy that is leveraged in virtually every visit of behavioral weight loss interventions and is specifically used to deal with adherence and motivational issues is problem solving. Problem solving has been successfully implemented in depression mobile apps, but not yet in weight loss apps. Objective: This study describes the development and feasibility testing of the Habit app, which was designed to automate problem-solving therapy for weight loss. Methods: Two iterative single-arm pilot studies were conducted to evaluate the feasibility and acceptability of the Habit app. In each pilot study, adults who were overweight or obese were enrolled in an 8-week intervention that included the Habit app plus support via a private Facebook group. Feasibility outcomes included retention, app usage, usability, and acceptability. Changes in problem-solving skills and weight over 8 weeks are described, as well as app usage and weight change at 16 weeks. Results: Results from both pilots show acceptable use of the Habit app over 8 weeks with on average two to three uses per week, the recommended rate of use. Acceptability ratings were mixed such that 54% (13/24) and 73% (11/15) of participants found the diet solutions helpful and 71% (17/24) and 80% (12/15) found setting reminders for habits helpful in pilots 1 and 2, respectively. In both pilots, participants lost significant weight (P=.005 and P=.03, respectively). In neither pilot was an effect on problem-solving skills observed (P=.62 and P=.27, respectively). Conclusions: Problem-solving therapy for weight loss is feasible to implement in a mobile app environment; however, automated delivery may not impact problem-solving skills as has been observed previously via human delivery. Trial Registration: ClinicalTrials.gov NCT02192905; https://clinicaltrials.gov/ct2/show/NCT02192905 (Archived by WebCite at http://www.webcitation.org/6zPQmvOF2) [JMIR Mhealth Uhealth 2018;6(6):e145]

Validating Fitbit Zip for monitoring physical activity of children in school: a cross-sectional study (2018)

BMC Public Health

Authors: Mooses, K., Oja, M., Reisberg, S., Vilo, J. and Kull, M.

Abstract

BACKGROUND Modern activity trackers, including the Fitbit Zip, enable the measurement of both the step count as well as physical activity (PA) intensities. However, there is a need for field-based validation studies in a variety of populations before using trackers for research. Therefore, the purpose of the current study was to investigate the validity of Fitbit Zip step count, moderate to vigorous physical activity (MVPA) and sedentary minutes, in different school segments in 3rd grade students. METHODS Third grade students (N = 147, aged 9-10 years) wore a Fitbit Zip and an ActiGraph GT3x-BT accelerometer simultaneously on a belt for five days during school hours. The number of steps, minutes of MVPA and sedentary time during class time, physical education lessons and recess were extracted from both devices using time filters, based on the information from school time tables obtained from class teachers. The validity of the Fitbit Zip in different school segments was assessed using Bland-Altman analysis and Spearman's correlation. RESULTS There was a strong correlation in the number of steps in all in-school segments between the two devices (r = 0.85-0.96, P < 0.001). The Fitbit Zip overestimated the number of steps in all segments, with the greatest overestimation being present in physical education lessons (345 steps). As for PA intensities, the agreement between the two devices in physical education and recess was moderate for MVPA minutes (r = 0.56 and r = 0.72, P < 0.001, respectively) and strong for sedentary time (r = 0.85 and r = 0.87, P < 0.001, respectively). During class time, the correlation was weak for MVPA minutes (r = 0.24, P < 0.001) and moderate for sedentary time (r = 0.57, P < 0.001). For total in-school time, the correlation between the two devices was strong for steps (r = 0.98, P < 0.001), MVPA (r = 0.80, P < 0.001) and sedentary time (r = 0.94, P < 0.001). CONCLUSION In general, the Fitbit Zip can be considered a relatively accurate device for measuring the number of steps, MVPA and sedentary time in students in a school-setting. However, in segments where sedentary time dominates (e.g. academic classes), a research-grade accelerometer should be preferred.

VALIDITY AND RELIABILITY OF THE FITBIT FLEX™ AND ACTIGRAPH GT3X+ AT JOGGING AND RUNNING SPEEDS. (2018)

International journal of sports physical therapy

Authors: Jones, D., Crossley, K., Dascombe, B., Hart, H.F. and Kemp, J.

Abstract

Background Monitoring levels of physical activity, as an outcome or in guiding rehabilitation, is challenging for clinicians. Personal activity monitors are increasing in popularity and provide potential to enhance rehabilitation protocols. However, research to support the validity and reliability of these devices at jogging and running speeds is limited. Purpose The purpose of this study was to evaluate the validity of the Fitbit Flex™ and ActiGraph GT3X + for measuring step count at jogging and running speeds. A secondary purpose was to examine inter-device reliability of the Fitbit Flex™. Study Design Cross-sectional study. Methods Thirty healthy participants aged between 19 and 50 years, completed a treadmill protocol at jogging and running speeds (8 km/h to 16 km/h). Treadmill speed was progressively increased by intervals of 2 km/h. Each interval was four minutes in duration with a two minute rest period between stages. Participants were encouraged to continue through the graded exercise test until they reached the maximum running speed that they felt they could maintain for four minutes. Step count data was collected for Fitbit Flex™ devices and the ActiGraph GT3X+. Video analysis of step count was used as the criterion measure. Results At speeds of 8 to 14 km/h Mean Absolute Percentage Errors were ≤1% for the Fitbit Flex™ and the ActiGraph GT3X + when compared to step count via video analysis. Standard Error of Measurement between the three Fitbit Flex™ devices was ≤ 7 steps for speeds of 8 to 14 km/h and varied between 9 to 19 steps at 16 km/h. Fitbit Flex™ devices showed good to excellent between device reliability at speeds of 8 to14 km/h (ICC 0.723 to 0.999; p ≤ 0.001). Greater variability was evident with the low participant numbers at 16 km/h (ICC 0.527 to 0.896; p ≥ 0.02). Conclusion Both the Fitbit Flex™ and the ActiGraph GT3X + provide a valid account of steps taken at jogging and running speeds up to 14 km/hr, attainable by non-elite runners on a treadmill. Fitbit Flex™ devices provide equivalent step count output to each other, enabling comparison between devices during treadmill jogging and running. Level of evidence 2b.

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Veterans’ Perspectives on Fitbit Use in Treatment for Post-Traumatic Stress Disorder: An Interview Study (2018)

JMIR Mental Health

Authors: Ng, A., Reddy, M., Zalta, A.K. and Schueller, S.M.

Abstract

Background: The increase in availability of patient data through consumer health wearable devices and mobile phone sensors provides opportunities for mental health treatment beyond traditional self-report measurements. Previous studies have suggested that wearables can be effectively used to benefit the physical health of people with mental health issues, but little research has explored the integration of wearable devices into mental health care. As such, early research is still necessary to address factors that might impact integration including patients' motivations to use wearables and their subsequent data. Objective: The aim of this study was to gain an understanding of patients’ motivations to use or not to use wearables devices during an intensive treatment program for post-traumatic stress disorder (PTSD). During this treatment, they received a complementary Fitbit. We investigated the following research questions: How did the veterans in the intensive treatment program use their Fitbit? What are contributing motivators for the use and nonuse of the Fitbit? Methods: We conducted semistructured interviews with 13 veterans who completed an intensive treatment program for PTSD. We transcribed and analyzed interviews using thematic analysis. Results: We identified three major motivations for veterans to use the Fitbit during their time in the program: increase self-awareness, support social interactions, and give back to other veterans. We also identified three major reasons certain features of the Fitbit were not used: lack of clarity around the purpose of the Fitbit, lack of meaning in the Fitbit data, and challenges in the veteran-provider relationship. Conclusions: To integrate wearable data into mental health treatment programs, it is important to understand the patient’s perspectives and motivations in using wearables. We also discuss how the military culture and PTSD may have contributed to our participants' behaviors and attitudes toward Fitbit usage. We conclude with possible approaches for integrating patient-generated data into mental health treatment settings that may address the challenges we identified. [JMIR Ment Health 2018;5(2):e10415]

We12BFit!-Improving lifestyle physical activity in children aged 7-12 years with developmental coordination disorder: protocol of a multicentre single-arm mixed-method study. (2018)

BMJ open

Authors: Braaksma, P., Stuive, I., Boomsma, H., van der Sluis, C.K., Schoemaker, M.M. and Dekker, R.

Abstract

INTRODUCTION Children with developmental coordination disorder (DCD) are less physically active than their typically developing peers. No substantiated interventions are available to address this issue. Therefore, this study aims to describe the design and rationale of (1) a family-focused intervention to increase motivation for physical activity (PA) and, indirectly, lifestyle PA in children aged 7-12 years with DCD and (2) the methods to examine its preliminary effectiveness and feasibility. METHODS AND ANALYSIS This intervention is the second part of a more comprehensive, multidisciplinary treatment called We12BFit! The intervention was developed using the steps of treatment theory which includes the concept of targets, mechanism of action and essential ingredients. The content of the intervention is based on the transtheoretical model of change (TTM). In the intervention, the motivation for PA will be targeted through application of behaviour change strategies that fit the stages of the TTM. The modes of delivery include: pedometer, poster, parent meeting, booklet and coaching. At least 19 children with DCD, aged 7-12 years, will be included from two schools for special education and two rehabilitation centres. The intervention will be evaluated using a single-arm mixed-method design. Effectiveness will be assessed at three instances by using ActiGraph accelerometers accompanied by an activity log. Feasibility will be assessed using interviews with the participants and coaches. This evaluation may add to our understanding of motivation for PA in children with DCD and may eventually improve the rehabilitation programme of children with DCD. ETHICS AND DISSEMINATION The study has been approved by the Medical Ethics Committee of the University Medical Center of Groningen (METc 2015.216). We will disseminate the final results to the public through journal publications and presentations for practice providers and scientists. A final study report will also be provided to funding organisations. PROTOCOL VERSION 4, 12 April 2018. TRIAL REGISTRATION NUMBER NTR6334; Pre-results.

Wearable Activity Tracker Use Among Australian Adolescents: Usability and Acceptability Study. (2018)

JMIR mHealth and uHealth

Authors: Ridgers, N.D., Timperio, A., Brown, H., Ball, K., Macfarlane, S., Lai, S.K., Richards, K., Mackintosh, K.A., McNarry, M.A., Foster, M. and Salmon, J.

Abstract

BACKGROUND Wearable activity trackers have the potential to be integrated into physical activity interventions, yet little is known about how adolescents use these devices or perceive their acceptability. OBJECTIVE The aim of this study was to examine the usability and acceptability of a wearable activity tracker among adolescents. A secondary aim was to determine adolescents' awareness and use of the different functions and features in the wearable activity tracker and accompanying app. METHODS Sixty adolescents (aged 13-14 years) in year 8 from 3 secondary schools in Melbourne, Australia, were provided with a wrist-worn Fitbit Flex and accompanying app, and were asked to use it for 6 weeks. Demographic data (age, sex) were collected via a Web-based survey completed during week 1 of the study. At the conclusion of the 6-week period, all adolescents participated in focus groups that explored their perceptions of the usability and acceptability of the Fitbit Flex, accompanying app, and Web-based Fitbit profile. Qualitative data were analyzed using pen profiles, which were constructed from verbatim transcripts. RESULTS Adolescents typically found the Fitbit Flex easy to use for activity tracking, though greater difficulties were reported for monitoring sleep. The Fitbit Flex was perceived to be useful for tracking daily activities, and adolescents used a range of features and functions available through the device and the app. Barriers to use included the comfort and design of the Fitbit Flex, a lack of specific feedback about activity levels, and the inability to wear the wearable activity tracker for water-based sports. CONCLUSIONS Adolescents reported that the Fitbit Flex was easy to use and that it was a useful tool for tracking daily activities. A number of functions and features were used, including the device's visual display to track and self-monitor activity, goal-setting in the accompanying app, and undertaking challenges against friends. However, several barriers to use were identified, which may impact on sustained use over time. Overall, wearable activity trackers have the potential to be integrated into physical activity interventions targeted at adolescents, but both the functionality and wearability of the monitor should be considered.

"Pre-Habilitation" of Frail Candidates for Lung Transplantation Using a Mobile Health Enabled Home-Based Intervention Is Feasible and Safe (2017)

American Journal of Respiratory and Critical Care Medicine

Authors: Singer, J., Soong, A., Bruun, A., Hays, S., Kukreja, J., Bracha, A., Chin, G., Wolters, P.J., Peters, M. and Garvey, C.M.

Abstract

Rationale: Frailty is prevalent in lung transplant candidates and is associated delisting or death on the waiting list. Studies in community dwelling older adults suggest that frailty may be reversible through exercise-based intervention. It is unknown whether such an intervention in advanced lung disease is safe. Herein, we report early feasibility and safety data on a pilot intervention to treat frailty in lung transplant candidates using novel mobile health technologies. Methods: In March 2016, we launched a pilot, home-based combined exercise and nutrition intervention in lung transplant candidates diagnosed with COPD or pulmonary fibrosis. We customized a commercially available telehealth platform (AidCube) originally designed for home-based pulmonary rehabilitation (PR). The platform features a participant-facing app and a web-based provider interface, allowing for real-time interaction and communication between participants and study personnel. In our protocol, an in-person assessment and training is performed and measures of frailty (Short Physical Performance Battery), disability, and health-related quality of life collected. Subjects are provided tablets loaded with the customized app and can choose from a tailored menu of exercises based on ATS/ERS PR recommendations. Subjects are taught how to safely perform the exercises in person and are provided Fitbit activity trackers. Once home, adherence, safety, and progress is assessed in real-time through AidCube, Fitbit and weekly phone check-ins. Based on participant feedback, exercises are progressed via the provider interface. After 8-weeks, measures of frailty, disability, HRQL, are reassessed. Results: To date, we have enrolled 15 participants (target n=24). Participants to date are 31% female with a mean age of 62 years (standard deviation [SD]=5), FEV1% predicted 48 (SD=27), and median LAS 35 (25, 75%: 33, 37). Over 209 participant-weeks of the intervention, we have observed no adverse events (i.e., falls/injuries, desaturations <85%, respiratory complications). Qualitatively, participants report the “app” platform is easy to use and that the embedded gamification features and Fitbit trackers help in motivation. Early adherence appears reasonable. Participants have completed a median of 44 exercises per week (95% confidence interval: 27, 55). Of the eight subjects who have completed the intervention, six adhered; of these, four demonstrated improvement in SPPB frailty by at least 1 point on a 12-point scale. Conclusions: Preliminarily, a home-based pre-habilitation program to treat frailty in lung transplant candidates using a novel mobile health technology appears feasible and safe. Also, our very early data support that frailty is modifiable in a population of adults with end-stage lung disease.

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A Bit of Fit: Minimalist Intervention in Adolescents Based on a Physical Activity Tracker. (2017)

JMIR mHealth and uHealth

Authors: Gaudet, J., Gallant, F. and Bélanger, M.

Abstract

BACKGROUND Only 5% of Canadian youth meet the recommended 60 minutes of moderate to vigorous physical activity (MVPA) per day, with leisure time being increasingly allocated to technology usage. Direct-to-consumer mHealth devices that promote physical activity, such as wrist-worn physical activity trackers, have features with potential appeal to youth. OBJECTIVE The primary purpose of this study was to determine whether a minimalist physical activity tracker-based intervention would lead to an increase in physical activity in young adolescents. A secondary aim of this study was to assess change in physical activity across a 7-week intervention, as measured by the tracker. METHODS Using a quasi-experimental crossover design, two groups of 23 young adolescents (aged 13-14 years) were randomly assigned to immediate intervention or delayed intervention. The intervention consisted of wearing a Fitbit-Charge-HR physical activity tracker over a 7-week period. Actical accelerometers were used to measure participants' levels of MVPA before and at the end of intervention periods for each group. Covariates such as age, sex, stage of change for physical activity behavior, and goal commitment were also measured. RESULTS There was an increase in physical activity over the course of the study period, though it was not related to overall physical activity tracker use. An intervention response did, however, occur in a subset of participants. Specifically, exposure to the physical activity tracker was associated with an average daily increase in MVPA by more than 15 minutes (P=.01) among participants who reported being in the action and maintenance stages of behavior change in relation to participation in physical activity. Participants in the precontemplation, contemplation, and preparation stages of behavior change had no change in their level of MVPA (P=.81). CONCLUSIONS These results suggest that physical activity trackers may elicit improved physical activity related behavior in young adolescents demonstrating a readiness to be active. Future studies should seek to investigate if integrating physical activity trackers as part of more intensive interventions leads to greater increases in physical activity across different levels of stages of behavior change and if these changes can be sustained over longer periods of time.

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A Community-Based Physical Activity Counselling Program for People With Knee Osteoarthritis: Feasibility and Preliminary Efficacy of the Track-OA Study (2017)

JMIR mHealth and uHealth

Authors: Li, L.C., Sayre, E.C., Xie, H., Clayton, C. and Feehan, L.M.

Abstract

Background: Physical activity can improve health outcomes in people with knee osteoarthritis (OA); however, participation in physical activity is very low in this population. Objective: The objective of our study was to assess the feasibility and preliminary efficacy of the use of wearables (Fitbit Flex) and telephone counselling by a physical therapist (PT) for improving physical activity in people with a physician-confirmed diagnosis of knee OA, or who have passed 2 validated criteria for early OA. Methods: We conducted a community-based feasibility randomized controlled trial. The immediate group (n=17) received a brief education session by a physical therapist, a Fitbit Flex activity tracker, and a weekly telephone call for activity counselling with the physical therapist. The delayed group (n=17) received the same intervention 1 month later. All participants were assessed at baseline (T0), and the end of 1 month (T1) and 2 months (T2). Outcomes were (1) mean moderate to vigorous physical activity time, (2) mean time spent on sedentary behavior, (3) Knee Injury and Osteoarthritis Outcome Score (KOOS), and (4) Partners in Health Scale. Feasibility data were summarized with descriptive statistics. We used analysis of covariance to evaluate the effect of the group type on the outcome measures at T1 and T2, after adjusting for blocking and T0. We assessed planned contrasts of changes in outcome measures over measurement periods. Results: We identified 46 eligible individuals; of those, 34 (74%) enrolled and no one dropped out. All but 1 participant adhered to the intervention protocol. We found a significant effect, with the immediate intervention group having improved in the moderate to vigorous physical activity time and in the Partners in Health Scale at T0 to T1 compared with the delayed intervention group. The planned contrast of the immediate intervention group at T0 to T1 versus the delayed group at T1 to T2 showed a significant effect in the sedentary time and the KOOS symptoms subscale, favoring the delayed group. Conclusions: This study demonstrated the feasibility of a behavioral intervention, supported by the use of a wearable device, to promote physical activity among people with knee OA.

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A Feasible and Effective Mobile Health Weight Loss Lifestyle Intervention for Filipinos With Type 2 Diabetes (2017)

Circulation

Authors: Bender, M.S., Cooper, B. and Arai, S.

Abstract

Introduction: Filipino Americans have the highest prevalence of obesity and type 2 diabetes (T2D) compared to Asian American subgroups placing them at high risk for cardiometabolic disease. Effective interventions are needed to reduce these health disparities. Mobile health (mHealth) weight loss lifestyle interventions have been effective in reducing cardiometabolic risks, but are untested among Filipinos, particularly with T2D. As prolific users of digital technology, Filipinos are ideal candidates for mHealth lifestyle interventions. Therefore, we conducted the PilAm Go4Health intervention study - a culturally adapted weight loss lifestyle intervention using mobile technology to reduce cardiometabolic risks among Filipinos with T2D. Objective: To demonstrate intervention feasibility and potential efficacy. Hypothesis: 1) participant retention rate will be greater than 80%; 2) Compared to the control, intervention group will have significantly greater reduction in: % weight loss, waist circumference, fasting plasma glucose, and HbA1; and greater increase in step-counts. Methods: Two-arm (intervention +active control groups) RCT compared a 3-month intervention (Fitbit accelerometer +mHealth app/diary +Facebook group) and control (Fitbit accelerometer). N=45 overweight Filipino adults with T2D were recruited from Northern California communities. Between group differences from baseline to 3-months were analyzed using: 1) multilevel regression for within-person change in weight and step-counts using a nonparametric bias-corrected bootstrapped 95% CI for the multilevel models, and 2) T-tests, ANOVA for waist circumference, fasting plasma glucose, and HbA1c (significance =ptextless0.05, 2-sided). Cohen's d was used for effect size analyses. Results: Randomized N=45 Filipinos (intervention =22 and control =23). Mean age was 58±10 years, 62% women, and retention rate=100%. There was significantly greater reduction in the intervention group compared to the control for: % weight (2.3% greater decrease, d=0.46); waist circumference (-2.68cm; d= 0.88); and fasting plasma glucose (-18.52mg/dl; d= -0.86). HbA1c group difference was not significant (-0.34%; ptextless 0.19). Step-counts significantly increased in the intervention group compared to control (3432 steps at endpoint; d=1.44). Conclusion: PilAm Go4Health intervention demonstrated excellent feasibility in recruitment and retention, and potential efficacy for reducing cardiometabolic risks in Filipinos with T2D. Results warrant further testing of this lifestyle intervention that may support translation to other at-risk diverse populations living with T2D.

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A Feasible and Efficacious Mobile-Phone Based Lifestyle Intervention for Filipino Americans with Type 2 Diabetes: Randomized Controlled Trial (2017)

JMIR Diabetes

Authors: Bender, M.S., Cooper, B.A., Park, L.G., Padash, S. and Arai, S.

Abstract

Background: Filipino Americans have a high prevalence of obesity, type 2 diabetes (T2D), and cardiovascular disease compared with other Asian American subgroups and non-Hispanic whites. Mobile health (mHealth) weight loss interventions can reduce chronic disease risks, but these are untested in Filipino Americans with T2D. Objective: The objective of this study was to assess feasibility and potential efficacy of a pilot, randomized controlled trial (RCT) of a culturally adapted mHealth weight loss lifestyle intervention (Pilipino Americans Go4Health [PilAm Go4Health]) for overweight Filipino Americans with T2D. Methods: This was a 2-arm pilot RCT of the 3-month PilAm Go4Health intervention (phase 1) with an active waitlist control and 3-month follow-up (phase 2). The waitlist control received the PilAm Go4Health in phase 2, whereas the intervention group transitioned to the 3-month follow-up. PilAm Go4Health incorporated a Fitbit accelerometer, mobile app with diary for health behavior tracking (steps, food/calories, and weight), and social media (Facebook) for virtual social support, including 7 in-person monthly meetings. Filipino American adults ≥18 years with T2D were recruited from Northern California. Feasibility was measured by rates of recruitment, engagement, and retention. Multilevel regression analyses assessed within and between group differences for the secondary outcome of percent weight change and other outcomes of weight (kg), body mass index (BMI), waist circumference, fasting plasma glucose, HbA1c, and steps. Results: A total of 45 Filipino American adults were enrolled and randomized. Mean age was 58 (SD 10) years, 62% (28/45) were women, and mean BMI was 30.1 (SD 4.6). Participant retention and study completion were 100%, with both the intervention and waitlist group achieving near-perfect attendance at all 7 intervention office visits. Groups receiving the PilAm Go4Health in phase 1 (intervention group) and phase 2 (waitlist group) had significantly greater weight loss, −2.6% (−3.9 to −1.4) and −3.3% (−1.8 to −4.8), respectively, compared with the nonintervention group, resulting in a moderate to small effect sizes (d=0.53 and 0.37, respectively). In phase 1, 18% (4/22) of the intervention group achieved a 5% weight loss, whereas 82% (18/22) maintained or lost 2% to 5% of their weight and continued to maintain this weight loss in the 3-month follow-up. Other health outcomes, including waist circumference, BMI, and step counts, improved when each arm received the PilAm Go4Health, but the fasting glucose and HbA1c outcomes were mixed. Conclusions: The PilAm Go4Health was feasible and demonstrated potential efficacy in reducing diabetes risks in overweight Filipino Americans with T2D. This study supports the use of mHealth and other promising intervention strategies to reduce obesity and diabetes risks in Filipino Americans. Further testing in a full-scale RCT is warranted. These findings may support intervention translation to reduce diabetes risks in other at-risk diverse populations. Trial Registration: Clinicaltrials.gov NCT02290184; https://clinicaltrials.gov/ct2/show/NCT02290184 (Archived by WebCite at http://www.webcitation.org/6vDfrvIPp) [JMIR Diabetes 2017;2(2):e30]

A Pilot Study to Assess the Feasibility and Impact of a Home Exercise Program on Heart Rate and Heart Rate Variability in Children with Muscular Dystrophy (P4.163) (2017)

Neurology

Authors: Zelikovich, A.S., Oswald, T. and Kuntz, N.L.

Abstract

Objective: To determine if a home exercise program is feasible and beneficial in a pediatric muscular dystrophy (MD) population. Background: Research has shown that children with MD exhibit tachycardia and decreased heart rate variability (HRV), sometimes reversible with aerobic exercise. Whether aerobic exercise will improve long-term clinical outcomes in children with MD is unknown. Feasibility and barriers with respect to a voluntary, aerobic home exercise program are poorly studied. Design/Methods: A 4-week voluntary game-based home exercise program was created and trialed by 12 children (3–11 yrs) with MD. Fitbit Charge HR bands were worn to track heart rate (HR). Satisfaction surveys and Pediatric Quality of Life Neuromuscular Module (Peds QOL:NM) were submitted weekly by parents. 24-hour Holter monitoring was performed concurrently with Fitbit in a subset of subjects. Results: 12 games were created to provide exercise at a mean of 25 minutes three times weekly (with 95% rate of positive feedback). 75% of the participants completed participation with 82% of total surveys returned. Peds QOL: NM demonstrated a high baseline quality of life without interval change. 60% of the HR recordings during exercise were adequate. These demonstrated tachycardia for age at baseline (mean 113 BPM) with a mean increase during exercise of 7 BPM. 24-hour Holter monitoring was performed on 3 subjects simultaneously wearing a Fitbit. Holter HR and Fitbit HR were comparable with Holter mean HR consistently higher than Fitbit mean HR (+2.0% to +8.4%). The average cost per exercise kit was $3.88. Conclusions: A novel, inexpensive aerobic exercise program was trialed allowing children with MD to exercise at home in an enjoyable, cost-effective manner. Fitbit Charge HR is an inexpensive, long term HR monitor that recorded values comparable to Holter HR monitoring. Fitbit HR averages are slightly lower than Holter monitoring likely due to inability to capture short bursts of tachycardia.

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A pragmatic, phase III, multisite, double-blind, placebo-controlled, parallel-arm, dose increment randomised trial of regular, low-dose extended-release morphine for chronic breathlessness: Breathlessness, Exertion And Morphine Sulfate (BEAMS) study protocol (2017)

BMJ Open

Authors: Currow, D., Watts, G.J., Johnson, M., McDonald, C.F., Miners, J.O., Somogyi, A.A., Denehy, L., McCaffrey, N., Eckert, D.J., McCloud, P., Louw, S., Lam, L., Greene, A., Fazekas, B., Clark, K.C., Fong, K., Agar, M.R., Joshi, R., Kilbreath, S., Ferreira, D. and Ekström, M.

Abstract

Introduction: Chronic breathlessness is highly prevalent and distressing to patients and families. No medication is registered for its symptomatic reduction. The strongest evidence is for regular, low-dose, extended- release (ER) oral morphine. A recent large phase III study suggests the subgroup most likely to benefit have chronic obstructive pulmonary disease (COPD) and modified Medical Research Council breathlessness scores of 3 or 4. This protocol is for an adequately powered, parallel-arm, placebo-controlled, multisite, factorial, block-randomised study evaluating regular ER morphine for chronic breathlessness in people with COPD. Methods and analysis: The primary question is what effect regular ER morphine has on worst breathlessness, measured daily on a 0–10 numerical rating scale. Uniquely, the coprimary outcome will use a FitBit to measure habitual physical activity. Secondary questions include safety and, whether upward titration after initial benefit delivers greater net symptom reduction. Substudies include longitudinal driving simulation, sleep, caregiver, health economic and pharmacogenetic studies. Seventeen centres will recruit 171 participants from respiratory and palliative care. The study has five phases including three randomisation phases to increasing doses of ER morphine. All participants will receive placebo or active laxatives as appropriate. Appropriate statistical analysis of primary and secondary outcomes will be used. Ethics and dissemination: Ethics approval has been obtained. Results of the study will be submitted for publication in peer-reviewed journals, findings presented at relevant conferences and potentially used to inform registration of ER morphine for chronic breathlessness.

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A Six-Week Supervised Exercise and Educational Intervention After Total Hip Arthroplasty: A Case Series (2017)

The International Journal of Sports Physical Therapy

Authors: Pozzi, F., Madara, K. and Zeni Jr, J.A.

Abstract

Background and Purpose: Most rehabilitation interventions after total hip arthroplasty (THA) are not designed to return patients to high-levels of physical activity and, thus, low levels of physical activity and residual weakness are common. The purpose of this case series was to describe the feasibility and preliminary efficacy of an exercise and education intervention for patients after THA who have already completed formal outpatient physical therapy. Study Design: Case series Case Description: Two participants underwent unilateral THA seven (case A) or eight (case B) months prior to the intervention. Individuals participated in 18 treatment sessions that included progressive aerobic and strengthening exercises and meetings with a health coach. Change in function, strength, and self-reported physical activity were measured. Outcomes 12 months after surgery were compared to a historical cohort of patients after THA. Outcome: There were no adverse events during the intervention. At the end of the intervention, hip and knee strength on the surgical side increased approximately 30% compared to baseline in both cases. Activity level, and recreational performance, including walking up stairs and hiking uphill (case A), and running and golfing (case B), improved by the end of the intervention. Most changes were maintained at follow-up, although hip strength for case B decreased 27% after discharge from the intervention. Outcomes for both cases exceeded historical averages for patients 12 months after THA, with the exception of strength in case B. Discussion: The exercise intervention was well tolerated and without negative effects in two participants. Both par-ticipants increased their ability to complete demanding recreational and sports-related activities, physical activity, and demonstrated improved hip abductor and knee extensor strength. Further research is needed to evaluate the implementation and effectiveness of similar interventions after THA. Acknowledgements: We would like to acknowledge Alan Jette, PT, PhD, FAPTA and Stefano Zaffagnini, MD for critically reviewing our work; Tara Leonard, MS who carried out the health coach portion of the intervention; and Michael Brian, PhD for performing the graded exercise tests.

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A technology-enabled Counselling program versus a delayed treatment control to support physical activity participation in people with inflammatory arthritis: study protocol for the OPAM-IA randomized controlled trial (2017)

BMC Rheumatology

Authors: Li, L.C., Feehan, L.M., Shaw, C., Xie, H., Sayre, E.C., Aviña-Zubeita, A., Grewal, N., Townsend, A.F., Gromala, D., Noonan, G. and Backman, C.L.

Abstract

Being physically active is an essential component of successful self-management for people with inflammatory arthritis; however, the vast majority of patients are inactive. This study aims to determine whether a technology-enabled counselling intervention can improve physical activity participation and patient outcomes. The Effectiveness of Online Physical Activity Monitoring in Inflammatory Arthritis (OPAM-IA) project is a community-based randomized controlled trial with a delayed control design. We will recruit 130 people with rheumatoid arthritis or systemic lupus erythematosus, who can be physically active without health professional supervision. Randomization will be stratified by diagnosis. In Weeks 1–8, participants in the Immediate Group will: 1) receive education and counselling by a physical therapist (PT), 2) use a Fitbit and a new web-based application, FitViz, to track and obtain feedback about their physical activity, 3) receive 4 biweekly follow-up calls from the PT. Those in the Delayed Group will receive the same program in Week 10. We will interview a sample of participants about their experiences with the intervention. Participants will be assessed at baseline, and Weeks 9, 18 and 27. The primary outcome measure is time spent in moderate/vigorous physical activity in bouts of ≥ 10 min, measured with a portable multi-sensor device in the free-living environment. Secondary outcomes include step count, time in sedentary behaviour, pain, fatigue, mood, self-management capacity, and habitual behaviour. A limitation of this study is that participants, who also administer the outcome measures, will not be blinded. Nonetheless, by customizing existing self-monitoring technologies in a patient-centered manner, individuals can be coached to engage in an active lifestyle and monitor their performance. The results will determine if this intervention improves physical activity participation. The qualitative interviews will also provide insight into a paradigm to integrate this program to support self-management. Date of last update in ClinicalTrials.gov: September 18, 2015. ClinicalTrials.gov Identifier: NCT02554474 .

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Acceptability of the Fitbit in behavioural activation therapy for depression: a qualitative study. (2017)

Evidence-based Mental Health

Authors: Chum, J., Kim, M.S., Zielinski, L., Bhatt, M., Chung, D., Yeung, S., Litke, K., McCabe, K., Whattam, J., Garrick, L., O'Neill, L., Goyert, S., Merrifield, C., Patel, Y. and Samaan, Z.

Abstract

INTRODUCTION Major depressive disorder is characterised by low mood and poor motivation. Literature suggests that increased physical activity has positive effects on alleviating depression. Fitness-tracking devices may complement behavioural activation (BA) therapy to improve physical activity and mental health in patients with depression. OBJECTIVES To understand patients' perceived benefit from the Fitbit and explore themes associated with patient experiences. To compare perceived benefit, patient factors, Fitbit usage and Beck's Depression Inventory (BDI) scores. METHODS Semistructured interviews were conducted with patients (n=36) who completed a 28-week BA group programme in a mood disorders outpatient clinic. All patients were asked to carry a Fitbit One device. We conducted thematic analyses on the interviews and exploratory quantitative analyses on patient characteristics, Fitbit usage, steps recorded, perceived benefit and BDI scores. FINDINGS Twenty-three patients found the Fitbit helpful for their physical activity. Themes of positive experiences included self-awareness, peer motivation and goal-setting opportunities. Negative themes included inconvenience, inaccuracies and disinterest. Age, baseline and change in BDI scores, prior physical activity goals and familiarity with technology were not associated with perceived benefit from the Fitbit or usage. Perceived benefit was significantly (p<0.01) associated with usage. CONCLUSIONS Overall, the Fitbit is an acceptable tool to complement BA therapy for patients with depression. Many positive themes were concordant with current literature; however, patients also reported negative aspects that may affect use. CLINICAL IMPLICATIONS Clinicians and researchers should consider both strengths and limitations of activity trackers when implementing them to motivate patients with depression. TRIAL REGISTRATION NUMBER NCT02045771; Pre-results.

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Accuracy And Reliability Of The Fitbit Charge? Activity Tracker Among Older Adults (2017)

Medicine & Science in Sports & Exercise

Authors: Powers, M., Smith, M., Henderson, O. and Bodman, T.

Abstract

Wearable technology, including activity trackers, remains a top fitness trend world-wide; however, the ability of individual activity trackers to accurately and consistently record physical activity remains unknown. PURPOSE: To evaluate the accuracy and reliability of step counts from the Fitbit Charge™ among older adults. METHODS: Thirteen participants with a mean age of 70.38 ±4.27 years volunteered to participate and completed all testing. Participants completed a 96 meter walk around a gymnasium while wearing the Fitbit Charge™ activity tracker. Step counts on the activity tracker were recorded before and after the walk to determine the step count. The walk was also video recorded to determine the actual number of steps taken during the walk. Step counts from video analysis were confirmed by two researchers. The same procedures were repeated on a second, non-consecutive day of testing to determine the reliability of the activity tracker. Accuracy of the activity tracker was determined by comparing step counts to the observed step counts from each testing session. The reliability of the activity tracker was determined by correlation analysis and comparison of step counts from the first testing session to the second testing session. RESULTS: The activity tracker significantly underestimated observed steps at both testing sessions by 21.31 steps and 22.62 steps, respectively (p < .05). No difference in step count from the activity tracker was seen from session one to session two (151.85 steps vs. 152.54 steps, p > .05); however, the correlation between the two sessions was only moderate, r = .55, p = .05. CONCLUSION: Among older adults, the Fitbit Charge™ appears to underestimate steps taken even over a short distance. The reliability of the Fitbit Charge™ is questionable given only a moderate correlation between sessions. While preliminary, these results call into question the accuracy and reliability of daily step counts from the Fitbit Charge™. It is suggested that all new activity trackers to hit the market are given careful study to determine their ability to accurately measure daily activity.

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Accuracy of Accelerometer (Fitbit® ChargeHR™) Measured Distance and Heart Rate in Patients with Pulmonary Arterial Hypertension (2017)

American Journal of Respiratory and Critical Care Medicine

Authors: Chowdhury, A., Sehgal, S., Rabih, F., Gadre, A. and Highland, K.B.

Abstract

Journal of Respiratory and Critical Care MedicineRationale: Functional capacity assessment in patients with pulmonary arterial hypertension (PAH) is used to establish treatment goals and prognoses. Higher resting heart rate and poor heart rate recovery after activity has been associated with worse outcomes. Devices that can accurately monitor heart rate and activity can thus be valuable to monitor patients with PAH. Accelerometers measure movement using a piezo-electric crystal and can quantify activity as steps. Several accelerometers can monitor heart rate using optical blood flow sensing by photoplethysmography. Accelerometers have been validated to measure step count in healthy adults and patients with COPD. Studies validating distance and heart rate (HR) measured by activity monitors are discrepant. Validity in patients with PAH has not been studied. The Fitbit® ChargeHR™ is a “watch” type activity monitor that can continuously measure step count and heart rate. It uses height to estimate gait length and calculates distance walked. We examined the accuracy of this device in measuring distance walked and HR at rest and after exercise in patients with PAH. Methods: Thirty patients with WHO Group I PAH were enrolled. Subjects wore a Fitbit® ChargeHR™ during a 6 minute walk test (6MWT). Distance and HR as determined by the Fitbit® and 6MWT were recorded. HR measured using pulse oximetry was used at the reference. The Fitbit® failed to record steps if patients used a walker (n = 6), and these data were not analyzed. The concordance correlation coefficient (CCC) was used to compare the accelerometer with reference values. Results: 30 patients with WHO Group I PAH (23 idiopathic and 7 connective tissue disease), with a mean age 50.49 ± 12.97 were enrolled in the study. Mean six minute walk distance was 368.6 ± 144 m, WHO functional class was I - 0%, II - 56%, III - 34.9 %, and IV - 8.7% The distance walked as determined by the accelerometer did not correlate with distance measured in the 6MWT (CCC 0.52, 95% CI [0.19, 0.74]). Heart rate measured by the Fitbit® did not correlate with HR measured by pulse oximetry at rest or after exertion (CCC and [95% CI] were 0.57 [0.28, 0.76] and 0.24 [-0.03, 0.47]. Conclusions: We demonstrate that the Fitbit® ChargeHR™ did not accurately determine walk distance or resting heart rate in a controlled test environment in patients with WHO Group I PAH. Reported HR and distance walked should be interpreted with caution in patients with PAH.

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Accuracy of Consumer Monitors for Measuring Sleep Across Seven Nights (2017)

Sleep

Authors: Nowakowski, S., Grandner, M., Stout-Aguilar, J., Meers, J., Lewis-Powell, Z., Swartz, M., Choi, H. and Lyons, E.

Abstract

Introduction: Sleep and fitness trackers available to the consumer market show promise for measuring sleep. However, there are few published studies examining their accuracy compared with well-validated actigraphy devices for multiple nights outside the sleep laboratory. The purpose of this study was to evaluate the reliability and validity of several commercially-available devices compared to a well-validated actigraphy device. Methods: Healthy adults (N=40, mean age= 42?±?14, 50% female) wore a Fitbit Flex, Jawbone Up24, Misfit Shine, and Actiwatch-2 (AW-2) on the same wrist for seven consecutive 24-hour periods. Outcome variables included total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE) averaged over 7 nights. Both “Normal” and “Sensitive” sleep-recording Fitbit modes were examined. Each commercial monitor was compared with AW-2 using paired t-test and Bland-Altman concordance analyses. Clinical acceptance was defined a priori as =60 minutes difference between devices for TST and WASO, and =10% difference for SE. Results: Fitbit (normal), Jawbone, and Misfit were in the clinically acceptable range for TST, with Fitbit (normal) and Misfit overestimating by 2 minutes and 60 minutes, respectively; and Jawbone underestimating by 15 minutes compared with AW-2 (m=406?±?47 minutes). Fitbit (sensitive) overestimated by 160 minutes. All devices met clinically acceptable criteria but underestimated WASO by 13 minutes (Jawbone), 21 minutes (Fitbit sensitive), 23 minutes (Fitbit normal), and 25 minutes (Misfit) compared to AW-2 (m=38?±?15 minutes). Jawbone and Fitbit (normal) met clinically acceptable criteria for SE, with both devices overestimating by 4% and 5%, respectively compared to AW-2 (m=85?±?6%). Misfit overestimated by 12% and Fitbit (sensitive) underestimated by 30%. Conclusion: Fitbit (normal) and Jawbone accelerometers provided clinically comparable result for TST, WASO, and SE when compared to AW-2. Misfit met criteria for TST and WASO but not SE. Fitbit (sensitive) performed poorest. Further research is needed to reevaluate these findings with newer models.

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Accuracy of Fitbit Activity Trackers During Walking in a Controlled Setting (2017)

Medicine & Science in Sports & Exercise

Authors: Gamez, J.L., Gonzalez, J., Leyva, P., Figueroa, I.A., Lucio, N., Salazar, V.E., Salazar, C., Garcia, M. and Funk, M.D.

Abstract

BACKGROUND: Activity trackers are widely used to measure daily physical activity. Many devices have been shown to measure steps more accurately at higher intensities, however, it is also important to determine accuracy at a walking pace. PURPOSE: To assess 6 popular activity trackers at measuring steps while walking on a treadmill. METHODS: Twenty-six college students (Mean±SD; 22.1±3.7yrs; 25.1±4.0kg/m2; 13 male) walked 500 steps at 3mph on a treadmill while wearing 6 different activity trackers (Pedometer, Fitbit Blaze, Charge HR, Alta, Flex, Zip, One). The Charge HR was placed two fingers above the right wrist while the Flex was next to the wrist bone. The Blaze was placed two fingers above the left wrist while the Alta was next to the wrist bone. The Fitbit Zip and the One were aligned with the hip bone on the left and right waistband respectively. A trained researcher using a hand tally counter counted the steps. Missing values were replaced with the mean value for that device. Step counts were correlated between Fitbit devices and the pedometer and tally counter using Pearson correlations. Significance was set at ptextless0.05. Mean bias scores were calculated between the step counts for each device and the tally counter. Mean Absolute Percent Error (MAPE) values were also calculated for each device relative to the tally counter. RESULTS: Fitbit Zip and One were significantly correlated with the tally counter (r=0.50, ptextless0.05; r=0.68, ptextless0.01, respectively) while the other devices were not significantly correlated. Mean bias and MAPE values were as follows: Fitbit Zip and One were within one half percent of actual steps while wrist-worn Fitbits ranged from 7.0-19.7% from actual step counts. CONCLUSION: Consistent with previous research, activity trackers worn at the waist provide the most accurate step counts compared to wrist-worn models. Differences found in wrist-worn models may result in significant over- or underestimation of activity levels when worn for long periods of time.

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Accuracy of Fitbit Charge 2 Worn at Different Wrist Locations During Exercise (2017)

Medicine & Science in Sports & Exercise

Authors: Salazar, V.E., Lucio, N.D. and Funk, M.D.

Abstract

Many newly released activity monitors use heart rate measured at the wrist to estimate exercise intensity, however, where the device is placed on the wrist may affect accuracy of the measurement. PURPOSE: To determine whether the Pure Pulse technology on the Fitbit Charge 2 will show different heart rate readings when placed on the recommended exercise position compared to the all-day wear position at various exercise intensities. METHODS: Thirty five participants (MEAN ± SD; 22.0 ± 2.9yrs; 23.9 ± 2.6kg/m2; 18 male) consented to participate in a single visit where two Fitbit Charge 2 devices were placed on the non-dominant wrist. Fitbit A was placed 2-3 fingers above the wrist bone. Fitbit B was placed directly above the wrist bone. The treadmill was set at 3 mph with 0% grade. Participants remained at this speed for 4 minutes. Heart rate measurements were taken at the last 10 seconds of each stage from both Fitbits and a polar heart rate monitor (chest strap). The same procedure was followed for 5 and 6 mph. Statistical analyses were performed using IBM SPSS 23.0. A Two-way (speed x location) Repeated Measures ANOVA was used to examine mean differences. Pairwise comparisons with Bonferroni correction were used in post-hoc analysis. Pearson correlations and mean bias between polar heart rate monitor and activity monitors were also calculated for each speed. RESULTS: Repeated Measures ANOVA found significant differences between speeds (ptextless0.01) and location (ptextless0.01), but not for the interaction (p=0.234). Pairwise comparisons indicated significant differences between each speed (ptextless0.01) and between the polar monitor and Fitbit B (ptextless0.05), but not between the polar monitor and Fitbit A (p=0.608). Pearson correlations indicated strong correlations between each Fitbit and the polar monitor (r= .58-.91; all ptextless0.01). Mean bias decreased as speed increased for Fitbit A (mean bias bpm ± SD; -1.1 ± 5.4; -1.9 ± 9.5; -0.4 ± 6.9; -0.3 ± 7.3 for resting, 3mph, 5mph, 6mph respectively) while mean bias for Fitbit B increased as speed increased (-2.8 ± 8.8; -3.1 ± 11.1; -3.9 ± 14.6; -6.7 ± 14.3 for resting, 3mph, 5mph, 6mph respectively). CONCLUSION: Wrist-worn heart rate monitors appear to provide values adequate for recreational use, however, following recommended guidelines on wear-position may impact heart rate readings.

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Accuracy of Smartwatches in Assessing College Students’ Energy Expenditure in Exercise with Different Intensities (2017)

Medicine & Science in Sports & Exercise

Authors: Gao, Z., Li, X., Zeng, N., Pope, Z., Yang, H., Liu, W., Xiong, H., Chen, Y., Li, J. and He, W.

Abstract

PURPOSE: Despite the recent prevalence of health wearable devices (e.g., smartwatches), the validity and reliability of smartwatches’ physiological outcomes remain largely unexplored. This study was designed to examine the accuracy of the Microsoft Band (MS), Fitbit Surge HR (FB), TomTom Cardio Watch (TT) and Apple Watch (AW) in assessing energy expenditure (EE) during three exercise sessions with different intensities. METHODS: Participants were 25 college students (12 males; Mage= 23.52, SD = ± 1.04) from Southcenter region in China. They completed three separate 10-minute exercise sessions at light physical activity (LPA, walking at 3.0 km/h), moderate PA (MPA, running at 5.0 km/h), and vigorous PA (VPA, running at 7.0 km/h) conditions on the Hpcosmos treadmill at a highly controlled laboratory. In this study, the AW and TT were placed on the right wrist while the FB and MS were worn on the left wrist. All demographic information (i.e., height, weight, age, gender) was loaded onto each smartwatch prior to testing. EEs of smartwatches were then validated against EE data from a Actigraph wGT3X accelerometer worn on the right side of waist. RESULTS: ANOVAs with repeated measures revealed significant differences between smartwatches for EE, F(9, 16)=45.73, p<0.01, ?2=0.98. When validated against accelerometer, post-hoc comparisons suggested significantly different EE assessments for the FB at LPA and MPA conditions (p<0.01), and for MS and FB at the VPA (p<0.01). Interclass correlations between the accelerometer and smartwatches revealed reliability for EE for the TT at LPA (r=0.65, p<0.01), for the FB, TT and AW at MPA (r=0.53-0.59, p<0.01), and for MS, FB and TT at VPA (r=0.59-0.65, p<0.01). However, only the TT demonstrated excellent agreement with the accelerometer at LPA with coefficient of variation of 2.0%. Additionally, Bland-Altman plots yielded satisfactory precision/no bias for FB and TT measurements against the accelerometers at all conditions (p<0.05), for MS at LPA and VPA (p<0.05), and for AW at VPA (p < 0.05). CONCLUSIONS: Findings suggested EE measurements of smartwatches are far from ideal in terms of validity and reliability. In this study the most valid and reliable measurements were from the TT. Future study may investigate the validity and reliability of smartwatch measurements in everyday life.

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Accuracy of Wearable Devices for Determining Physiological Measures during Different Physical Activities (2017)

Medicine & Science in Sports & Exercise

Authors: Boudreaux, B.D., Cormier, C.L., Williams, B.M., Hebert, E.P. and Kraemer, R.R.

Abstract

PURPOSE: Wearable technology is ACSM's number one 2016-2017 fitness trend. The accuracy of these devices has yet to be firmly established. The objective of the study was to determine the validity of wearable devices' assessment of step count, heart rate (HR) and caloric expenditure (KCAL) during various physical activities. METHODS: Thirty college students (19 female, 11 male) engaged in 3 activity sessions (sweeping with a broom and dustpan, climbing stairs, and walking 1/4 mile) while wearing an Apple Watch Sport, Fitbit Charge HR, Accusplit Hip Pedometer, and iPhone 6 Plus. Step counts from devices were compared to those objectively recorded using a tally counter. Subjects also completed a treadmill graded exercise test during which HR and KCAL were reported by an Apple Watch Sport, Fitbit Charge HR, and Polar T-31. Values were compared to those from a six-lead ECG and metabolic analyzer. HR was recorded at rest and during each stage. KCAL was determined at the end of the protocol. RESULTS: Correlations between objective step counts and from the devices were: walking (.08 to .84), stair climbing (.12 to .90), and sweeping (.12 to .70). No device was accurate across all activities. The most accurate devices for activities were: walking (Apple Watch, r=.84); stair climbing (iPhone, r=.90); sweeping (Fitbit, r=.70). During the treadmill test, correlations between HR assessed via ECG and devices were: Apple Watch (.76 to .99), Polar T-31 (.72 to .94), and Fitbit (.19 to .98). Heart rate accuracy across the session was highest in the Apple Watch. KCAL from neither the Apple Watch (r=.63) nor Fitbit (r=.48) had a high correlational value to that from the metabolic analyzer. CONCLUSIONS: Fitness-related values provided by wearable devices had varying levels of accuracy when compared to objective step counts, HR and KCAL assessed by calibrated scientific equipment. Accuracy of step counts varied by activity and was higher across activities in the iPhone. HR reported from wearable devices, similarly, had varying levels of accuracy, with the Apple Watch being most accurate across a graded exercise test. Fitness-related information from wearables that are not medical devices and should be considered as estimates and used for motivation. Further validation of these devices should include a variety of physical activity modalities.

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Adaptive goal setting and financial incentives: a 2 × 2 factorial randomized controlled trial to increase adults' physical activity (2017)

BMC Public Health

Authors: Adams, M.A., Hurley, J.C., Todd, M., Bhuiyan, N., Jarrett, C.L., Tucker, W.J., Hollingshead, K.E. and Angadi, S.S.

Abstract

Background: Emerging interventions that rely on and harness variability in behavior to adapt to individual performance over time may outperform interventions that prescribe static goals (e.g., 10,000 steps/day). The purpose of this factorial trial was to compare adaptive vs. static goal setting and immediate vs. delayed, non-contingent financial rewards for increasing free-living physical activity (PA). Methods: A 4-month 2 × 2 factorial randomized controlled trial tested main effects for goal setting (adaptive vs. static goals) and rewards (immediate vs. delayed) and interactions between factors to increase steps/day as measured by a Fitbit Zip. Moderate-to-vigorous PA (MVPA) minutes/day was examined as a secondary outcome. Results: Participants (N = 96) were mainly female (77%), aged 41 ± 9.5 years, and all were insufficiently active and overweight/obese (mean BMI = 34.1 ± 6.2). Participants across all groups increased by 2389 steps/day on average from baseline to intervention phase (p textless .001). Participants receiving static goals showed a stronger increase in steps per day from baseline phase to intervention phase (2630 steps/day) than those receiving adaptive goals (2149 steps/day; difference = 482 steps/day, p = .095). Participants receiving immediate rewards showed stronger improvement (2762 step/day increase) from baseline to intervention phase than those receiving delayed rewards (2016 steps/day increase; difference = 746 steps/day, p = .009). However, the adaptive goals group showed a slower decrease in steps/day from the beginning of the intervention phase to the end of the intervention phase (i.e. less than half the rate) compared to the static goals group (-7.7 steps vs. -18.3 steps each day; difference = 10.7 steps/day, p textless .001) resulting in better improvements for the adaptive goals group by study end. Rate of change over the intervention phase did not differ between reward groups. Significant goal phase x goal setting x reward interactions were observed. Conclusions: Adaptive goals outperformed static goals (i.e., 10,000 steps) over a 4-month period. Small immediate rewards outperformed larger, delayed rewards. Adaptive goals with either immediate or delayed rewards should be preferred for promoting PA.

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Aerobic exercise training in children and adolescents with inflammatory bowel disease: Influence on psychological functioning, sleep and physical performance – An exploratory trial (2017)

Mental Health and Physical Activity

Authors: Mählmanna, L., Gerber, M., Furlano, R.I., Legeret, C., Kalak, N., Holsboer-Trachsler, E. and Brand, S.

Abstract

People with Inflammatory Bowel Disease (IBD) are at risk for mental health issues, poor sleep quality and limited engagement in physical activity (PA). Standard treatment consists of immune modulating pharmaceuticals though evidence is growing that aerobic exercise training (AET) could serve as an adjuvant option to reduce disease symptoms and improve mental health. The aim of the present exploratory trial was to investigate possible AET effects on psychological functioning, symptoms of depression, sleep and physical activity in paediatric patients with IBD. Twenty-one paediatric patients with IBD and 23 gender- and age-matched healthy controls (HC) were assessed. The IBD group was further split into a “remission-group” (IBD-RE; n = 14) and an “active disease group” (IBD-AD; n = 7). All participants completed an 8-week AET exergame intervention reaching 60–80% of maximum heart rate for 5 days per week. At baseline and after 8 weeks, psychological functioning, depressive symptoms, objective sleep EEG, subjective sleep and objective and subjective PA were assessed. AET improved the exercise capacity of all participants. Self-reported fitness and daily physical activity increased in IBD-AD, but not in IBD-RE and HC. No improvements were observed for psychological functioning, depressive symptoms or subjective sleep. Objective sleep improved, deep sleep increased, light sleep decreased, and in the IBD-AD group the number of arousals after sleep onset decreased. Descriptively, the IBD-AD group reported lower psychological functioning and poorer subjective sleep quality. Among paediatric patients with IBD and healthy controls, an exergaming intervention has the potential to improve exercise capacity, self-reported fitness, daily physical activity, and aspects of objective sleep. Results suggest that children and adolescents in an active state of IBD are at increased risk of poor psychological functioning and poor sleep quality.

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An Examination of Body Mass Index Influence on Activity Tracker Accuracy (2017)

Medicine & Science in Sports & Exercise

Authors: Dondzila, C., Johnson, H. and Steckel, M.

Abstract

A variety of activity trackers with evolving technology are commercially available, yet it remains uncertain the influence body size has on these devices' accuracy (as previous activity trackers have been), which would compromise their generalizability. PURPOSE: To examine the accuracy of consumer-grade activity trackers in quantifying steps and moderate-vigorous physical activity (MVPA) engagement in free-living conditions in a diverse sample of body mass index (BMI) categories. METHODS: Sixty individuals (21.1 ± 1.5 years, 2.3 ± 0.2 ft stride length) across three BMI categories (“Normal” [n=25]: 20-24.9 kg/m2; “Overweight” [n=22]: 25-29.9 kg/m2; “Obese” [n=13]: =30 kg/m2) wore four activity trackers during one 24-hour day (wear time 12.7 ± 1.9 hours). On the non-dominant side of the body, the Fitbit Charge HR (Charge) and Jawbone UP3 (UP3) were worn on the wrist and the Fitbit One (ONE) on the waist, with the NL1000 activity tracker (NL; serving as the criterion device) worn on the dominant side of the waist. Mixed between-within ANOVA analyses were performed to examine differences in steps and MVPA for the activity trackers across three BMI categories. RESULTS: There were no differences in steps or MVPA for the individual devices across BMI categories. In the Normal group, the UP3 (6667 ± 3366 steps) and ONE (7400 ± 8135 steps) underestimated steps (p=.000), compared to the NL (8135 ± 3562 steps). Similarly, in the Overweight group, the UP3 (8799 ± 3986 steps) and ONE (9019 ± 3841 steps) underestimated steps (NL 9312 ± 3986 steps, both < .05). In the Obese group the Charge overestimated steps (8847 ± 4168, < .05) and the ONE underestimated steps (7726 ± 3791, < .05), compared to the NL (8224 ± 4264 steps). The UP3 overestimated MVPA in the Normal group (67.7 ± 44.3 minutes), compared to the NL (27.6 ± 16.3, p=.000). In both the Overweight and Obese groups, the UP3 overestimated MVPA (Overweight: 81.5 ± 44.3 minutes, Obese: 77.5 ± 39.4 minutes, both p=.000), whereas the ONE underestimated MVPA (Overweight: 25.9 ± 26.5 minutes, Obese: 19.5 ± 25.3 minutes, both < .05), compared to the NL (Overweight: 36.6 ± 19.2 minutes, Obese: 31.6 ± 27.3 minutes). CONCLUSION: Within BMI groups, The UP3 underestimated steps and overestimated MVPA, the ONE underestimated steps and MVPA, whereas the Charge performed relatively well for both measures.

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Assessing the Benefits and Use of Gain-Framed Text Messaging to Improve Physical Activity in Advanced Stage Lung Cancer (2017)

Chest

Authors: Bade, B., Pastis, A., Owens, L., Hyer, J. and Silvestri, G.

Abstract

PURPOSE: Physical activity (PA) is a potential therapy to improve quality of life (QoL) in patients with advanced stage lung cancer (LC). Many regimens have been studied, but no PA regimen has been shown to be both beneficial and sustainable. We have previously used weekly phone calls to deliver PA goals. We hypothesize that a walking-based PA regimen using gain-framed text messaging will improve PA levels more effectively than weekly phone calls. METHODS: In patients with advanced stage LC, we implemented a Patient-Centered Activity Regimen (PCAR) utilizing a FitBit Flex® (San Francisco, CA) accelerometer, an educational session at enrollment, individualized walking goals, and twice daily gain-framed text messages. Feedback surveys were collected at the end of the intervention. Over a 4 week period, activity levels were compared between the PCAR group (n=15) and prior efforts using weekly phone calls (n=29). Data collection and likelihood of increasing PA were compared, and a repeated measures, mixed-effects model was constructed. RESULTS: Compared to those receiving weekly phone calls, subjects receiving twice daily gain-framed text messages more frequently used the device (100% vs 76%), increased their step count (67% vs 34%), and less frequently had missing data (12% vs 37%). Scatterplots revealed “more active” and “less active” groups. Participants were grouped into “more active” and “less active” groups based on above- or below-average step counts at baseline. The “less active” group improved their PA level whereas the “more active” group became less active. Most subjects (92%) found the intervention helpful and would participate in another activity study. Most subjects would prefer individualized (rather than group) PA interventions (83%) and to be motivated via daily text messages (55%) that are sent at noon (55%). CONCLUSIONS: In this small cohort, compared to weekly phone calls, twice daily gain-framed text messaging (1) improves data collection, (2) is more likely than weekly phone calls to improve PA (especially in “less active” subjects), and (3) has high patient satisfaction scores. Gain-framed text messaging appears to be an effective way to motivate patients with advanced stage LC to exercise. Future studies should further evaluate the benefits of walking-based PA in this group as well as the differences between the “more active” and “less active” groups. CLINICAL IMPLICATIONS: This study will help inform future efforts to motivate patients with advanced stage lung cancer toward exercise.

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Assessing the Influence of a Fitbit Physical Activity Monitor on the Exercise Practices of Emergency Medicine Residents: A Pilot Study (2017)

JMIR mHealth and uHealth

Authors: Schrager, J.D., Shayne, P., Wolf, S., Das, S., Patzer, R.E., White, M. and Heron, S.

Abstract

Background: Targeted interventions have improved physical activity and wellness of medical residents. However, no exercise interventions have focused on emergency medicine residents. Objective: This study aimed to measure the effectiveness of a wearable device for tracking physical activity on the exercise habits and wellness of this population, while also measuring barriers to adoption and continued use. Methods: This pre-post cohort study enrolled 30 emergency medicine residents. Study duration was 6 months. Statistical comparisons were conducted for the primary end point and secondary exercise end points with nonparametric tests. Descriptive statistics were provided for subjective responses. Results: The physical activity tracker did not increase the overall self-reported median number of days of physical activity per week within this population: baseline 2.5 days (interquartile range, IQR, 1.9) versus 2.8 days (IQR 1.5) at 1 month (P=.36). There was a significant increase in physical activity from baseline to 1 month among residents with median weekly physical activity level below that recommended by the Centers for Disease Control and Prevention at study start, that is, 1.5 days (IQR 0.9) versus 2.4 days (IQR 1.2; P=.04), to 2.0 days (IQR 2.0; P=.04) at 6 months. More than half (60%, 18/30) of participants reported a benefit to their overall wellness, and 53% (16/30) reported a benefit to their physical activity. Overall continued use of the device was 67% (20/30) at 1 month and 33% (10/30) at 6 months. Conclusions: The wearable physical activity tracker did not change the overall physical activity levels among this population of emergency medicine residents. However, there was an improvement in physical activity among the residents with the lowest preintervention physical activity. Subjective improvements in overall wellness and physical activity were noted among the entire study population. [JMIR Mhealth Uhealth 2017;5(1):e2]

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Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors (2017)

PLOS ONE

Authors: Chowdhury, E.A., Western, M.J., Nightingale, T.E., Peacock, O.J. and Thompson, D.

Abstract

Wearable physical activity monitors are growing in popularity and provide the opportunity for large numbers of the public to self-monitor physical activity behaviours. The latest generation of these devices feature multiple sensors, ostensibly similar or even superior to advanced research instruments. However, little is known about the accuracy of their energy expenditure estimates. Here, we assessed their performance against criterion measurements in both controlled laboratory conditions (simulated activities of daily living and structured exercise) and over a 24 hour period in free-living conditions. Thirty men (n = 15) and women (n = 15) wore three multi-sensor consumer monitors (Microsoft Band, Apple Watch and Fitbit Charge HR), an accelerometry-only device as a comparison (Jawbone UP24) and validated research-grade multi-sensor devices (BodyMedia Core and individually calibrated Actiheart™). During discrete laboratory activities when compared against indirect calorimetry, the Apple Watch performed similarly to criterion measures. The Fitbit Charge HR was less consistent at measurement of discrete activities, but produced similar free-living estimates to the Apple Watch. Both these devices underestimated free-living energy expenditure (-394 kcal/d and -405 kcal/d, respectively; Ptextless0.01). The multi-sensor Microsoft Band and accelerometry-only Jawbone UP24 devices underestimated most laboratory activities and substantially underestimated free-living expenditure (-1128 kcal/d and -998 kcal/d, respectively; Ptextless0.01). None of the consumer devices were deemed equivalent to the reference method for daily energy expenditure. For all devices, there was a tendency for negative bias with greater daily energy expenditure. No consumer monitors performed as well as the research-grade devices although in some (but not all) cases, estimates were close to criterion measurements. Thus, whilst industry-led innovation has improved the accuracy of consumer monitors, these devices are not yet equivalent to the best research-grade devices or indeed equivalent to each other. We propose independent quality standards and/or accuracy ratings for consumer devices are required.

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Comparison Between SenseWear and FitBit Physical Activity Monitors in Chronic Obstructive Pulmonary Disease (2017)

American Journal of Respiratory and Critical Care Medicine

Authors: Fuhr, D., Michaelchuk, W. and Stickland, M.

Abstract

Introduction: Higher physical activity levels have been shown to reduce the likelihood of hospital readmission in chronic obstructive pulmonary disease (COPD). Improving physical activity levels may be an effective disease management strategy, thus accurate physical activity monitors (PAMs) are needed.The Sensewear Mini armband (SWM), a relatively expensive PAM, has been shown to provide accurate estimations of energy expenditure,but underestimate step count in patients with COPD. The Fitbit Flex (FB), a relatively inexpensive and more accessible PAM, has been shown to give accurate estimations of step count at a variety of walking speeds, but underestimate energy expenditure in other clinical conditions. The aim of this study was to compare the step count and energy expenditure calculated for FB and SWM in individuals with COPD. Methods: 39 individuals with COPD (mean±SD; Age (yrs): 68±10; FEV (% predicted): 63.2±28.2) wore SWM and FB devices during 1 unrestricted physical activity over a period of five days and an average five day step count and energy expenditure was determined. Results: While a significant correlation between FB and SWM daily step count was observed (R =0.89, p<0.05), SWM daily step count was 2 significantly lower than FB step count (FB (steps/day): 3704±2325 vs. SWM (steps/day): 2486±1895; p<0.01). In spite of this, SWM calculated a significantly higher daily energy expenditure as compared to the FB (FB (kcal): 919±229 vs. SWM (kcal): 1220±471; p<0.01). Conclusions: A strong correlation between FB and SWM devices was found in individuals with COPD, however, caution must be taken when interpreting absolute results for step count and energy expenditure. Slower walking speeds in patients with COPD may affect the algorithms used to calculate step count and energy expenditure in both PAMs. Future work should include a criterion measure for step count and energy expenditure between these PAMs in order to more accurately assess their validity.

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Comparison of wrist-worn Fitbit Flex and waist-worn ActiGraph for measuring steps in free-living adults (2017)

PLOS ONE

Authors: Chu, A.H.Y., Ng, S.H.X., Paknezhad, M., Gauterin, A., Koh, D., Brown, M.S. and Müller-Riemenschneider, F.

Abstract

Introduction: Accelerometers are commonly used to assess physical activity. Consumer activity trackers have become increasingly popular today, such as the Fitbit. This study aimed to compare the average number of steps per day using the wrist-worn Fitbit Flex and waist-worn ActiGraph (wGT3X-BT) in free-living conditions. Methods: 104 adult participants (n = 35 males; n = 69 females) were asked to wear a Fitbit Flex and an ActiGraph concurrently for 7 days. Daily step counts were used to classify inactive (textless10,000 steps) and active (=10,000 steps) days, which is one of the commonly used physical activity guidelines to maintain health. Proportion of agreement between physical activity categorizations from ActiGraph and Fitbit Flex was assessed. Statistical analyses included Spearman's rho, intraclass correlation (ICC), median absolute percentage error (MAPE), Kappa statistics, and Bland-Altman plots. Analyses were performed among all participants, by each step-defined daily physical activity category and gender. Results: The median average steps/day recorded by Fitbit Flex and ActiGraph were 10193 and 8812, respectively. Strong positive correlations and agreement were found for all participants, both genders, as well as daily physical activity categories (Spearman's rho: 0.76–0.91; ICC: 0.73–0.87). The MAPE was: 15.5% (95% confidence interval [CI]: 5.8–28.1%) for overall steps, 16.9% (6.8–30.3%) vs. 15.1% (4.5–27.3%) in males and females, and 20.4% (8.7–35.9%) vs. 9.6% (1.0–18.4%) during inactive days and active days. Bland-Altman plot indicated a median overestimation of 1300 steps/day by the Fitbit Flex in all participants. Fitbit Flex and ActiGraph respectively classified 51.5% and 37.5% of the days as active (Kappa: 0.66). Conclusions: There were high correlations and agreement in steps between Fitbit Flex and ActiGraph. However, findings suggested discrepancies in steps between devices. This imposed a challenge that needs to be considered when using Fitbit Flex in research and health promotion programs.

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Criterion-Validity of Commercially Available Physical Activity Tracker to Estimate Step Count, Covered Distance and Energy Expenditure during Sports Conditions (2017)

Frontiers in Physiology

Authors: Wahl, Y., Düking, P., Droszez, A., Wahl, P. and Mester, J.

Abstract

Background: In the past years, there was an increasing development of physical activity tracker (Wearables). For recreational people, testing of these devices under walking or light jogging conditions might be sufficient. For (elite) athletes, however, scientific trustworthiness needs to be given for a broad spectrum of velocities or even fast changes in velocities reflecting the demands of the sport. Therefore, the aim was to evaluate the validity of eleven Wearables for monitoring step count, covered distance and energy expenditure (EE) under laboratory conditions with different constant and varying velocities. Methods: Twenty healthy sport students (10 men, 10 women) performed a running protocol consisting of four 5 min stages of different constant velocities (4.3; 7.2; 10.1; 13.0 km·h−1), a 5 min period of intermittent velocity, and a 2.4 km outdoor run (10.1 km·h−1) while wearing eleven different Wearables (Bodymedia Sensewear, Beurer AS 80, Polar Loop, Garmin Vivofit, Garmin Vivosmart, Garmin Vivoactive, Garmin Forerunner 920XT, Fitbit Charge, Fitbit Charge HR, Xaomi MiBand, Withings Pulse Ox). Step count, covered distance, and EE were evaluated by comparing each Wearable with a criterion method (Optogait system and manual counting for step count, treadmill for covered distance and indirect calorimetry for EE). Results: All Wearables, except Bodymedia Sensewear, Polar Loop, and Beurer AS80, revealed good validity (small MAPE, good ICC) for all constant and varying velocities for monitoring step count. For covered distance, all Wearables showed a very low ICC (<0.1) and high MAPE (up to 50%), revealing no good validity. The measurement of EE was acceptable for the Garmin, Fitbit and Withings Wearables (small to moderate MAPE), while Bodymedia Sensewear, Polar Loop, and Beurer AS80 showed a high MAPE up to 56% for all test conditions. Conclusion: In our study, most Wearables provide an acceptable level of validity for step counts at different constant and intermittent running velocities reflecting sports conditions. However, the covered distance, as well as the EE could not be assessed validly with the investigated Wearables. Consequently, covered distance and EE should not be monitored with the presented Wearables, in sport specific conditions.

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Daily Activity Measured With Wearable Technology as a Novel Measurement of Treatment Effect in Patients With Coronary Microvascular Dysfunction: Substudy of a Randomized Controlled Crossover Trial (2017)

JMIR Research Protocols

Authors: Birkeland, K., Khandwalla, R.M., Kedan, I., Shufelt, C.L., Mehta, P.K., Minissian, M.B., Wei, J., Handberg, E.M., Thomson, L.E., Berman, D.S., Petersen, J.W., Anderson, R.D., Cook-Wiens, G., Pepine, C.J. and Bairey Merz, C.N.

Abstract

Background: Digital wearable devices provide a “real-world” assessment of physical activity and quantify intervention-related changes in clinical trials. However, the value of digital wearable device-recorded physical activity as a clinical trial outcome is unknown. Objective: Because late sodium channel inhibition (ranolazine) improves stress laboratory exercise duration among angina patients, we proposed that this benefit could be quantified and translated during daily life by measuring digital wearable device-determined step count in a clinical trial. Methods: We conducted a substudy in a randomized, double-blinded, placebo-controlled, crossover trial of participants with angina and coronary microvascular dysfunction (CMD) with no obstructive coronary artery disease to evaluate the value of digital wearable device monitoring. Ranolazine or placebo were administered (500-1000 mg twice a day) for 2 weeks with a subsequent 2-week washout followed by crossover to ranolazine or placebo (500-1000 mg twice a day) for an additional 2 weeks. The outcome of interest was within-subject difference in Fitbit Flex daily step count during week 2 of ranolazine versus placebo during each treatment period. Secondary outcomes included within-subject differences in angina, quality of life, myocardial perfusion reserve, and diastolic function. Results: A total of 43 participants were enrolled in the substudy and 30 successfully completed the substudy for analysis. Overall, late sodium channel inhibition reduced within-subject daily step count versus placebo (mean 5757 [SD 3076] vs mean 6593 [SD 339], P=.01) but did not improve angina (Seattle Angina Questionnaire-7 [SAQ-7]) (P=.83). Among the subgroup with improved angina (SAQ-7), a direct correlation with increased step count (r=.42, P=.02) was observed. Conclusions: We report one of the first studies to use digital wearable device-determined step count as an outcome variable in a placebo-controlled crossover trial of late sodium channel inhibition in participants with CMD. Our substudy demonstrates that late sodium channel inhibition was associated with a decreased step count overall, although the subgroup with angina improvement had a step count increase. Our findings suggest digital wearable device technology may provide new insights in clinical trial research. Trial Registration: Clinicaltrials.gov NCT01342029; https://clinicaltrials.gov/ct2/show/NCT01342029 (Archived by WebCite at http://www.webcitation.org/6uyd6B2PO) [JMIR Res Protoc 2017;6(12):e255]

Determinants for Sustained Use of an Activity Tracker: Observational Study (2017)

JMIR mHealth and uHealth

Authors: Hermsen, S., Moons, J., Kerkhof, P., Wiekens, C. and De Groot, M.

Abstract

Background: A lack of physical activity is considered to cause 6% of deaths globally. Feedback from wearables such as activity trackers has the potential to encourage daily physical activity. To date, little research is available on the natural development of adherence to activity trackers or on potential factors that predict which users manage to keep using their activity tracker during the first year (and thereby increasing the chance of healthy behavior change) and which users discontinue using their trackers after a short time. Objective: The aim of this study was to identify the determinants for sustained use in the first year after purchase. Specifically, we look at the relative importance of demographic and socioeconomic, psychological, health-related, goal-related, technological, user experience–related, and social predictors of feedback device use. Furthermore, this study tests the effect of these predictors on physical activity. Methods: A total of 711 participants from four urban areas in France received an activity tracker (Fitbit Zip) and gave permission to use their logged data. Participants filled out three Web-based questionnaires: at start, after 98 days, and after 232 days to measure the aforementioned determinants. Furthermore, for each participant, we collected activity data tracked by their Fitbit tracker for 320 days. We determined the relative importance of all included predictors by using Random Forest, a machine learning analysis technique. Results: The data showed a slow exponential decay in Fitbit use, with 73.9% (526/711) of participants still tracking after 100 days and 16.0% (114/711) of participants tracking after 320 days. On average, participants used the tracker for 129 days. Most important reasons to quit tracking were technical issues such as empty batteries and broken trackers or lost trackers (21.5% of all Q3 respondents, 130/601). Random Forest analysis of predictors revealed that the most influential determinants were age, user experience–related factors, mobile phone type, household type, perceived effect of the Fitbit tracker, and goal-related factors. We explore the role of those predictors that show meaningful differences in the number of days the tracker was worn. Conclusions: This study offers an overview of the natural development of the use of an activity tracker, as well as the relative importance of a range of determinants from literature. Decay is exponential but slower than may be expected from existing literature. Many factors have a small contribution to sustained use. The most important determinants are technical condition, age, user experience, and goal-related factors. This finding suggests that activity tracking is potentially beneficial for a broad range of target groups, but more attention should be paid to technical and user experience–related aspects of activity trackers. [JMIR Mhealth Uhealth 2017;5(10):e164]

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Determining the role of Maternal Leptin and Activity in Pregnancy Outcomes (2017)

The FASEB Journal

Authors: Nishimura, T.E., Polgreen, P.M., Polgreen, L.A., Brandt, D.S., Thomas, K.M., Scroggins, S.M., Evans, N.J., Alexander, L.B., Santillan, M.K. and Santillan, D.A.

Abstract

Leptin, an adipocytokine with an important role in energy homeostasis and other neuroendocrine functions, is found in higher levels in obese individuals. Maternal obesity is associated with numerous adverse pregnancy outcomes, such as miscarriage, gestational diabetes, gestational hypertension, and preeclampsia. However, the relationship between leptin, activity, and pregnancy outcomes is unclear. Some studies have found reduced leptin with physical activity and leptin is known to have direct effects on the cardiovascular system. Therefore, we hypothesized that women who have higher activity during pregnancy will have lower plasma leptin levels and experience fewer adverse outcomes during their pregnancy. In a cross-sectional study, 100 pregnant women were co-enrolled into the Maternal Fetal Tissue Bank (IRB200901784) and this study (IRB201502767). Pregnant women received triaxial accelerometers (Fitbit Zip) to wear throughout gestation. Maternal blood samples from each trimester were assayed in duplicate for plasma leptin concentration using an enzyme-linked immunosorbent assay (ELISA). Pregnancy outcomes including maternal development of gestational diseases such as preeclampsia as well as mode of delivery, birthweight, fetal gender, and APGAR scores were extracted from the electronic health record (EPIC). Additionally, maternal demographics (age, race, and ethnicity) and health characteristics such as body mass index and any chronic health conditions at the beginning of pregnancy were recorded. Average step counts were obtained for the first (5523.77 ± 3720.33), second (5667.62 ± 4029.63), and third (4979.32 ± 3138.37) trimesters. In addition, no significant differences in average plasma leptin concentrations were obtained for the first (19839.8 ± 2390.9 pg/mL), second (11319.0 ± 2000.9 pg/mL), and third (26468.3 ± 5918.5 pg/mL) trimesters (P = 0.08). Leptin was only inversely correlated with activity in the first trimester (R2 =-0.32, P = 0.02), whereas no associations were detected in the 2nd and 3rd trimester. As an adverse outcome, we examined activity and leptin in patients with and without preeclampsia. The preeclamptic cohort took significantly fewer steps than the control group (5656.59 vs. 3586.72, P textless 0.05) during the first trimester. The preeclamptic cohort also had a significantly higher average BMI (39 ± 6 vs. 27 ± 7, P = 0.02) and rates of chronic hypertension (67% vs. 6%, P textless 0.001) than controls. Leptin was also significantly higher in the preeclamptic cohort than controls (52476.1 ± 10456.0 pg/mL vs. 16777.1 ± 1395.0 pg/mL, P textless0.001). In conclusion, significant differences exist between the activity levels, leptin, and pregnancy outcomes of the preeclamptic and control groups.

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Development and evaluation of two web-based interventions for the promotion of physical activity in older adults: study protocol for a community-based controlled intervention trial (2017)

BMC Public Health

Authors: Muellmann, S., Bragina, I., Voelcker-Rehage, C., Rost, E., Lippke, S., Meyer, J., Schnauber, J., Wasmann, M., Toborg, M., Koppelin, F., Brand, T., Zeeb, H. and Pischke, C.R.

Abstract

BACKGROUND Regular physical activity (PA) is a key contributor to healthy ageing. However, despite known health benefits, only one third of older adults in Germany reach the PA levels recommended for persons aged 65 years and above by the World Health Organization. The aim of the current study is to evaluate the effectiveness of two web-based interventions for the initiation and maintenance of regular PA (i.e., intervention groups 1 and 2) compared to a delayed intervention control group of older adults aged 65 to 75 years. METHODS/DESIGN Study participants will be randomly assigned to one of three study arms in five communities in the Bremen-Oldenburg metropolitan region: a) Participants in the first arm will receive access to a web-based intervention for 10 weeks allowing them to track their weekly PA (subjective self-monitoring, intervention group 1); b) participants in the second arm will receive access to the web-based intervention for 10 weeks and, in addition, track PA using Fitbit Zips (objective self-monitoring, intervention group 2); c) participants in the delayed intervention control group will receive access to the intervention implemented in the first study arm after completion of the 12-week follow-up in the other two groups within each community. In addition, weekly group meetings in the communities will be offered to study participants in the intervention groups providing the opportunity to address questions related to the use of the website and to practice PA in groups (e.g., neighborhood walks, strength and balance exercises). To evaluate short-term effects of the intervention on physical and psychological health, PA, physical fitness, and cognitive and psychological variables will be assessed at baseline and 12-week follow-up. DISCUSSION This study will provide answers regarding acceptance and effectiveness of web-based interventions promoting uptake and maintenance of regular PA in persons aged 65-75 years. Study findings will contribute to a growing body of evidence in Germany concerning the role of community-based interventions for the promotion of PA and healthy ageing in older adults. T

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Development of the Physical activity and Your Nutrition for Cancer (PYNC) smartphone app for preventing breast cancer in women (2017)

mHealth

Authors: Coughlin, S.S., Besenyi, G.M., Bowen, D. and De Leo, G.

Abstract

Background: In the U.S., breast cancer accounts for more cancer deaths in women than any site other than lung cancer. Based upon attributable risks, about 30–35% of breast cancers could potentially be prevented by addressing obesity, physical inactivity, increased alcohol consumption, and carcinogenic exposures such as hormone replacement therapy (HRT). We need methods of reducing women's risks of this disease that are attractive and easy to use, widely accessible to diverse women, and able to be easily amended to account for new research. Methods: The overall objective of this 12-month project is to develop and test a smartphone app to provide women with information about how they can reduce their risk of breast cancer through healthy behaviors such as physical activity, weight management, restricting caloric intake, consuming a healthy diet and proper nutrition, engaging in regular physical activity, and avoiding carcinogenic exposures such as HRT and alcohol. The specific aims are: (I) to develop a smartphone app for breast cancer prevention using a behavioral framework; (II) to ensure interconnectivity with commercially available products (Fitbit device for monitoring physical activity and the LoseIt! smartphone app for monitoring and tracking diet and nutrition); and (III) to ensure that the mHealth intervention is suitable for women with varying levels of health literacy and eHealth literacy. Results: The app, referred to as Physical activity and Your Nutrition for Cancer (PYNC), is being coded on an iOS platform. Users will be able to access the breast cancer prevention app using their smartphone or tablet. The app's design will ensure interconnectivity with commercially available products for monitoring and tracking physical activity, caloric intake, diet and nutrition. Using the app, it will be feasible for users to connect and sync their Fitbit and LoseIt! accounts so that information collected about physical activity, caloric intake, diet, and nutrition can be conveniently assessed from one portal. The Fitbit device and app provides reminders and allows users to set physical activity goals. Users will be able to access health education information about breast cancer risk-reduction with attractive graphics and visual displays. Conclusions: Future directions will include testing the efficacy of the mHealth intervention in increasing physical activity, improving diet and nutrition, and weight management through a randomized controlled trial, and widespread dissemination and implementation research.

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Does Stress Result in You Exercising Less? Or Does Exercising Result in You Being Less Stressed? Or Is It Both? Testing the Bi-directional Stress-Exercise Association at the Group and Person (N of 1) Level (2017)

Annals of Behavioral Medicine

Authors: Burg, M.M., Schwartz, J.E., Kronish, I.M., Diaz, K.M., Alcantara, C., Duer-Hefele, J. and Davidson, K.W.

Abstract

Background: Psychosocial stress contributes to heart disease in part by adversely affecting maintenance of health behaviors, while exercise can reduce stress. Assessing the bi-directional relationship between stress and exercise has been limited by lack of real-time data and theoretical and statistical models. This lack may hinder efforts to promote exercise maintenance. Purpose: We test the bi-directional relationship between stress and exercise using real-time data for the average person and the variability—individual differences—in this relationship. Methods: An observational study was conducted within a single cohort randomized controlled experiment. Healthy young adults, (n = 79) who reported only intermittent exercise, completed 12 months of stress monitoring by ecological momentary assessment (at the beginning of, end of, and during the day) and continuous activity monitoring by Fitbit. A random coefficients linear mixed model was used to predict end-of-day stress from the occurrence/non-occurrence of exercise that day; a logistic mixed model was used to predict the occurrence/non-occurrence of exercise from ratings of anticipated stress. Separate regression analyses were also performed for each participant. Sensitivity analysis tested all models, restricted to the first 180 days of observation (prior to randomization). Results: We found a significant average inverse (i.e., negative) effect of exercise on stress and of stress on exercise. There was significant between-person variability. Of N = 69, exercise was associated with a stress reduction for 15, a stress increase for 2, and no change for the remainder. We also found that an increase in anticipated stress reported the previous night or that morning was associated with a significant 20–22% decrease (OR = 0.78–0.80) in the odds of exercising that day. Of N = 69, this increase in stress reduced the likelihood of exercise for 17, increased the odds for 1, and had no effect for the remainder. We were unable to identify psychosocial factors that moderate the individual differences in these effects. Conclusions: The relationship of stress to exercise can be uni- or bi-directional and varies from person to person. A precision medicine approach may improve exercise uptake.

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Does supplementation with carnosine improve cardiometabolic health and cognitive function in patients with pre-diabetes and type 2 diabetes? study protocol for a randomised, double-blind, placebo-controlled trial (2017)

BMJ Open

Authors: Baye, E., Menon, K., de Courten, M.P., Earnest, A., Cameron, J. and de Courten, B.

Abstract

Introduction: Carnosine, an over-the-counter food supplement, has a promising potential for the prevention and treatment of chronic diseases such as type 2 diabetes (T2DM), cardiovascular and neurodegenerative diseases through its anti-inflammatory, antiglycation, antioxidative and chelating effects. We have previously shown that supplementation with carnosine preserves insulin sensitivity and secretion in non-diabetic overweight and obese individuals. The effect of carnosine on cardiometabolic risk and related cognitive outcomes in patients with pre-diabetes and T2DM has thus far not been studied. We therefore aim to investigate whether supplementation with carnosine improves cardiometabolic health and cognitive function in patients with pre-diabetes and T2DM. Methods and analysis: We will employ a parallel design randomised controlled trial. Fifty participants with pre-diabetes (impaired fasting glycaemia and impaired glucose tolerance) and T2DM (with HbA1c level textless 8%) aged between 18 to 70 years will be randomly assigned to the intervention or control group. At baseline, participants will undergo a medical review and series of tests including anthropometric measurements (body mass index, a dual X-ray absorptiometry and peripheral quantitative computed tomography scan), an oral glucose tolerance test, cardiovascular measurements (central blood pressure, endothelial function and arterial stiffness), cognitive function, physical activity measurement, heart rate variability and liver fibroscan as well as questionnaires to assess dietary habits, sleep quality, depression and quality of life. The intervention group will receive 2?g of carnosine daily in two divided doses while the control group will receive identical placebo capsules for 14 weeks. All baseline measurements will be repeated at the end of the intervention. The change in glycaemic, cardiovascular and cognitive parameters as well as other measures will be compared between the groups. Ethics and dissemination: This study is approved by the Human Research Ethics Committee of Monash Health and Monash University, Australia. The findings will be disseminated via peer-reviewed publications and conference presentations.

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Does Wearable Technology Provide Accurate Heart Rate Measures While Playing Pickleball Doubles? (2017)

Medicine & Science in Sports & Exercise

Authors: Denning, M., Smith, M., Zagrodnik, J. and Ruden, T.

Abstract

The sport of pickleball is increasing in popularity throughout the United States, especially in middle-aged, and older adults. Research investigating the physiological demands of pickleball is limited. The use of wearable technology is also gaining popularity, however, the accuracy of such devices is under question. PURPOSE: The purpose of this study was to determine if wearable technology provide valid heart rate (HR) measures during pickleball doubles in middle aged adults. METHODS: 8 female, intermediate level pickleball players (IFP = 3.0 ± 0.8; age = 47 ± 11 years; mass = 72.5 ± 12.8 kg; height = 1.70 ± 0.08 m) participated in this study. All subjects played pickleball doubles for 30 minutes. HR was measured using two devices (Fitbit HR, worn on the dominate writs, and Polar HR monitor, worn at the xiphoid process level). Peak and mean HR were determined for each device. A paired sample t-tests was used to determine differences in HR between devices for each dependent variable (HR max and HR mean). A Pearson product-moment correlation coefficient was used to evaluate the concurrent validity between the gold standard (Polar HR system) and the wearable technology (Fitbit HR). RESULTS: Peak HR measured by the Polar system (151.9 ± 15.9 beats/min) was not significantly different from the peak HR measured by the Fitbit HR (149.6 ± 18.0 beats/min; p = 0.69). Similarly, mean HR measured by the Polar system (127.9 ± 17.9 beats/min) was not significantly different from the mean HR measured by the Fitbit HR (121.0 ± 18.2 beats/min; p = 0.23). Concurrent validity between the Polar HR system and the Fitbit HR for both peak (r = 0.6) and mean HR (r = 0.66) was also nonsignificant (p textgreater 0.05). CONCLUSIONS: On average, peak and mean HR was similar between the two devices. These results support the validity of wearable technology; the Fitbit HR was moderately valid in peak and mean HR compared to the Polar HR system. These results are promising for those who own wearable technology and are using it to monitor HR during physical activities such as pickleball doubles. We acknowledge our small sample size and admit that further investigation of the validity of wearable technology on physiological measures during pickleball and other racket sports is warranted.

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Effect of a Game-Based Intervention Designed to Enhance Social Incentives to Increase Physical Activity Among Families: The BE FIT Randomized Clinical Trial (2017)

AMA Internal Medicine

Authors: Patel, M.S., Benjamin, E.J., Volpp, K.G., Fox, C.S., Small, D.S., Massaro, J.M., Lee, J.J., Hilbert, V., Valentino, M., Taylor, D.H., Manders, E.S., Mutalik, K., Zhu, J., Wang, W. and Murabito, J.M.

Abstract

mportance Gamification, the application of game design elements such as points and levels in nongame contexts, is often used in digital health interventions, but evidence on its effectiveness is limited. Objective To test the effectiveness of a gamification intervention designed using insights from behavioral economics to enhance social incentives within families to increase physical activity. Design, Setting, and Participants The Behavioral Economics Framingham Incentive Trial (BE FIT) was a randomized clinical trial with a 12-week intervention period and a 12-week follow-up period. The investigation was a community-based study between December 7, 2015, and August 14, 2016. Participants in the modified intent-to-treat analysis were adults enrolled in the Framingham Heart Study, a long-standing cohort of families. Interventions All participants tracked daily step counts using a wearable device or a smartphone, established a baseline, selected a step goal increase, and received daily individual feedback on goal performance by text message or email for 24 weeks. Families in the gamification arm could earn points and progress through levels based on physical activity goal achievement during the 12-week intervention. The game design was meant to enhance collaboration, accountability, and peer support. Main Outcomes and Measures The primary outcome was the proportion of participant-days that step goals were achieved during the intervention period. Secondary outcomes included the proportion of participant-days that step goals were achieved during the follow-up period and the change in the mean daily steps during the intervention and follow-up periods. Results Among 200 adults comprising 94 families, the mean age was 55.4 years, and 56.0% (n = 112) were female. During the intervention period, participants in the gamification arm achieved step goals on a significantly greater proportion of participant-days (0.53 vs 0.32; adjusted difference, 0.27; 95% CI, 0.20-0.33; P < .001) and had a significantly greater increase in the mean daily steps compared with baseline (1661 vs 636; adjusted difference, 953; 95% CI, 505-1401; P < .001) than the control arm. During the follow-up period, physical activity in the gamification arm declined but remained significantly greater than that in the control arm for the proportion of participant-days achieving step goals (0.44 vs 0.33; adjusted difference, 0.12; 95% CI, 0.05-0.19; P < .001) and the mean daily steps compared with baseline (1385 vs 798; adjusted difference, 494; 95% CI, 170-818; P < .01). Conclusions and Relevance Gamification designed to leverage insights from behavioral economics to enhance social incentives significantly increased physical activity among families in the community.

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Effect of personal activity trackers on weight loss in families enrolled in a comprehensive behavioral family-lifestyle intervention program in the federally qualified health center setting: A randomized controlled trial (2017)

Contemporary Clinical Trials Communications

Authors: Espinoza, J., Chen, A., Orozco, J., Deavenport-Saman, A. and Yin, L.

Abstract

BACKGROUND Childhood obesity continues to be a substantial problem despite major public health efforts, and disproportionately impacts children from low-income families. Digital health tools and consumer technology offer promising opportunities for interventions, but few studies have evaluated how they might be incorporated into existing interventions or used to create new types of interventions. It remains unclear which approaches would be most beneficial for underserved pediatric populations. PURPOSE To describe the design and rationale of a single-center randomized, controlled trial evaluating the effects of personal activity tracker (PAT) use by parents on weight-status improvement in both parents and overweight children enrolled in BodyWorks (BW), a comprehensive behavioral family-lifestyle intervention program (CBFLI), in a primary-care clinic serving a predominantly low-income Latino population. METHODS This study is being conducted in the AltaMed general pediatrics clinic at Children's Hospital Los Angeles. Eligible participants are families (child and adult caregiver) in which the child is between 7 and 18 years of age, has a BMI =85th percentile for age and sex, and has been referred to BW by their AltaMed pediatrician. BW consists of one weekly, two-hour session for 7 weeks. In a given cycle, the program is offered on two separate nights: Monday (Spanish) and Wednesday (English). Families self sort into one of two groups based on language preference. To ensure balanced allocation of language preference groups and prevent in-group cross contamination, block randomization is used to assign whole groups to either the intervention or control arms of the study. The control arm consists of usual care, while the intervention arm adds assigning a Fitbit PAT to the parents and training them in its proper use. Study personnel are blinded to group assignment during the analysis phase. Study outcomes include attendance rate, program completion rate, and changes in weight-status improvement, defined as change in weight and BMI for adults and change in BMI z-score for children. We hypothesize that the intervention arm will have better weight-related outcomes than the control arm. Study completion is anticipated in 2017, after the enrollment of approximately 150 families. CONCLUSIONS The study aim is to evaluate the effects of PATs on weight-related outcomes in overweight children and parents participating in a CBFLI. The results will be important for determining whether wearable devices are an effective addition to weight loss interventions for overweight and obese children.

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Effectiveness of SmartMoms, a Novel eHealth Intervention for Management of Gestational Weight Gain: Randomized Controlled Pilot Trial (2017)

JMIR mHealth and uHealth

Authors: Redman, L.M., Gilmore, L.A., Breaux, J., Thomas, D.M., Elkind-Hirsch, K., Stewart, T., Hsia, D.S., Burton, J., Apolzan, J.W., Cain, L.E., Altazan, A.D., Ragusa, S., Brady, H., Davis, A., Tilford, J.M., Sutton, E.F. and Martin, C.K.

Abstract

Background: Two-thirds of pregnant women exceed gestational weight gain (GWG) recommendations. Because excess GWG is associated with adverse outcomes for mother and child, development of scalable and cost-effective approaches to deliver intensive lifestyle programs during pregnancy is urgent. Objective: The aim of this study was to decrease the proportion of women who exceed the Institute of Medicine (IOM) 2009 GWG guidelines. Methods: In a parallel-arm randomized controlled trial, 54 pregnant women (age 18-40 years) who were overweight (n=25) or obese (n=29) were enrolled to test whether an intensive lifestyle intervention (called SmartMoms) decreased the proportion of women with excess GWG, defined as exceeding the 2009 IOM guidelines, compared to no intervention (usual care group). The SmartMoms intervention was delivered through mobile phone (remote group) or in a traditional in-person, clinic-based setting (in-person group), and included a personalized dietary intake prescription, self-monitoring weight against a personalized weight graph, activity tracking with a pedometer, receipt of health information, and continuous personalized feedback from counselors. Results: A significantly smaller proportion of women exceeded the IOM 2009 GWG guidelines in the SmartMoms intervention groups (in-person: 56%, 10/18; remote: 58%, 11/19) compared to usual care (85%, 11/13; P=.02). The remote intervention was a lower cost to participants (mean US $97, SD $6 vs mean US $347, SD $40 per participant; Ptextless.001) and clinics (US $215 vs US $419 per participant) and with increased intervention adherence (76.5% vs 60.8%; P=.049). Conclusions: An intensive lifestyle intervention for GWG can be effectively delivered via a mobile phone, which is both cost-effective and scalable. Trial Registration: Clinicaltrials.gov NCT01610752; https://clinicaltrials.gov/ct2/show/NCT01610752 (Archived by WebCite at http://www.webcitation.org/6sarNB4iW) [JMIR Mhealth Uhealth 2017;5(9):e133]

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Enhancing mHealth Technology in the Patient-Centered Medical Home Environment to Activate Patients With Type 2 Diabetes: A Multisite Feasibility Study Protocol. (2017)

JMIR Research Protocols

Authors: Gimbel, R., Shi, L., Williams, J.E., Dye, C.J., Chen, L., Crawford, P., Shry, E.A., Griffin, S.F., Jones, K.O., Sherrill, W.W., Truong, K., Little, J.R., Edwards, K.W., Hing, M. and Moss, J.B.

Abstract

BACKGROUND The potential of mHealth technologies in the care of patients with diabetes and other chronic conditions has captured the attention of clinicians and researchers. Efforts to date have incorporated a variety of tools and techniques, including Web-based portals, short message service (SMS) text messaging, remote collection of biometric data, electronic coaching, electronic-based health education, secure email communication between visits, and electronic collection of lifestyle and quality-of-life surveys. Each of these tools, used alone or in combination, have demonstrated varying degrees of effectiveness. Some of the more promising results have been demonstrated using regular collection of biometric devices, SMS text messaging, secure email communication with clinical teams, and regular reporting of quality-of-life variables. In this study, we seek to incorporate several of the most promising mHealth capabilities in a patient-centered medical home (PCMH) workflow. OBJECTIVE We aim to address underlying technology needs and gaps related to the use of mHealth technology and the activation of patients living with type 2 diabetes. Stated differently, we enable supporting technologies while seeking to influence patient activation and self-care activities. METHODS This is a multisite phased study, conducted within the US Military Health System, that includes a user-centered design phase and a PCMH-based feasibility trial. In phase 1, we will assess both patient and provider preferences regarding the enhancement of the enabling technology capabilities for type 2 diabetes chronic care management. Phase 2 research will be a single-blinded 12-month feasibility study that incorporates randomization principles. Phase 2 research will seek to improve patient activation and self-care activities through the use of the Mobile Health Care Environment with tailored behavioral messaging. The primary outcome measure is the Patient Activation Measure scores. Secondary outcome measures are Summary of Diabetes Self-care Activities Measure scores, clinical measures, comorbid conditions, health services resource consumption, and technology system usage statistics. RESULTS We have completed phase 1 data collection. Formal analysis of phase 1 data has not been completed. We have obtained institutional review board approval and began phase 1 research in late fall 2016. CONCLUSIONS The study hypotheses suggest that patients can, and will, improve their activation in chronic care management. Improved activation should translate into improved diabetes self-care. Expected benefits of this research to the scientific community and health care services include improved understanding of how to leverage mHealth technology to activate patients living with type 2 diabetes in self-management behaviors. The research will shed light on implementation strategies in integrating mHealth into the clinical workflow of the PCMH setting. TRIAL REGISTRATION ClinicalTrials.gov NCT02949037. https://clinicaltrials.gov/ct2/show/NCT02949037.

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Estimating Accuracy at Exercise Intensities: A Comparative Study of Self-Monitoring Heart Rate and Physical Activity Wearable Devices (2017)

JMIR mHealth and uHealth

Authors: Dooley, E.E., Golaszewski, N.M. and Bartholomew, J.B.

Abstract

Background: Physical activity tracking wearable devices have emerged as an increasingly popular method for consumers to assess their daily activity and calories expended. However, whether these wearable devices are valid at different levels of exercise intensity is unknown. Objective: The objective of this study was to examine heart rate (HR) and energy expenditure (EE) validity of 3 popular wrist-worn activity monitors at different exercise intensities. Methods: A total of 62 participants (females: 58%, 36/62; nonwhite: 47% [13/62 Hispanic, 8/62 Asian, 7/62 black/ African American, 1/62 other]) wore the Apple Watch, Fitbit Charge HR, and Garmin Forerunner 225. Validity was assessed using 2 criterion devices: HR chest strap and a metabolic cart. Participants completed a 10-minute seated baseline assessment; separate 4-minute stages of light-, moderate-, and vigorous-intensity treadmill exercises; and a 10-minute seated recovery period. Data from devices were compared with each criterion via two-way repeated-measures analysis of variance and Bland-Altman analysis. Differences are expressed in mean absolute percentage error (MAPE). Results: For the Apple Watch, HR MAPE was between 1.14% and 6.70%. HR was not significantly different at the start (P=.78), during baseline (P=.76), or vigorous intensity (P=.84); lower HR readings were measured during light intensity (P=.03), moderate intensity (P=.001), and recovery (P=.004). EE MAPE was between 14.07% and 210.84%. The device measured higher EE at all stages (Ptextless.01). For the Fitbit device, the HR MAPE was between 2.38% and 16.99%. HR was not significantly different at the start (P=.67) or during moderate intensity (P=.34); lower HR readings were measured during baseline, vigorous intensity, and recovery (Ptextless.001) and higher HR during light intensity (Ptextless.001). EE MAPE was between 16.85% and 84.98%. The device measured higher EE at baseline (P=.003), light intensity (Ptextless.001), and moderate intensity (P=.001). EE was not significantly different at vigorous (P=.70) or recovery (P=.10). For Garmin Forerunner 225, HR MAPE was between 7.87% and 24.38%. HR was not significantly different at vigorous intensity (P=.35). The device measured higher HR readings at start, baseline, light intensity, moderate intensity (Ptextless.001), and recovery (P=.04). EE MAPE was between 30.77% and 155.05%. The device measured higher EE at all stages (Ptextless.001). Conclusions: This study provides one of the first validation assessments for the Fitbit Charge HR, Apple Watch, and Garmin Forerunner 225. An advantage and novel approach of the study is the examination of HR and EE at specific physical activity intensities. Establishing validity of wearable devices is of particular interest as these devices are being used in weight loss interventions and could impact findings. Future research should investigate why differences between exercise intensities and the devices exist. [JMIR Mhealth Uhealth 2017;5(3):e34]

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Estimation of Sleep Stages Using Cardias and Accelerometer Data from a Wrist-Worn Device (2017)

Sleep

Authors: Beattie, Z., Pantelopoulos, A., Ghoreyshi, A., Oyang, Y., Statan, A. and Heneghan, C.

Abstract

Introduction: We investigated the ability of a wrist-worn tracker to estimate sleep stages in normal adult sleepers. Such a device could be useful in simplifying sleep research and in increasing public knowledge of sleep. Methods: Movement and cardiac data was collected from 60 adult subjects (36 M: 24 F, ages 34?±?10 yrs) wearing two wrist worn devices (left and right hand) containing a 3D-accelerometer and an optical photoplethysmogram (PPG), while undergoing a sleep stage study using a Type III home sleep testing device. The accelerometer was used to generate various features of movement; the PPG records cardiac peaks generated by each heartbeat, and can be used to determine heart rate and heart rate variability metrics. The sleep study was scored independently by two registered PSG technicians, using consensus AASM scoring rules. Using these labels, an automated classifier and post-processing rule was developed to label 30-second epochs as one of Wake/Light/Deep/REM (note that Stages N1 and N2 were combined into a single “Light” classification). The estimated performance of this automated classifier system was calculated using a leave-one out validation method. The performance metrics were Cohen's kappa (measures the level of agreement greater than chance) and per-epoch accuracy (percent of epochs correctly labeled). Results: The estimated Cohen's kappa was 0.52?±?0.14 for left hand wear, and 0.53?±?0.14 (right hand). The per-epoch accuracy was 69%. Across the population, there was no statistically significant bias in the estimated durations of the wake, light, deep and REM stages versus the gold standard measurements. Conclusion: These results suggest that a wrist worn device with movement and cardiac sensors can be used to determine sleep stages with a reasonable degree of accuracy in normal adult sleepers, but without the cost and artificial sleep environment of a sleep laboratory. The reported performance figures are similar or better than previously reported results from non-EEG based sleep staging using combinations of cardiac, respiratory and movement information.

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Estimation of Symptom Severity During Chemotherapy From Passively Sensed Data: Exploratory Study. (2017)

Journal of Medical Internet Research

Authors: Low, C.A., Dey, A.K., Ferreira, D., Kamarck, T., Sun, W., Bae, S. and Doryab, A.

Abstract

BACKGROUND Physical and psychological symptoms are common during chemotherapy in cancer patients, and real-time monitoring of these symptoms can improve patient outcomes. Sensors embedded in mobile phones and wearable activity trackers could be potentially useful in monitoring symptoms passively, with minimal patient burden. OBJECTIVE The aim of this study was to explore whether passively sensed mobile phone and Fitbit data could be used to estimate daily symptom burden during chemotherapy. METHODS A total of 14 patients undergoing chemotherapy for gastrointestinal cancer participated in the 4-week study. Participants carried an Android phone and wore a Fitbit device for the duration of the study and also completed daily severity ratings of 12 common symptoms. Symptom severity ratings were summed to create a total symptom burden score for each day, and ratings were centered on individual patient means and categorized into low, average, and high symptom burden days. Day-level features were extracted from raw mobile phone sensor and Fitbit data and included features reflecting mobility and activity, sleep, phone usage (eg, duration of interaction with phone and apps), and communication (eg, number of incoming and outgoing calls and messages). We used a rotation random forests classifier with cross-validation and resampling with replacement to evaluate population and individual model performance and correlation-based feature subset selection to select nonredundant features with the best predictive ability. RESULTS Across 295 days of data with both symptom and sensor data, a number of mobile phone and Fitbit features were correlated with patient-reported symptom burden scores. We achieved an accuracy of 88.1% for our population model. The subset of features with the best accuracy included sedentary behavior as the most frequent activity, fewer minutes in light physical activity, less variable and average acceleration of the phone, and longer screen-on time and interactions with apps on the phone. Mobile phone features had better predictive ability than Fitbit features. Accuracy of individual models ranged from 78.1% to 100% (mean 88.4%), and subsets of relevant features varied across participants. CONCLUSIONS Passive sensor data, including mobile phone accelerometer and usage and Fitbit-assessed activity and sleep, were related to daily symptom burden during chemotherapy. These findings highlight opportunities for long-term monitoring of cancer patients during chemotherapy with minimal patient burden as well as real-time adaptive interventions aimed at early management of worsening or severe symptoms.

Evaluating the Consistency of Current Mainstream Wearable Devices in Health Monitoring: A Comparison Under Free-Living Conditions (2017)

Journal of Medical Internet Research

Authors: Wen, D., Zhang, X., Liu, X. and Lei, J.

Abstract

Background: Wearable devices are gaining increasing market attention; however, the monitoring accuracy and consistency of the devices remains unknown. Objective: The purpose of this study was to assess the consistency of the monitoring measurements of the latest wearable devices in the state of normal activities to provide advice to the industry and support to consumers in making purchasing choices. Methods: Ten pieces of representative wearable devices (2 smart watches, 4 smart bracelets of Chinese brands or foreign brands, and 4 mobile phone apps) were selected, and 5 subjects were employed to simultaneously use all the devices and the apps. From these devices, intact health monitoring data were acquired for 5 consecutive days and analyzed on the degree of differences and the relationships of the monitoring measurements ??by the different devices. Results: The daily measurements by the different devices fluctuated greatly, and the coefficient of variation (CV) fluctuated in the range of 2-38% for the number of steps, 5-30% for distance, 19-112% for activity duration, .1-17% for total energy expenditure (EE), 22-100% for activity EE, 2-44% for sleep duration, and 35-117% for deep sleep duration. After integrating the measurement data of 25 days among the devices, the measurements of the number of steps (intraclass correlation coefficient, ICC=.89) and distance (ICC=.84) displayed excellent consistencies, followed by those of activity duration (ICC=.59) and the total EE (ICC=.59) and activity EE (ICC=.57). However, the measurements for sleep duration (ICC=.30) and deep sleep duration (ICC=.27) were poor. For most devices, there was a strong correlation between the number of steps and distance measurements (R2 >.95), and for some devices, there was a strong correlation between activity duration measurements and EE measurements (R2 > .7). A strong correlation was observed in the measurements of steps, distance and EE from smart watches and mobile phones of the same brand, Apple or Samsung (R2 > 88). Conclusions: Although wearable devices are developing rapidly, the current mainstream devices are only reliable in measuring the number of steps and distance, which can be used as health assessment indicators. However, the measurement consistencies of activity duration, EE, sleep quality, and so on, are still inadequate, which require further investigation and improved algorithms. [J Med Internet Res 2017;19(3):e68]

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Examination of a Wearable Activity Tracker to Assess Children’s Physical Activity (2017)

Medicine & Science in Sports & Exercise

Authors: Kang, S.-K., An, H.-S., Hong, S. and Lee, J-M.

Abstract

ewer wearable activity monitors have the capability to measure heart rate (HR) from the user’s wrist using an optical blood flow sensor (i.e., photoplethysmography techniques), and none of the previous studies examining children’s free-living activity utilizing a newly developed wearable activity tracker which includes built-in HR sensor. PURPOSE: To examine PA intensity using the wearable HR monitor. METHODS: a total of 43 children (girls = 18, boys = 25), aged 8 - 12 years, participated in the study. Participants were asked to wear the Fitbit Charge HR (FHR) on their left (FHRL), right wrist (FHRR) and Polar HR (PHR) monitor on their chest, while completing 11 different activities lasted 48 mins, monitoring their HR. Oxygen consumption was measured throughout the routine with the Cosmed K4B2 metabolic analyzer. 10 min average values of the resting metabolic rate were used as one metabolic equivalent of task (MET) to categorize children’s PA intensity. Activity intensities using HR from the FHR were classified by calculating children’s target HR between 50 and 75% of their maximum HR as moderate intensity activity and greater than 75% of their maximum HR as a vigorous intensity activity. An estimate of children’s maximum age-related HR was obtained from the 208 - 0.7 (age) equation. Each intensity classified by the MET determined by HR was compared to the intensity classified by the MET determined by resting metabolic rate (i.e., criterion measure) to examine the measurement agreement. McNemar’s test was used to examine the measurement agreement for paired intensity frequency. RESULTS: After setting PA intensity classification with 50% and 75% of HR, the frequency determined by measured MET from the Cosmed K4B2 were 1002, 407, and 120 for light, moderate, and vigorous intensity. The frequency determined by HR monitor and FHR were as follow: 1076, 394, and 58 by PHR, 1393, 127, and 9 by FHRL, 1393, 129, and 7 by FHRR. The values of weighted Kappa statistics from the McNemar’s test were 0.40 (95% CL: 0.36-0.44) for the intensity by PHR, 0.21 (95% CL: 0.18-0.25) for the intensity by FHRL, 0.19 (95% CL: 0.16-0.23) for the intensity by FHRR. CONCLUSIONS: The agreement of PA intensity classified by the wearable activity tracker to the intensity classified the metabolic analyzer showed fair agreement.

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Exercise Among Women With Ovarian Cancer: A Feasibility and Pre-/Post-Test Exploratory Pilot Study. (2017)

Oncology Nursing Forum

Authors: Zhang, X., McClean, D., Ko, E., Morgan, M.A. and Schmitz, K.

Abstract

PURPOSE/OBJECTIVES: To establish the feasibility and acceptability of completing a higher dose of the planned physical activity volume among women with ovarian cancer, including those undergoing active treatment.  . DESIGN: A pre-/post-test exercise intervention. All participants were asked to complete 225 minutes per week of physical activity for 26 weeks. Multiple supports were provided, including exercise DVDs, self-reported logs, and an objective physical activity tracker (Fitbit®). . SETTING: Home-based exercise intervention with in-person training and telephone follow-ups. . SAMPLE: 10 women with ovarian cancer who were treated within Penn Medicine in Philadelphia, Pennsylvania. . METHODS: Home-based, in-person exercise counseling was provided by an exercise trainer weekly for the first six weeks and then monthly for a total of 26 weeks. Weekly follow-up telephone calls were used to assess exercise adherence and barriers to completing exercise, review symptom changes, and provide behavioral support.  . MAIN RESEARCH VARIABLES: Feasibility and acceptability. . FINDINGS: Eight participants completed the study and achieved at least 80% of the prescribed exercise dose. Five participants were undergoing chemotherapy simultaneously. Participants experienced no adverse events during the 26-week intervention. Compared to baseline, average steps increased by 1,593 per day and moderate-intensity physical activity increased by 15 minutes per day.  . CONCLUSIONS: A 225-minutes-per-week exercise program is feasible and acceptable in a population of patients with ovarian cancer. Participants significantly improved their physical activity during the 26-week intervention. . IMPLICATIONS FOR NURSING: The findings suggest that nursing professionals could recommend that women with ovarian cancer exercise 225 minutes per week regardless of cancer and/or treatment trajectory. For those experiencing aches and pains, behavioral supports and suggestions of a lower exercise dose are needed to maintain physical activity.

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Fitbit And Actigraph: A Comparison Of Physical Activity And Sedentary Time In Overweight/obese Adults (2017)

Medicine & Science in Sports & Exercise

Authors: Szabo-Reed, A.N., Willis, E., Ptomey, L., Washburn, R. and Donnelly, J.

Abstract

here is limited information regarding the validity of consumer targeted wearable physical activity (PA) trackers, such as the Fitbit, to assess PA in free-living adults. PURPOSE: To compare daily minutes of sedentary time, and moderate-to-vigorous (MVPA) colleted using two types of activity trackers, in a sample of overweight and obese adults (n = 12, BMI= 37±4 kg/m2, age = 48±12 yrs.) who completed a 6-mo. weight loss intervention (diet + self-directed PA) delivered using Facebook. METHODS: Participants wore a Fitbit FlexTM on their non-dominant wrist continuously over 6 mos. They were also asked to wear an ActiGraph GTX1TM on their non-dominant hip for 7 consecutive days at both baseline and 6 mos. Fitbit and ActiGraph data for a minimum of one 10-hr. day at baseline and 6 mos. was required for inclusion in this analysis. Categorization of sedentary time and MVPA was derived from the Fitbit algorithm or using NHANES Actigraph cut-points (Troiano, 2008). RESULTS: Sedentary time was significantly lower and MVPA was significantly higher when assessed with the Fitbit compared with the ActiGraph at both baseline (sedentary time: Fitbit = 427 ±168, ActiGraph = 639 ±132 min/d, p< 0.001; MPVA: Fitbit= 128 ±49, ActiGraph = 18 ±19 min/d, p <0.0001) or 6 mos. (sedentary time: Fitbit = 459 ±168, ActiGraph = 613 ±103 min/d, p= 0.001; MPVA: Fitbit= 123±53, ActiGraph= 14 ±10 min/d, p<0.0001). Change in both sedentary time and MVPA from baseline to 6 mos. was not statistically significant measured either with the Fitbit (sedentary time = +63 ±46, p =0.16; MVPA = -8±13 min/d, p = 0.72) or the ActiGraph (sedentary time = - 49±52, p =0.39; MVPA = -2±13 min/d, p = 0.48). CONCLUSIONS: The Fitbit significantly underestimated sedentary time and overestimated MVPA when compared with the ActiGraph in a small sample. Changes in sedentary time and MVPA over 6 mos. were non-significant when assessed by either the Fitbit or ActiGraph. These observations suggest that the Fitbit, which is relatively inexpensive when compared with the ActiGraph, may be useful for assessing changes in sedentary time and MVPA in response to an intervention. However, the absolute values for sedentary time and MVPA assessed by the Fitbit are questionable, and worthy of additional investigation in larger samples of free-living adults.Funded by Kansas City Life Sciences Institute

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Fitbit Charge HR Wireless Heart Rate Monitor: Validation Study Conducted Under Free-Living Conditions (2017)

JMIR mHealth and uHealth

Authors: Gorny, A.W., Liew, S.J., Tan, C.S. and Müller-Riemenschneider, F.

Abstract

Background: Many modern smart watches and activity trackers feature an optical sensor that estimates the wearer's heart rate. Recent studies have evaluated the performance of these consumer devices in the laboratory. Objective: The objective of our study was to examine the accuracy and sensitivity of a common wrist-worn tracker device in measuring heart rates and detecting 1-min bouts of moderate to vigorous physical activity (MVPA) under free-living conditions. Methods: Ten healthy volunteers were recruited from a large university in Singapore to participate in a limited field test, followed by a month of continuous data collection. During the field test, each participant would wear one Fitbit Charge HR activity tracker and one Polar H6 heart rate monitor. Fitbit measures were accessed at 1-min intervals, while Polar readings were available for 10-s intervals. We derived intraclass correlation coefficients (ICCs) for individual participants comparing heart rate estimates. We applied Centers for Disease Control and Prevention heart rate zone cut-offs to ascertain the sensitivity and specificity of Fitbit in identifying 1-min epochs falling into MVPA heart rate zone. Results: We collected paired heart rate data for 2509 1-min epochs in 10 individuals under free-living conditions of 3 to 6 hours. The overall ICC comparing 1-min Fitbit measures with average 10-s Polar H6 measures for the same epoch was .83 (95% CI .63-.91). On average, the Fitbit tracker underestimated heart rate measures by −5.96 bpm (standard error, SE=0.18). At the low intensity heart rate zone, the underestimate was smaller at −4.22 bpm (SE=0.15). This underestimate grew to −16.2 bpm (SE=0.74) in the MVPA heart rate zone. Fitbit devices detected 52.9% (192/363) of MVPA heart rate zone epochs correctly. Positive and negative predictive values were 86.1% (192/223) and 92.52% (2115/2286), respectively. During subsequent 1 month of continuous data collection (270 person-days), only 3.9% of 1-min epochs could be categorized as MVPA according to heart rate zones. This measure was affected by decreasing wear time and adherence over the period of follow-up. Conclusions: Under free-living conditions, Fitbit trackers are affected by significant systematic errors. Improvements in tracker accuracy and sensitivity when measuring MVPA are required before they can be considered for use in the context of exercise prescription to promote better health. [JMIR Mhealth Uhealth 2017;5(10):e157]

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Fitbit Vs Six Minute Walk in PAH (2017)

American Journal of Respiratory and Critical Care Medicine

Authors: Sehgal, S., Chowdhury, A., Rabih, F., Gadre, A. and Highland, K.B.

Abstract

Rationale: The six minute walk test is a widely used instrument for monitoring and prognostication in patients with pulmonary arterial hypertension (PAH). It is a valid measure of exercise capacity and has been used as an endpoint in clinical trials. Limitations include a ‘ceiling effect’ in patients with minimal functional limitation and confounding factors affecting mobility. Accelerometers measure an individual's activity in step counts. A piezo-electric crystal measures acceleration, which is quantified as steps. Accelerometers have been validated as a measure of step count in patients with chronic lung disease. In patients with PAH, activity measured by an accelerometer has correlated with WHO functional class, six minute walk distance and survival. We prospectively studied the use of a wrist worn accelerometer (Fitbit ChargeHR) as a monitoring tool in patients with PAH. We present initial data from the first two weeks of patient monitoring. Methods: 30 ambulatory patients with WHO group one PAH were enrolled. A Fitbit ChargeHR was worn by the patient on the wrist until their next follow up visit. Six minute walk test, physical exam and WHO functional class stratification were done during the visits. Serum biomarkers and ECHO were done if clinically indicated. Pearson correlation test was used for continuous variables. ANOVA was performed for categorical variables. Results: 30 patients with WHO group one PAH (23- idiopathic, 7- connective tissue disease) with a mean age 50.49 ± 12.97 were enrolled. Mean six minute walk distance (6MWD) was 368.6 ± 144 m, WHO functional class classification was FC I- 10%, II-46%, III-36 %, IV- 2% The mean daily step count (r 0.55, p 0.004) and peak daily six minute step counts (r 0.44, p 0.01) in the first two weeks, correlated with the baseline 6MWD. Mean daily step count correlated with ability to self-care, but not with mobility, usual care, anxiety or pain. Both the daily step count and 6MWD did not correlate with NTproBNP levels and ECHO parameters (RA dilatation, LA dilatation, RV function, RVSP). Correlation of Step count with six minute walk distance – Pearson correlation Mean step count (two weeks) R=0.55 P=0.004 Peak daily six minute walk step count R=0.46 P=0.01 Conclusions: We demonstrate that daily step count measured by a wrist worn accelerometer (Fitbit ChargeHR) correlates with the 6MWD and ability to self-care in patients with PAH. 6MWD and daily step counts in our patients did not correlate with other PAH parameters measured. The Fitbit ChargeHR can be used to measure activity and a change over time may be useful monitoring tool.

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Healthy lifestyle intervention for adult clinic patients with type 2 diabetes mellitus (2017)

Diabetes Management

Authors: Coughlin, S.S., Hatzigeorgiou, C., Anglin, J., Xie, D., Besenyi, G.M., De Leo, G., Stewart, J. and Wilkins, T.

Abstract

Background: Diet and exercise therapy have been reported to be effective in improving blood glucose control and are an important part of treatment of type 2 diabetes mellitus. Objective: The goal of this study is to examine the efficacy of a healthy lifestyle intervention for adult clinic patients with type 2 diabetes mellitus, as measured by Hgb-A1c, cardiovascular indicators, physical activity, weight, and BMI. Also of interest are optimal strategies for subject recruitment, the number of intervention sessions attended, and participant use of the Fitbit watch to monitor their physical activity and track food and beverage consumption. Methods: A pre/post-test design will be used in this pilot study. Non-institutionalized adult patients (n=50) aged 18-65 years who have been seen at the Augusta Health outpatient clinics (General Internal Medicine or Family Medicine) for type 2 diabetes in the past 12 months, and who are interested in reducing their risk of disease recurrence through healthy lifestyle behaviors, will be eligible to participate. At orientation visit, eligible individuals will be asked to provide written informed consent. Consenting volunteers (n=50) will be asked to complete the baseline and 6-month follow-up questionnaire and to participate in 12 weekly group sessions of 90 min duration, involving physical activity and to meet with a dietitian (baseline, one month, 90 days) to receive individualized advice on diet and nutrition. The technology–based intervention will use wrist-worn Fitbit Blaze physical activity monitoring devices. Conclusions: This pilot study will provide important information about the feasibility and preliminary efficacy of a healthy lifestyle intervention for adult clinic patients with type 2 diabetes mellitus. The use of consumer-facing devices such as the Fitbit watch has the potential advantage over the use of research accelerometers, pedometers, or actigraphs in increasing the likelihood that the intervention will be sustainable after the study ends.

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How Accurate Is Your Activity Tracker? A Comparative Study of Step Counts in Low-Intensity Physical Activities (2017)

JMIR Mhealth and Uhealth

Authors: Alinia, P., Cain, C., Fallahzadeh, R., Shahrokni, A., Cook, D. and Ghasemzadeh, H.

Abstract

Background: As commercially available activity trackers are being utilized in clinical trials, the research community remains uncertain about reliability of the trackers, particularly in studies that involve walking aids and low-intensity activities. While these trackers have been tested for reliability during walking and running activities, there has been limited research on validating them during low-intensity activities and walking with assistive tools. Objective: The aim of this study was to (1) determine the accuracy of 3 Fitbit devices (ie, Zip, One, and Flex) at different wearing positions (ie, pants pocket, chest, and wrist) during walking at 3 different speeds, 2.5, 5, and 8 km/h, performed by healthy adults on a treadmill; (2) determine the accuracy of the mentioned trackers worn at different sites during activities of daily living; and (3) examine whether intensity of physical activity (PA) impacts the choice of optimal wearing site of the tracker. Methods: We recruited 15 healthy young adults to perform 6 PAs while wearing 3 Fitbit devices (ie, Zip, One, and Flex) on their chest, pants pocket, and wrist. The activities include walking at 2.5, 5, and 8 km/h, pushing a shopping cart, walking with aid of a walker, and eating while sitting. We compared the number of steps counted by each tracker with gold standard numbers. We performed multiple statistical analyses to compute descriptive statistics (ie, ANOVA test), intraclass correlation coefficient (ICC), mean absolute error rate, and correlation by comparing the tracker-recorded data with that of the gold standard. Results: All the 3 trackers demonstrated good-to-excellent (ICC>0.75) correlation with the gold standard step counts during treadmill experiments. The correlation was poor (ICC<0.60), and the error rate was significantly higher in walker experiment compared to other activities. There was no significant difference between the trackers and the gold standard in the shopping cart experiment. The wrist worn tracker, Flex, counted several steps when eating (P<.01). The chest tracker was identified as the most promising site to capture steps in more intense activities, while the wrist was the optimal wearing site in less intense activities. Conclusions: This feasibility study focused on 6 PAs and demonstrated that Fitbit trackers were most accurate when walking on a treadmill and least accurate during walking with a walking aid and for low-intensity activities. This may suggest excluding participants with assistive devices from studies that focus on PA interventions using commercially available trackers. This study also indicates that the wearing site of the tracker is an important factor impacting the accuracy performance. A larger scale study with a more diverse population, various activity tracker vendors, and a larger activity set are warranted to generalize our results.

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Implementation of a Home Monitoring System for Heart Failure Patients: A Feasibility Study. (2017)

JMIR Research Protocols

Authors: Kohn, M.S., Haggard, J., Kreindler, J., Birkeland, K., Kedan, I., Zimmer, R. and Khandwalla, R.

Abstract

BACKGROUND Improving the management of patients with complex chronic disease is a substantial undertaking with the simultaneous goals of improving patient outcomes and controlling costs. Reducing avoidable hospitalization for such patients is a step toward both objectives. Some of the deterioration experienced in chronic disease patients occurs outside the view of their clinicians, and before the patient becomes overtly symptomatic. Home monitoring has been used for more than 20 years to detect deterioration earlier so that the patients could be treated before they became ill enough to require hospitalization. Patient participation is an important requirement for successful home monitoring. There has been some concern that patients would be unwilling or unable to engage in a program that collected multiple measurements. The Cedars-Sinai Cardiology Center provides a high-touch, intense management program for patients with congestive heart failure (CHF). A group of their patients were chosen to join a complex, multidevice home monitoring system to see whether such patients would find value in the additional effort. OBJECTIVE The objective of our study was to determine whether patients already actively engaged in a high-touch intensive management program for CHF would take on the additional burden of a complex home monitoring effort. METHODS A total of 20 patients from the Cedars-Sinai group were enrolled in a monitoring program utilizing 5 different devices. Anonymous surveys were collected from the patients to assess their satisfaction with the program. RESULTS In total, 90% (18/20) completed the program, and 61% (11/20) submitted the survey. Among the 18 patients, overall compliance with the requested measurements was 70%. It was found that 73% (8/11) felt better about their health as a result of the program, whereas another 73% (8/11) believed that the care team now had a better picture of their health. CONCLUSIONS Substantial patient compliance and satisfaction can be achieved in a sophisticated home monitoring program.

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Implementation of a workplace intervention using financial rewards to promote adherence to physical activity guidelines: a feasibility study (2017)

BMC Public Health

Authors: Losina, E., Smith, S.R., Usiskin, I.M., Klara, K.M., Michl, G.L., Deshpande, B.R., Yang, H.Y., Smith, K.C., Collins, J.E. and Katz, J.N.

Abstract

We designed and implemented the Brigham and Women's Wellness Initiative (B-Well), a single-arm study to examine the feasibility of a workplace program that used individual and team-based financial incentives to increase physical activity among sedentary hospital employees. We enrolled sedentary, non-clinician employees of a tertiary medical center who self-reported low physical activity. Eligible participants formed or joined teams of three members and wore Fitbit Flex activity monitors for two pre-intervention weeks followed by 24 weeks during which they could earn monetary rewards. Participants were rewarded for increasing their moderate-to-vigorous physical activity (MVPA) by 10% from the previous week or for meeting the Centers for Disease Control and Prevention (CDC) physical activity guidelines (150 min of MVPA per week). Our primary outcome was the proportion of participants meeting weekly MVPA goals and CDC physical activity guidelines. Secondary outcomes included Fitbit-wear adherence and factors associated with meeting CDC guidelines more consistently. B-Well included 292 hospital employees. Participants had a mean age of 38 years (SD 11), 83% were female, 38% were obese, and 62% were non-Hispanic White. Sixty-three percent of participants wore the Fitbit ≥4 days per week for ≥20 weeks. Two-thirds were satisfied with the B-Well program, with 79% indicating that they would participate again. Eighty-six percent met either their personal weekly goal or CDC physical activity guidelines for at least 6 out of 24 weeks, and 52% met their goals or CDC physical activity guidelines for at least 12 weeks. African Americans, non-obese subjects, and those with lower impulsivity scores reached CDC guidelines more consistently. Our data suggest that a financial incentives-based workplace wellness program can increase MVPA among sedentary employees. These results should be reproduced in a randomized controlled trial. Clinicaltrials.gov, NCT02850094 . Registered July 27, 2016 [retrospectively registered].

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Measuring and understanding adherence in a home-based exercise intervention during chemotherapy for early breast cancer (2017)

Breast Cancer Research and Treatment

Authors: Nyrop, K.A., Deal, A.M., Choi, S.K., Wagoner, C.W., Lee, J.T., Wood, A., Anders, C., Carey, L.A., Dees, E.C., Jolly, T.A., Reeder-Hayes, K.E. and Muss, H.B.

Abstract

PURPOSE Ensuring and measuring adherence to prescribed exercise regimens are fundamental challenges in intervention studies to promote exercise in adults with cancer. This study reports exercise adherence in women who were asked to walk 150 min/week throughout chemotherapy treatment for early breast cancer. Participants were asked to wear a Fitbit(TM) throughout their waking hours, and Fitbit steps were uploaded directly into study computers. METHODS Descriptive statistics are reported, and both unadjusted and multivariable linear regression models were used to assess associations between participant characteristics, breast cancer diagnosis, treatment, chemotherapy toxicities, and patient-reported symptoms with average Fitbit steps/week. RESULTS Of 127 women consented to the study, 100 had analyzable Fitbit data (79%); mean age was 48 and 31% were non-white. Mean walking steps were 3956 per day. Nineteen percent were fully adherent with the target of 6686 steps/day and an additional 24% were moderately adherent. In unadjusted analysis, baseline variables associated with fewer Fitbit steps were: non-white race (p = 0.012), high school education or less (p = 0.0005), higher body mass index (p = 0.0024), and never/almost never drinking alcohol (p = 0.0048). Physical activity variables associated with greater Fitbit steps were: pre-chemotherapy history of vigorous physical activity (p = 0.0091) and higher self-reported walking minutes/week (p textless 0.001), and higher outcome expectations from exercise (p = 0.014). Higher baseline anxiety (p = 0.03) and higher number of chemotherapy-related symptoms rates "severe/very severe" (p = 0.012) were associated with fewer steps. In multivariable analysis, white race was associated with 12,146 greater Fitbit steps per week (p = 0.004), as was self-reported walking minutes prior to start of chemotherapy (p < 0.0001). CONCLUSIONS Inexpensive commercial-grade activity trackers, with data uploaded directly into research computers, enable objective monitoring of home-based exercise interventions in adults diagnosed with cancer. Analysis of the association of walking steps with participant characteristics at baseline and toxicities during chemotherapy can identify reasons for low/non-adherence with prescribed exercise regimens.

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Metformin to Augment Strength Training Effective Response in Seniors (MASTERS): study protocol for a randomized controlled trial (2017)

Trials

Authors: Long, D.E., Peck, B.D., Martz, J.L., Tuggle, S.C., Bush, H.M., McGwin, G., Kern, P.A., Bamman, M.M. and Peterson, C.A.

Abstract

Background Muscle mass and strength are strong determinants of a person's quality of life and functional independence with advancing age. While resistance training is the most effective intervention to combat age-associated muscle atrophy (sarcopenia), the ability of older adults to increase muscle mass and strength in response to training is blunted and highly variable. Thus, finding novel ways to complement resistance training to improve muscle response and ultimately quality of life among older individuals is critical. The purpose of this study is to determine whether a commonly prescribed medication called metformin can be repurposed to improve the response to resistance exercise training by altering the muscle tissue inflammatory environment. Methods/design Individuals aged 65 and older are participating in a two-site, randomized, double-blind, placebo-controlled trial testing the effects of metformin or placebo on muscle size, strength, and physical function when combined with a progressive resistance training program. Participants consume 1700 mg of metformin per day or placebo for 2 weeks before engaging in a 14-week progressive resistance training regimen, with continued metformin or placebo. Participants are then monitored post-training to determine if the group taking metformin derived greater overall benefit from training in terms of muscle mass and strength gains than those on placebo. Muscle biopsies are taken from the vastus lateralis at three time points to assess individual cellular and molecular adaptations to resistance training and also changes in response to metformin. Discussion The response of aged muscles to a resistance training program does not always result in a positive outcome; some individuals even experience a loss in muscle mass following resistance training. Thus, adjuvant therapies, including pharmacological ones, are required to optimize response to training in those who do not respond and may be at increased risk of frailty. This is the first known metformin repurposing trial in non-diseased individuals, aimed specifically at the resistance exercise “non-responder” phenotype present in the aging population. The overall goal of this trial is to determine if combined exercise-metformin intervention therapy will benefit older individuals by promoting muscle hypertrophy and strength gains, thereby maintaining functional independence.

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Minimal Detectable Change Thresholds and Responsiveness of Zephyr Bioharness & Fitbit Charge Devices. (2017)

Journal of Strength and Conditioning Research

Authors: Nazari, G. and MacDermid, J.C.

Abstract

The aim of the current study was to define the MDC thresholds for Zephyr Bioharness (ZB) and Fitbit Charge (FC-HR) heart rate variables, and to establish the internal responsiveness of ZB and FC-HR devices in terms of their heart rate, respiratory rate variables and number of steps taken variables, in a healthy sample of males and females at resting, sub-maximal activity and throughout recovery phases. A total of sixty participants (30 females, 48 ± 15) and (30 males, 48 ± 15) were recruited using stratified convenience and snowball sampling approaches from our university student, staff and faculty population. At rest, MDC90 values of ± 4.89 and ± 5.15 were noted for ZB and FC-HR devices respectively. Throughout the recovery, thresholds of ±8.14 for ZB and ± 8.74 for FC-HR were reported. During the sub-maximal phases, scores of ± 8.18 and ± 9.35 were established for ZB and FC-HR respectively. From a resting to a sub-maximal state, the Standardized Response Means for ZB and FC-HR heart rate variables exhibited large responsiveness of SRMZB-HR=4.42; SRMFC-HR=4.04. In addition, the ZB respiratory rate variable showed the largest effect size of SRMZB-RR= 2.55. Similarly, large effect size of SRMFC-ST=1.76 were reported for the FC-HR steps taken variable. From a sub-maximal to a recovery state, he Standardized Response Means for ZB and FC-HR heart rate variables demonstrated effect sizes of SRMZBHR= -3.10; SRMFC-HR= -3.12). Furthermore, the ZB respiratory rate variable displayed similar internal responsiveness measures of SRMZB-RR= -2.45. To conclude, Similar MDC heart rate thresholds can be expected using the ZB and FC-HR devices, and that the two devices demonstrated large internal responsiveness in our healthy male and female cohort when transitioning from resting to submaximal states and vice-versa. Our findings suggest that the ZB and FC-HR devices can be used in monitoring performance improvements or deterioration over time, and would allow qualified personnel in assessing the effectiveness of exercise programs in healthy individuals.

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Mobile Device Accuracy for Step Counting Across Age Groups. (2017)

JMIR mHealth and uHealth

Authors: Modave, F., Guo, Y., Bian, J., Gurka, M.J., Parish, A., Smith, M.D., Lee, A.M. and Buford, T.W.

Abstract

BACKGROUND Only one in five American meets the physical activity recommendations of the Department of Health and Human Services. The proliferation of wearable devices and smartphones for physical activity tracking has led to an increasing number of interventions designed to facilitate regular physical activity, in particular to address the obesity epidemic, but also for cardiovascular disease patients, cancer survivors, and older adults. However, the inconsistent findings pertaining to the accuracy of wearable devices for step counting needs to be addressed, as well as factors known to affect gait (and thus potentially impact accuracy) such as age, body mass index (BMI), or leading arm. OBJECTIVE We aim to assess the accuracy of recent mobile devices for counting steps, across three different age groups. METHODS We recruited 60 participants in three age groups: 18-39 years, 40-64 years, and 65-84 years, who completed two separate 1000 step walks on a treadmill at a self-selected speed between 2 and 3 miles per hour. We tested two smartphones attached on each side of the waist, and five wrist-based devices worn on both wrists (2 devices on one wrist and 3 devices on the other), as well as the Actigraph wGT3X-BT, and swapped sides between each walk. All devices were swapped dominant-to-nondominant side and vice-versa between the two 1000 step walks. The number of steps was recorded with a tally counter. Age, sex, height, weight, and dominant hand were self-reported by each participant. RESULTS Among the 60 participants, 36 were female (60%) and 54 were right-handed (90%). Median age was 53 years (min=19, max=83), median BMI was 24.1 (min=18.4, max=39.6). There was no significant difference in left- and right-hand step counts by device. Our analyses show that the Fitbit Surge significantly undercounted steps across all age groups. Samsung Gear S2 significantly undercounted steps only for participants among the 40-64 year age group. Finally, the Nexus 6P significantly undercounted steps for the group ranging from 65-84 years. CONCLUSIONS Our analysis shows that apart from the Fitbit Surge, most of the recent mobile devices we tested do not overcount or undercount steps in the 18-39-year-old age group, however some devices undercount steps in older age groups. This finding suggests that accuracy in step counting may be an issue with some popular wearable devices, and that age may be a factor in undercounting. These results are particularly important for clinical interventions using such devices and other activity trackers, in particular to balance energy requirements with energy expenditure in the context of a weight loss intervention program.

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Nurses’ Physical Activity Study: Caring For You So You Can Care For Others (2017)

Medicine & Science in Sports & Exercise

Authors: Das, B.M., Clemmons, B.S., Kemble, C.D., Schreier, A.M. and Mahar, M.T.

Abstract

Nurses face multiple negative stressors and report the greatest stress of all health care workers. The stress can have a negative effect on the health of nurses (e.g., obesity, fatigue, decrease in quality of life and satisfaction with life, and burnout). Stress is common among nurses with negative impacts on a nurse’s health as well as the quality of care patients receive. It is important for nurses to implement self-care strategies techniques (e.g., physical activity) to lower feelings of stress. PURPOSE: To examine the relationship between physical activity levels and measures of health among nurses in eastern NC. METHODS: Nurses (n = 62, 94% females; 85% White; age = 42.2 ± 11.7) were assessed for physical activity via the Fitbit Flex activity tracker over a 7 day period and the International Physical Activity Questionnaire. Nurses reported burnout, stress, and fatigue using self-reported questionnaires. Body mass index was measured by dividing weight (kg) by the participant’s squared height (m). RESULTS: BMI was significantly correlated with moderate-to-vigorous physical activity (r = -.28), steps (r = -0.29), and vigorous intensity physical activity (r = -.32). Fatigue was significantly correlated with moderate-to-vigorous physical activity (r = -.27). Stress was significantly correlated with steps (r = -.27), moderate intensity physical activity (r = -.25), and light intensity physical activity (r = -.40). Significant associations were also found between quality of life and light intensity physical activity (r = .40), moderate intensity physical activity (r = .30), and steps (r = .29). A relationship was found between high intensity physical activity and burnout (r = .23, p < .001) and between steps and compassion fatigue (r = -.26, p < .05). CONCLUSIONS: Findings demonstrated that stress, fatigue, and burnout were lowly correlated with physical activity among nurses. Thus, a physical activity intervention among nurses may be needed to fully see the effects of physical activity on nurses’ health, and ultimately patient health and safety.

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Patient-Specific Activity Level Benchmarks During Recovery for Total Knee Arthoplasty (2017)

Orthopaedic Proceedings

Authors: Twiggs, J., Roe, J., Salmon, L., Miles, B. and Theodore, W.

Abstract

Introduction: Ambulation in the postoperative period following TKR is a marker of speed of recovery and, potentially longer term outcomes. However, patient lifestyle factors are a major confounder. This study sought to develop a model of expected patient step count taking into account preoperative condition and demographics in order to benchmark recovery at a patient specific level. Method: 94 patients were recruited to the study. BMI, demographics, the Short Form 12 (SF-12) and the Knee injury and Osteoarthritis Outcome Score (KOOS) were all captured preoperatively. Step count was measured using commercially available Fitbit devices preoperatively, immediately postoperatively and at 6 weeks postoperatively. Stepwise multiple linear regression models were developed using the preoperative information to define a predictive model of the postoperative step count levels. Spearman's Rho correlations for all relevant data series were also calculated. Results: Of the personal and clinical characteristics, BMI and the SF-12 physical component score had the strongest correlations with outcome. Prior step count periods all had significant correlations with later step count periods. The most significant correlations occurred between the 6 week postoperative step count period and the preoperative period (0.709), while correlations with the period immediately following surgery were weaker (0.389 and 0.536 for preoperative and 6 week postoperative step counts respectively.) All are significantly different from 0 (to p textless 0.01.) Likewise, BMI had a significantly negative relationship with step count (-0.526, -0.346 and -0.553 for the preoperative, immediate postoperative and 6 week postoperative periods, see Figure 2), as did the KOOS activities of daily living score and the SF-12 physical health component score. Males were significantly less mobile than females during recovery. A multiple linear regression model of 6 week step count using prior data had an adjusted R2 of 0.754, explaining much of the variation, but the immediate postoperative period performed poorly. Predictors in the 6 week model were gender, preoperative SF-12 score, preoperative and immediate postoperative step count. Conclusions: Patient specific factors, including but not limited to that from prior step count periods need to be considered if using step count as a means of benchmarking patient recovery after surgery. The variation in recovery at 6 weeks is more readily explained with the data collected than in the immediate postoperative period, where variations in specific care received, anaesthetic response or surgical outcomes might be more expected to have an impact. Reporting patient performance against customised goals on an individual patient basis could provide a means to drive greater patient mobility and appropriate activity levels during postoperative recovery.

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Physical Activities in Patients with β-Thalassemia As Measured By Fitbit in Association with Patient-Reported Outcomes (2017)

Blood

Authors: Kattamis, A., Sutcharitchan, P., Taher, A., Cappellini, M.D., Mahmoud, D., Pariseau, J., Laadem, A., Khan, A., Hu, X.H. and Viprakasit, V.

Abstract

Background: Tiredness, weakness, and shortness of breath are the most commonly reported symptoms in patients with β-thalassemia, and they may also adversely affect the quality of life (QoL) of patients. We aimed to explore the associations between β-thalassemia symptom severity and QoL in relation to physical activities, as tracked by Fitbit wearable electronic devices (Fitbit, Inc., San Francisco, CA). Method: Adult patients with β-thalassemia under routine clinical care were enrolled in a prospective observational study. All patients completed Short Form 36 Health Survey version 2 (SF-36v2) and Functional Assessment of Cancer Therapy (FACT)-Anemia (An) questionnaires at baseline and then once every 3 weeks using a hand-held electronic device. Patients with transfusion-dependent (TD) β-thalassemia also completed the Transfusion-dependent QoL (TranQoL) questionnaire, a disease-specific QoL instrument developed for TD patients, with the same scheduling. Transfusion dependent was defined as receiving ≥ 6 red blood cell units in the 24 weeks prior to study entry and no transfusion-free period for ≥ 35 days during that period. Patients with non-transfusion-dependent (NTD) β-thalassemia were instructed to complete the NTDT-PROtextcopyright daily, a symptom diary developed specifically for patients with NTD β-thalassemia with 2 domains: tiredness/weakness (T/W; score range: 0-40) and shortness of breath (SoB; score range: 0-20) with higher scores indicating more severe symptoms. Physical activities were passively tracked by a Fitbit wearable electronic device in terms of steps taken and floors climbed. This analysis examined the association between physical activities at week 1 of the study with QoL measurements and β-thalassemia symptom severity at baseline. For this analysis, average daily steps taken and floors climbed were grouped into quartile categories for those patients who had 4 or more days of Fitbit data during week 1. Results: A total of 102 patients with β-thalassemia (52 TD and 50 NTD) were enrolled; the mean age of patients was 31.2 years and 70 (68.6%) were females. A total of 91 patients had Fitbit data and, on average, they took 10,811 steps (median: 9,656) and climbed 16.0 floors (median: 10.0) daily. There were no associations observed between the number of steps taken and QoL measurements and β-thalassemia symptom severity. The floors climbed, however, were associated with SF-36v2 Physical Functioning and General Health domains. Patients in the lowest quartile for floors climbed had statistically significant lower Physical Functioning and General Health scores compared with patients in the highest quartile for floors climbed (47.0 vs 52.3; P textless 0.01; and 42.1 vs 46.3; P= 0.01, respectively). Floors climbed were also associated with the NTDT-PROtextcopyright symptom severity scores for T/W and SoB domains. Patients in the lowest quartile for floors climbed had T/W and SoB domain scores of 12.8 and 4.6, respectively, compared with those patients in the highest quartile for floors climbed who had scores of 4.9 and 0.8 (P textless 0.01 and P= 0.02). Conclusions: Steps taken tracked by Fitbit did not appear to be associated with QoL and symptom severity in patients with β-thalassemia. Floors climbed, however, were associated with SF-36v2 Physical Functioning and General Health domains, and β-thalassemia symptom severity. Floors climbed is likely to be a more sensitive endpoint as a measurement for physical activities in clinical studies.

Physical Activity Trackers in Combination with Motivational Interviewing to Increase Activity (2017)

Medicine & Science in Sports & Exercise

Authors: Perez, M., Ellingson, L., Bai, Y., Peyer, K. and Welk, G.

Abstract

Evidence is equivocal regarding the benefits of wearable technology for increasing physical activity. Use of these devices in combination with health coaching strategies like motivational interviewing (MI) may be more effective. PURPOSE: The study examined if physical activity trackers increase activity levels in healthy adults and if the addition of MI results in greater benefits. A secondary purpose was to examine characteristics of those who were successful in increasing physical activity versus those who were not in order to determine who is more likely to benefit from this type of intervention. METHODS: Ninety-four healthy men and women (mean age 41 ± 9 years) were randomly assigned to one of two groups for a 12-week intervention. Groups received either 1) a physical activity tracker (PAT) alone, or 2) a physical activity tracker and three sessions of MI (PAT+MI). Physical activity was assessed pre and post-intervention with accelerometers. Average steps per day were compared within and between groups pre- and post-intervention using paired and independent sample t-tests. Participants were then split into two groups based on whether they increased their mean daily step count from baseline. These post-hoc groups were then compared on demographic and baseline physical activity characteristics. RESULTS: Complete data were collected on 84 individuals. Physical activity measured in average steps per day did not increase significantly for either group (PAT+MI – pre: 7496 ± 2895 steps/day, post: 7624 ± 3557 steps/day; PAT – pre: 7519 ± 2259 steps/day, post: 7097 ± 2179 steps/day; p>0.05); further, no group differences were observed (p>0.05). When comparing those who improved over the intervention to those who did not, there were no differences in demographic characteristics including age, gender, income, or education level. However, those who improved over the intervention accumulated significantly fewer steps at baseline (6650 ± 2056 vs. 8522 ± 2871, p < 0.0001). CONCLUSION: The provision of a physical activity tracker (with or without brief MI sessions) was not sufficient to increase physical activity in this sample; however, individuals with low baseline activity achieved more significant benefits.

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Polysomnography vs Consumer Devices: Comparing Common Sleep Indices (2017)

Sleep

Authors: Wedderburn-Bisshop, J., Kharatishvili-Bredt, I., Martin, I. and Tolhurst, S.

Abstract

Introduction: As public interest in health tracking technology increases, so too does the prevalence of commercially available consumer activity devices and apps utilising actigraphy. With the increase of the population's ability to access this technology, and limited research available on the concordance of these devices with polysomnography (PSG), the accuracy, specificity and sensitivity of the FitbitCharge HR device's common sleep indices were compared and evaluated against those of Level 1 PSG in participants with a diagnosis of respiration within normal limits and those with varying degrees of sleep-disordered breathing (SDB). Methods: Analysis was performed on 41 participants (age, mean ± SD: 55?±?14 years; BMI ± SD: 32?±?6?kg/m2). The different categories of SDB were classified upon AASM PSG guidelines and consequently broken up into normal respiration (AHI = 5); mild OSA (AHI = 5 but = 14.99); moderate OSA (AHI = 15 but = 29.99); severe OSA (AHI = 30.0). Full overnight PSG was performed (in accordance with AASM guidelines) in a laboratory setting and recorded concurrently with the consumer device. Primary outcome measures were limited to sleep-onset latency (SOL), total sleep time (TST), wake after sleep-onset (WASO) and sleep-efficiency (SE). Exclusion criteria were applied. Results: These common sleep indices of Fitbit Charge HR were compared to similar indices of PSG using paired t-tests and Bland-Altman plots. Significant differences were seen in SOL for the participants within the category of respiration within normal limits, moderate OSA and severe OSA; WASO was significantly different in all categories; SE was significantly different in the category of moderate OSA; there were no significant differences in TST at any category. Conclusion: Previous research has shown that actigraphy has high sensitivity in detecting sleep, but poor specificity in detecting wake in persons with respiration within normal limits. This poster shows that there was a significant difference in the participants with SDB in their SOL, SE and WASO but no difference in TST when comparing the FitbitCharge HR to PSG.

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Promoting Optimal Physical Exercise for Life (PROPEL): aerobic exercise and self-management early after stroke to increase daily physical activity-study protocol for a stepped-wedge randomised trial. (2017)

BMJ Open

Authors: Mansfield, A., Brooks, D., Tang, A., Taylor, D., Inness, E.L., Kiss, A., Middleton, L., Biasin, L., Fleck, R., French, E., LeBlanc, K., Aqui, A. and Danells, C.

Abstract

INTRODUCTION Physical exercise after stroke is essential for improving recovery and general health, and reducing future stroke risk. However, people with stroke are not sufficiently active on return to the community after rehabilitation. We developed the Promoting Optimal Physical Exercise for Life (PROPEL) programme, which combines exercise with self-management strategies within rehabilitation to promote ongoing physical activity in the community after rehabilitation. This study aims to evaluate the effect of PROPEL on long-term participation in exercise after discharge from stroke rehabilitation. We hypothesise that individuals who complete PROPEL will be more likely to meet recommended frequency, duration and intensity of exercise compared with individuals who do not complete the programme up to 6 months post discharge from stroke rehabilitation. METHODS AND ANALYSIS Individuals undergoing outpatient stroke rehabilitation at one of six hospitals will be recruited (target n=192 total). A stepped-wedge design will be employed; that is, the PROPEL intervention (group exercise plus self-management) will be 'rolled out' to each site at a random time within the study period. Prior to roll-out of the PROPEL intervention, sites will complete the control intervention (group aerobic exercise only). Participation in physical activity for 6 months post discharge will be measured via activity and heart rate monitors, and standardised physical activity questionnaire. Adherence to exercise guidelines will be evaluated by (1) number of 'active minutes' per week (from the activity monitor), (2) amount of time per week when heart rate is within a target range (ie, 55%-80% of age-predicted maximum) and (3) amount of time per week completing 'moderate' or 'strenuous' physical activities (from the questionnaire). We will compare the proportion of active and inactive individuals at 6 months post intervention using mixed-model logistic regression, with fixed effects of time and phase and random effect of cluster (site). ETHICS AND DISSEMINATION To date, research ethics approval has been received from five of the six sites, with conditional approval granted by the sixth site. Results will be disseminated directly to study participants at the end of the trial, and to other stake holders via publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER NCT02951338; Pre-results.

Quantitative and qualitative measures of poststroke walking activity with inertial technologies (2017)

Annals of Physical and Rehabilitation Medicine

Authors: Duclos, N., Tavares, L.A., Parent, G., Aissaoui, R., Nadeau, S. and Duclos, C.

Abstract

OBJECTIVE Inertial technologies (activity monitors, inertial sensors) allow the evaluation of the number of steps and spatial-temporal parameters (STP) in daily life environments. However, activity monitors, generally worn at the hip, are not accurate for quantifying steps at slow walking speed (textless0.8m/s). Moreover, current models behind inertial sensors measurements estimate STP supposing symmetry between limbs. The current use of these tools decreases the accuracy of outdoor walking assessment in individuals poststroke since they generally walk slowly and have an asymmetrical gait pattern. The aim of this study was to assess the accuracy of: (1) an activity monitor placed at the ankle to count the number of steps and (2) an algorithm developed to estimate asymmetric STP in individuals poststroke. MATERIAL/PATIENTS AND METHODS Up to now, eight poststroke individuals who were independent walkers (with or without walking aid) were recruited. Study 1: an activity monitor (Fitbit® One) placed at the non-paretic ankle (not at the hip as recommended) was tested during a walk in a commercial center. The number of steps measured was compared to the one measured by video recording. Study 2: four inertial sensors (OPAL, APDM inc.) were placed bilaterally at the ankle and thigh of the participants and used to assess a new algorithm developed to estimate the right and left STP independently. The estimated STP was compared to those measured simultaneously by a GAITRite® walking mat. For each study, the agreement between data provided by the tools was estimated using Altman-Bland charts. RESULTS Among participants, the range of walking speed (0.4–1.2m/s) and STP asymmetry was large. In study 1, the Fitbit® One error for the number of steps was acceptable (0.14–4.60%), for participants walking faster than 0.4m/s. In study 2, the stride times were precisely estimated but the support times were underestimated (−13 [6.2]%) and the oscillation times overestimated (+30.1 [11.3]%). Spatial parameter estimation was inconsistent. DISCUSSION, CONCLUSION Placing the Fitbit® One at the non-paretic ankle is a suitable method for evaluating the amount of poststroke walking, except for very slow walkers. The algorithm for estimating STP from inertial sensors needs further work before being used in the community.

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Randomized controlled trial of increasing physical activity on objectively measured and self-reported cognitive functioning among breast cancer survivors: The memory & motion study (2017)

Cancer

Authors: Hartman, S.J., Nelson, S.H., Myers, E., Natarajan, L., Sears, D.D., Palmer, B.W., Weiner, L.S., Parker, B.A. and Patterson, R.E.

Abstract

BACKGROUND Increasing physical activity can improve cognition in healthy and cognitively impaired adults; however, the benefits for cancer survivors are unknown. The current study examined a 12-week physical activity intervention, compared with a control condition, on objective and self-reported cognition among breast cancer survivors. METHODS Sedentary breast cancer survivors were randomized to an exercise arm (n = 43) or a control arm (n = 44). At baseline and at 12 weeks, objective cognition was measured with the National Institutes of Health Cognitive Toolbox, and self-reported cognition using the Patient-Reported Outcomes Measurement Information System scales. Linear mixed-effects regression models tested intervention effects for changes in cognition scores. RESULTS On average, participants (n = 87) were aged 57 years (standard deviation, 10.4 years) and were 2.5 years (standard deviation, 1.3 years) post surgery. Scores on the Oral Symbol Digit subscale (a measure of processing speed) evidenced differential improvement in the exercise arm versus the control arm (b = 2.01; P < .05). The between-group differences in improvement on self-reported cognition were not statistically significant but were suggestive of potential group differences. Time since surgery moderated the correlation, and participants who were ≤2 years post surgery had a significantly greater improvement in Oral Symbol Digit score (exercise vs control (b = 4.00; P < .01), but no significant improvement was observed in patients who were >2 years postsurgery (b = −1.19; P = .40). A significant dose response was observed with greater increased physical activity associated with objective and self-reported cognition in the exercise arm. CONCLUSIONS The exercise intervention significantly improved processing speed, but only among those who had been diagnosed with breast cancer within the past 2 years. Slowed processing speed can have substantial implications for independent functioning, supporting the potential importance of early implementation of an exercise intervention among patients with breast cancer. Cancer 2017. © 2017 American Cancer Society.

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Reduction of Health Disparities in Appalachians With Multiple Cardiovascular Disease Risk Factors: A Randomized Controlled Trial (2017)

Circulation

Authors: Moser, D.K., Feltner, F., Biddle, M.J., Chung, M.L. and Lennie, T.A.

Abstract

Introduction: Appalachia is a socioeconomically austere environment with marked health disparities. People living in Appalachian Kentucky represent the top 1% for cardiovascular disease (CVD) risk, morbidity and mortality in the US. Hypothesis: We hypothesized that compared to control (referral of patients to a primary care provider), a culturally appropriate, self-care CVD risk reduction intervention (HeartHealth) would be superior in promoting improvement of these risk factors: tobacco use (urinary cotinine), blood pressure (BP), lipid profile (point-of-care device), body mass index, depressive symptoms (PHQ-9), and physical activity levels (Fitbit). Methods: The study was developed with a community advisory board of lay community members, business owners, church leaders, and healthcare providers. In this randomized trial, we enrolled 352 individuals living in Appalachian Kentucky who were at risk for CVD by virtue of having two or more CVD risk factors. The intervention was delivered in person to groups of 10 or less over 6 weeks. The HeartHealth intervention was designed to provide participants with self-care skills appropriate to CVD risk reduction while reducing barriers to risk reduction found in austere environments. The targeted CVD risk factors were measured at baseline, then 4 and 12 months post-intervention. Linear mixed models analysis was used to compare outcomes between the groups across time. Results: The intervention produced improvement in systolic and diastolic BP (p=0.002 and p=0.001 for group X time interaction [GXT])), total cholesterol (p=0.026 GXT), high density lipoprotein (p=0.026 GXT), body mass index (p=0.017 GXT), smoking status (p=0.001 GXT), physical activity (p=0.001 GXT) and depressive symptoms (p=0.019 GTX) compared to the control group, and these improvements were maintained through 12 months. There were no differences seen across time by group in low density lipoprotein or triglyceride levels.Conclusion: Interventions like HeartHealth that focus on self-care of CVD risk factors and that are derived from collaboration with the community of interest are highly appropriate and effective in underserved, socioeconomically distressed areas.

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Reversal of type 2 diabetes in youth who adhere to a very-low-energy diet: a pilot study (2017)

Diabetologia

Authors: Gow, M.L., Baur, L.A., Johnson, N.A., Cowell, C.T. and Garnett, S.P.

Abstract

Aims/hypothesis: The aim of the study was to investigate whether a very-low-energy diet (VLED) is a feasible and acceptable treatment option for type 2 diabetes in children and adolescents, and whether adherence can lead to rapid weight loss, reversal of type 2 diabetes and reduced liver fat as seen in adult studies. Methods: Eight participants with type 2 diabetes and obesity, aged 7–16 years, non-medicated (n?=?1) or treated with metformin (n?=?7) and in some cases insulin (n?=?3), followed a VLED (textless3360 kJ/day) for 8 weeks, then transitioned to a hypocaloric diet (~6300 kJ/day) that they followed to 34 weeks. HbA1c, fasting glucose and 2 h post-glucose load plasma glucose (2hG) were determined from fasting blood and an OGTT. Liver fat concentration was quantified using proton magnetic resonance spectroscopy. Adherence was defined as =5% weight loss during the 8 week VLED. Results: Adherers (n?=?5) and non-adherers (n?=?3) had median weight loss of 7.5% and 0.5%, respectively, at 8 weeks. Overall, HbA1c (mean [SE] 8.1% [0.7%] to 6.6% [0.5%]; p?=?0.004) and 2hG (15.6 [1.6] mmol/l to 11.3 [1.0] mmol/l; p?=?0.009) were significantly reduced at 8 weeks compared with baseline. Liver fat was also significantly reduced from baseline (14.7% [2.2%]) to 8 weeks (5.8% [1.7%]; p?=?0.001). Only three out of eight participants met non-alcoholic fatty liver disease (NAFLD) criteria (=5.5%) at 8 weeks, compared with eight out of eight at baseline. The three participants on insulin therapy at baseline were able to cease therapy during the 8 week VLED. At 34 weeks, adherers (n?=?5) achieved 12.3% weight loss, none met NAFLD criteria and four did not meet American Diabetes Association criteria for type 2 diabetes. Conclusions/interpretation: A VLED appears to be a feasible treatment option for some youth with type 2 diabetes on metformin therapy. Youth who agree to participate and adhere to a VLED achieve rapid weight loss, dramatic reductions in liver fat and reversal of type 2 diabetes. This highlights the capacity of a VLED to be used as a first-line treatment option in newly diagnosed youth. A larger trial with a control group and longer follow-up will be required to encourage a change in standard treatment.

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Screening of Atrial Fibrillation Using Wrist Photoplethysmography from a Fitbit Tracker (2017)

Iproceedings

Authors: Pantelopoulos, A., Faranesh, A., Milescu, A., Hosking, P., Venkatraman, S. and Heneghan, C.

Abstract

Background: Atrial Fibrillation is the most common clinically significant cardiac arrhythmia, estimated to affect between 2% ( 65 years of age) of the U.S. population. Screening and early detection of AF can help prevent associated stroke and cardiovascular disease. Commonly used monitoring devices are limited to short periods (textless 4 weeks) and are usually employed in symptomatic subjects. Wrist-worn wearables equipped with photoplethysmography (PPG) could potentially aid in AF screening, as they can be easily worn by most people for extended periods of time. Objective: This study aimed to investigate the ability of wrist-based PPG to detect the presence of AF in subjects while at rest. Methods: This study was conducted with the approval of local institutional review boards, and all patients provided written, informed consent. The first dataset consisted of 9 patients with persistent AF and 13 subjects with normal sinus rhythm. For these 22 subjects, PPG and ECG data were collected while sitting stationary for 15 minutes (awake dataset). A second dataset consisted of 10 patients with persistent AF and 27 subjects with no known diagnosis of AF. These subjects were asked to wear a Fitbit wrist-band which recorded PPG and accelerometry data during sleep (sleep dataset, 73 total nights). There was no overlap between subjects in the awake and sleep datasets. Results: Data were analyzed in overlapping 1 or 5-minute windows. Pulse Rate Variability (PRV) features, PPG morphology features and accelerometer features were extracted for each window. An algorithm was trained on the awake dataset and was validated on the sleep dataset. The performance was 95.7% (98%) sensitivity (Se) and 0.8% (0.8%) False Positive Rate (FPR) for 1 min (5 min) windows. We also investigated the shortest duration of an AF episode that could be detected by using synthesized data. With 1 minute analysis windows, the algorithm was sensitive down to 40-second episodes. Using 5-minute intervals, episodes down to 3 minutes could be reliably detected. Conclusions: Wrist-bands equipped with PPG sensors can be used to detect atrial fibrillation during sleep or during awake, stationary periods. While reliable detection of short AF episodes can be challenging due to the noisy nature of PPG signals, we have demonstrated that select PPG features can enable accurate detection of AF down to 40 second periods. These findings suggest that wrist-worn devices equipped with a PPG sensor could be used to screen for AF in high-risk subjects or monitor patients post treatment, but are limited to cases where users are not moving or exercising. Additional, larger clinical studies are planned for the future to validate these promising early results and to validate the algorithm's specificity against other forms of arrhythmia. [iproc 2017;3(1):e17]

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Self-monitoring and reminder texts to increase physical activity after colorectal cancer (Smart Pace): A pilot trial. (2017)

Journal of Clinical Oncology

Authors: Van Blarigan, E., Van Loon, K., Kenfield, S.A., Chan, J.M., Fukuoka, Y., Laffan, A., Mitchell, E., Chan, H., Rodriguez-Jaquez, D., Meyerhardt, J.A. and Venook, A.P.

Abstract

Background: Colorectal cancer (CRC) survivors can improve their quality-of-life (QOL), and potentially survival, by engaging in physical activity. The aim of this pilot randomized controlled trial (RCT) is to determine the feasibility of a technology-based physical activity intervention for CRC survivors. Methods: 40 CRC survivors will be randomized (1:1) to a 12-week physical activity intervention (Fitbit Flex, daily text messages) or usual care. Eligible individuals must: 1) have stage I-III colon or rectal adenocarcinoma; 2) have completed therapy; 3) be considered cancer-free; 4) be English speaking; 5) have no contraindications to moderate physical activity; 6) engage in < 150 min/week of moderate physical activity; and 7) have Internet and a phone that can receive text messages. Our primary outcomes are adherence (e.g., Fitbit wear time, text response rate) and acceptability assessed via survey. Secondary outcomes include change in physical activity via 7-days of ActiGraph GT3X+ accelerometers and QOL. Results: We have screened 350 individuals with stage I-III CRC at the University of California, San Francisco (UCSF) for eligibility. Of these, 181 (52%) were not eligible [non-English speaking (46%), = 150 min/week of physical activity (22%), contraindications to physical activity (22%), not cancer-free (7%), did not own a mobile phone (2%)]. We invited the remaining 169 eligible CRC survivors to participate by mail, e-mail, phone, or in clinic; 76 (45%) actively declined and 59 (35%) did not respond after up to 3 contact efforts. As of October 2016, 34 CRC survivors have been randomized to intervention (n = 16) or control (n = 18). These individuals are: 55% female; 64% Non-Hispanic White; 73% have a 4-y college degree; and 64% work full-time. The median (IQR) age and BMI are: 56 (50, 65) y and 26.4 (23.2, 32.4) kg/m2, respectively. Conclusions: The results of this pilot study will inform a definitive RCT to determine whether a technology-based physical activity intervention improves QOL and survival after CRC diagnosis. Funding: This research was supported by the NIH (K07CA197077, KL2TR000143), Mt. Zion Health Fund and UCSF Helen Diller Family Comprehensive Cancer Center.

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Short-Term Efficacy of an Innovative Mobile Phone Technology-Based Intervention for Weight Management for Overweight and Obese Adolescents: Pilot Study. (2017)

Interactive Journal of Medical Research

Authors: Chen, J.-L., Guedes, C.M., Cooper, B.A. and Lung, A.E.

Abstract

BACKGROUND In the United States, approximately one-third of adolescents are now overweight or obese, and one in six is obese. This financial cost and the larger nonfinancial costs of obesity make obesity prevention and management for adolescents imperative for the health of the nation. However, primary care visits are typically brief, and primary care providers may lack adequate resources to help overweight or obese adolescents to manage weight issues. To augment the efficacy of primary care visits for adolescent weight management, mobile phone technology can be used as an adjunct treatment that provides additional opportunities for encouraging improvement in lifestyle, attainment, and maintenance of healthy weight. OBJECTIVE The purposes of this study were to (1) measure effects of an innovative mobile phone technology-based intervention for overweight and obese adolescents and to (2) examine the intervention's feasibility for use in primary care clinics. METHODS The mobile phone-based intervention had three components: use of the Fitbit Flex, participation in an online educational program, and receipt of biweekly text messages during the maintenance phase. A randomized controlled study design was utilized. Data regarding anthropometrics (body mass index [BMI] and waist-to-hip ratio), blood pressure, levels of physical and sedentary activity, diet, and self-efficacy regarding physical activity and diet were collected at baseline and at 3 and 6 months after the baseline assessment. RESULTS A total of 40 adolescents participated in the study. At the 6-month follow-up visit, compared to participants in the control group, the mobile phone-based intervention participants had significant improvement in BMI (z=-4.37, P=.001), diastolic blood pressure (z=-3.23, P=.001), physical activity days per week (z=2.58, P=.01), TV and computer time (z=-3.34, P=.001), servings of fruits and vegetables per day (z=2.74, P=.006), servings of soda and sweetened drinks (z=-3.19, P=.001), physical activity self-efficacy (z=2.75, P=.006), and dietary self-efficacy (z=5.05, P=.001). Medium to large effect sizes were found in these outcome variables. CONCLUSIONS The use of mobile technologies may offer a practical, reliable adjunct to weight management for overweight and obese adolescents in busy primary care clinics serving adolescents.

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Smartphone-Enabled Health Coaching Intervention (iMOVE) to Promote Long-Term Maintenance of Physical Activity in Breast Cancer Survivors: Protocol for a Feasibility Pilot Randomized Controlled Trial (2017)

JMIR Research Protocols

Authors: Ritvo, P., Obadia, M., Santa Mina, D., Alibhai, S., Sabiston, C., Oh, P., Campbell, K., McCready, D., Auger, L. and Jones, J.M.

Abstract

Background: Although physical activity has been shown to contribute to long-term disease control and health in breast cancer survivors, a majority of breast cancer survivors do not meet physical activity guidelines. Past research has focused on promoting physical activity components for short-term breast cancer survivor benefits, but insufficient attention has been devoted to long-term outcomes and sustained exercise adherence. We are assessing a health coach intervention (iMOVE) that uses mobile technology to increase and sustain physical activity maintenance in initially inactive breast cancer survivors. Objective: This pilot randomized controlled trial (RCT) is an initial step in evaluating the iMOVE intervention and will inform development of a full-scale pragmatic RCT. Methods: We will enroll 107 physically inactive breast cancer survivors and randomly assign them to intervention or control groups at the University Health Network, a tertiary cancer care center in Toronto, Canada. Participants will be women (age 18 to 74 years) stratified by age (55 years and older/younger than 55 years) and adjuvant hormone therapy (AHT) exposure (AHT vs no AHT) following breast cancer treatment with no metastases or recurrence who report less than 60 minutes of preplanned physical activity per week. Both intervention and control groups receive the 12-week physical activity program with weekly group sessions and an individualized, progressive, home-based exercise program. The intervention group will additionally receive (1) 10 telephone-based health coaching sessions, (2) smartphone with data plan, if needed, (3) supportive health tracking software (Connected Wellness, NexJ Health Inc), and (4) a wearable step-counting device linked to a smartphone program. Results: We will be assessing recruitment rates; acceptability reflected in selective, semistructured interviews; and enrollment, retention, and adherence quantitative intervention markers as pilot outcome measures. The primary clinical outcome will be directly measured peak oxygen consumption. Secondary clinical outcomes include health-related quality of life and anthropometric measures. All outcome measures are administered at baseline, after exercise program (month 3), and 6 months after program (month 9). Conclusions: This pilot RCT will inform full-scale RCT planning. We will assess pilot procedures and interventions and collect preliminary effect estimates. Clinical Trial: ClinicalTrials.gov NCT02620735; https://clinicaltrials.gov/ct2/show/NCT02620735 (Archived by WebCite at https://clinicaltrials.gov/ct2/show/NCT02620735) [JMIR Res Protoc 2017;6(8):e165]

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Sources of Error with Wearable Step Counters (2017)

Medicine & Science in Sports & Exercise

Authors: Park, S., Toth, L.P., Morton, A.L., Pittman, W.L., Sarasaltik, D. and Bassett, D.R.

Abstract

PURPOSE: To investigate sources of error with 11 wearable step counting devices, during common types of physical activities. METHODS: 20 participants performed 15 activities for 2 min each, while wearing 11 step counters on the waist, ankle, or non-dominant wrist. Arm activities included: snacking, brushing hair, folding laundry, sweeping, brushing teeth, and meal preparation. Overground activities included: walking holding onto backpack strap, walking with umbrella, walking with hands in pockets, and pushing stroller. Treadmill activities included: walking at 1 mph, walking at 2 mph, walking at 3 mph, walking at 3 mph holding onto bars, and jogging at 6 mph. Wrist-worn devices included: Garmin Vivofit 2, Fitbit Charge, Polar A360, Withings Pulse Ox, and ActiGraph GT3X. Waist-worn devices included: Yamax Digi-Walker SW-200, Fitbit Zip, Omron HJ-322U, and ActiGraph GT3X (without low-frequency extension). Ankle-worn devices included: two StepWatch 3 devices, one with preprogrammed, default settings and one with modified cadence and sensitivity settings. A researcher hand-counted steps during each activity; this served as the criterion. The step counts reported from each device compared to the hand count using a 1-way (1x12) repeated measured ANOVA. If the overall effect for an activity was significant, the outputs from individual devices and the criterion were analyzed using planned contrasts. Devices with significant contrasts (p = 0.05) and observed power greater than 0.8 were considered to be significantly different than the criterion. RESULTS: During arm activities, the wrist-worn devices overcounted steps while hip-worn devices slightly undercounted steps. The ActiGraph GT3X on the wrist greatly overcounted steps during arm activities, while other devices had smaller errors. During treadmill walking at 1 mph, all wrist and hip-worn devices undercounted steps. The ankle-worn device (StepWatch 3) had the smallest error across all activities, especially when programmed with the modified setting. CONCLUSIONS: Individuals using step counting devices should be aware of sources of error in step counts. Contributing factors to error are the wear location, the algorithms used to count steps, and the activities performed.

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Step Count Filters in Wearable Step Counters (2017)

Medicine & Science in Sports & Exercise

Authors: Toth, L., Park, S., Pittman, W., Sarasaltik, D., Morton, A.L. and Bassett, D.R.

Abstract

Manufacturers of step counting devices apply filters to their step counting algorithms to prevent accumulation of steps when none are taken (i.e. false positives). However because filters prevent steps from being recorded during short, intermittent walking bouts, it is possible that these filters may be a source of error. Since few manufacturers disclose the type of filter they use, we decided to investigate this topic. PURPOSE: To determine whether the devices used in this study have a filter, and to describe the effects of the filter on short, intermittent walking bouts with varied walk and pause durations. METHODS: In Parts A and B, 20 participants performed intermittent walking bouts for 2 min, at a cadence of 100 steps/min. In Part A participants were instructed to walk a certain number of steps (i.e. 4, 6, 8, 10, and 12) followed by a 10-sec pause and repeat this until the trial ended. In Part B participants were instructed to walk four steps followed by various pause intervals (i.e. 8, 6, 4, 2, and 1 sec) and repeat this. A researcher counted steps using a hand-tally device (criterion). “Percent of actual steps taken” was used for statistical analysis. A one-way repeated measures ANOVA was completed for both parts. In the case of significant overall effects (p textless 0.05), the results were further examined using planned contrasts to see which conditions differed from the criterion. RESULTS: In Parts A and B the multivariate results for ActiGraph GT3X (AG) (without low frequency extension) worn at the wrist, StepWatch 3, and Yamax Digi-Walker SW-200 were not significantly different from the criterion, indicating absence of a step count filter. Walking bouts shorter than 4 steps (AG at the hip), 6 steps (Withings), 8 steps (Omron and Garmin Vivofit 2), and 12 steps (Polar A360), resulted in a significant decrease in the number of steps counted, indicating presence of a filter. The minimum pause needed to break up a walking bout was 1 sec (Fitbit Charge, Fitbit Zip, and Withings), and textless 1 sec (Omron HJ-322U). For both the Polar and Garmin, the longer the pause, the less likely they were to record steps. CONCLUSIONS: Devices with step count filters will contribute to error in daily step counts because steps taken during short, intermittent walking bouts (e.g., meal preparation, and housework) are not registered.

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Step It Up: Higher Step Count Is Significantly Correlated with Better Exercise Capacity in Individuals with Cystic Fibrosis (2017)

American Journal of Respiratory and Critical Care Medicine

Authors: Powers, K., Herzog, T., Loosen, H., Berg, K.V., Weir, B., Riekert, K.A. and Mogayzel, P.J.

Abstract

Rationale: The positive health benefits of physical activity (PA) have been extensively studied and commonly accepted. The CDC and the American College of Sports Medicine have recommended regular PA to reduce risk factors for chronic disease including physical functioning, aerobic fitness and quality of life. PA in individuals with cystic fibrosis (CF) improves exercise capacity, slows decline in lung function, increases mucus clearance and improves health-related quality of life. Hypothesis: Increased daily PA as measured by step count in participants with CF will be associated with greater exercise capacity as measured by the Modified Shuttle Walk Test (MSWT). Methods: We completed the MSWT and spirometry in 22 participants at enrollment into the Do More, B’More, Live Fit trial. This randomized control trial is a 6-month fitness training program designed to optimize exercise habits of 12-21 year-olds. Participants received a FitBit Flex (Fitbit© Boston, MA). Daily step count was assessed over 7 consecutive days within the enrollment period prior to any intervention. The step count variables assessed included mean, median and highest daily step count. Lung function was measured via spirometry and was compared to both FitBit step count and the number of MSWT shuttles completed using multiple linear regression analysis and Spearman Rho correlation. Results: MWST shuttles were significantly correlated with better lung function as measured by FEV1pp, Rho=0.58 (p=0.005). FitBit step count (mean and maximum) was significantly correlated to performance on MSWT, Rho=0.53 (p=0.01) and Rho=0.58 (p=0.005) respectively. The association between mean FitBit step count with MSWT performance remained significant after controlling for FEV1pp, [overall model R2=0.67; step count B=0.006 (p=0.001)]. Similar results were found using the median step count and highest daily value step count values. Conclusions: Measuring FitBit daily step count provides a novel approach to assessing effects of PA on exercise capacity in individuals with CF. More daily steps significantly correlated with better MSWT performance. Based on these data, it is suggested that daily fitness as reflected in FitBit step count may be a significant predictor for exercise capacity even after accounting for disease severity as measured by lung function. Within the context of the Do More, B’More, Live Fit trial, the value of step counts as a real-world measure of changes in exercise capacity may be further elucidated.

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Stress moderation impacting lupus with exercise (S.M.I.L.E.): influence of daily moderate exercise and stress modification on autoimmune-mediated inflammation in mice and humans with lupus (2017)

Annals of the Rheumatic Diseases

Authors: Young, N., Thomas, E., Snoad, B., Sharma, J., Mobeen, M., Yedimenko, J., Steigelman, H., Meara, A., Valiente, G., Ardoin, S., Powell, N., Sheridan, J. and Jarjour, W.

Abstract

Background Despite numerous studies indicating the positive effects of exercise and psychological stress reduction in patients with autoimmune disease, these therapeutic modalities are currently underemphasized due to the absence of comprehensive immunological characterization and regimen standardization. Objectives In order to examine the influence on the immune system at the cellular and tissue level, disease pathology was analyzed in the NZM2410 mouse model of lupus nephritis. To translate these results and begin to characterize a consensus treatment regimen, a pilot cohort of systemic lupus erythematosus (SLE) patients with active disease was enrolled into a daily Tai Chi program, which emphasized moderate exercise levels with meditative breathing to provide daily physical activity and stress reduction. Methods Mice were exercised daily by treadmill walking at moderate intensity. Social disruption stress was induced in mice by disturbing the social order within an established hierarchy. All mice were removed from the study when experimental removal criteria was reached [blood urea nitrogen (BUN)textgreater50 mg/dL; weight losstextgreater20%]. Kidney tissue and serum were collected from mice at experimental endpoint. SLE patients completed daily Tai Chi exercises and data was collected at baseline and throughout the study via questionnaires to access physical activity and stress levels, activity trackers (Fitbit), and serum sample analysis. Results Histopathological analysis of NZM2410 mice demonstrated that psychosocial stress induction significantly exacerbated and daily moderate exercise significantly reduced lupus nephritis disease pathology, as measured by BUN levels, complement component 3 and IgG complex deposition in glomeruli, pathological grading of H&E-stained kidney sections, and renal macrophage infiltration. Furthermore, stressors induced levels of IL-6, TNF-a, and IL-1ß, while exercise suppressed IL-6, TNF-a, IL-10, and CXCL1 in mice. Compared to baseline data, questionnaires confirmed a significant reduction in perceived social stress and an increase in combined metabolic equivalent of task (MET) and overall physical activity in SLE patients. Moreover, fitness activity tracker data showed a significant increase in steps, distance, and activity calories with no changes in body mass index or vigorous activity levels. Interestingly, this correlated with an increased average time in bed each night. Analysis of pro-inflammatory serum cytokine expression revealed suppression in the relative fold change of IL-6 by 23%, IL-8 by 30%, TNF-a by 11%, and IFN-? by 21% with Tai Chi. Conclusions These data suggest that moderate exercise and stress management can have potent immunoregulatory effects on the chronic, systemic inflammation associated with SLE and identify daily Tai Chi exercise as a viable adjunct therapy to compliment current pharmacological interventions.

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Tea, talk and technology: patient and public involvement to improve connected health ‘wearables' research in dementia (2017)

Research Involvement and Engagement

Authors: Hassan, L., Swarbrick, C., Sanders, C., Parker, A., Machin, M., Tully, M.P. and Ainsworth, J.

Abstract

Background Increasingly, researchers are recognising the potential for connected health devices, including smartphones and smartwatches, to generate high resolution data about patterns of daily activity and health outcomes. One aim of the Dementias Platform UK (DPUK) project is to provide researchers with a secure means to collect, collate and link data generated by such devices, thereby accelerating this type of research in the field of dementia. We aimed to involve members of the public in discussions about the acceptability and feasibility of different devices and research designs to inform the development of a device pool, software platform and written guidance to support future studies. Methods Over 30 people attended a series of interactive workshops, drop-in sessions and meetings in Greater Manchester. This included people living with dementia and cognitive impairments, carers and people without memory problems. Discussions were tailored to suit different audiences and focused on the feasibility and acceptability of a range of different wearable devices and research designs. We also invited volunteers to borrow a device to test at home, enabling further insights from hands-on interactions with devices. Results Discussions revealed that people were supportive of connected health dementia research in principle, provided they gave informed consent and that devices were discreet, comfortable and easy to use. Moreover, they recommended technical support and regular feedback on study progress to encourage ongoing participation. Conclusion By using a range of discussion-based and practical activities, we found it was feasible to involve people affected by dementia and use their insights to shape the development of a software platform and device pool to support future connected health dementia research. We recommend that researchers planning such studies in future pay adequate attention to designing suitable participant information, technical support and mechanisms of providing study progress updates to support sustained engagement from participants.

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The Validity of Fitbit Charge in Free Living Conditions (2017)

Medicine & Science in Sports & Exercise

Authors: Bai, Y., Ellingson, L. and Welk, G.

Abstract

PURPOSE: Research is accumulating regarding the accuracy of wrist-worn consumer activity monitors in controlled lab settings. However, there is a lack of evidence of validity under free living conditions. The study investigated the accuracy of Fitbit Charge (FBC) for estimating minutes of moderate and vigorous physical activity (MVPA) compared to research grade accelerometers. A secondary purpose was to evaluate the accuracy of steps/day. METHODS: Ninety-four healthy men and women (mean age 41 ± 9 years) wore a FBC as part of a 12-week intervention. The participants were also asked to wear research grade accelerometers concurrently as the criterion physical activity measure during the last week of intervention. A minimal of 10 hours/day wear-time was applied to both methods. Estimated daily MVPA and steps taken from the FBC were compared against the criterion using indicators of Pearson correlation, mean absolute percent errors, mean percent errors, and equivalence testing. The activity classification agreement of MVPA at the minute level was evaluated with Kappa, sensitivity and specificity. RESULTS: Complete data were collected on 61 individuals with an average of 5.5 days of wear-time. The average daily MVPA measured by accelerometer was 76.3 minutes compared to a higher value, 118.7 minutes, estimated by the FBC. The correlation between the two methods was 0.8 (ptextless0.0001). The mean absolute percent errors and mean percent errors were 68.2% and -64.2% indicating a consistent overestimating MVPA by the FBC. The average daily steps were 8,897 and 7,716 measured by FBC and accelerometer, respectively, with a correlation of 0.76 (ptextless0.0001). The mean absolute percent errors and mean percent errors of steps estimated by FBC were 30.0% and -20.1%. Neither of the MVPA and steps measured by FBC fell into the ±10% equivalence zone set up by the accelerometer. The Kappa statistics of the classification agreement between the two methods was 0.32 with a low the sensitivity of 30.1% but a high specificity of 96.7%. CONCLUSIONS: This FBC estimated substantially higher minutes of MVPA in free living conditions among healthy adults and significantly higher steps compared to research grade accelerometer. The researchers who use FBC to track physical activity need to interpret their results with caution.

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Trial to Incentivise Adherence for Diabetes (TRIAD): study protocol for a randomised controlled trial (2017)

Trials

Authors: Bilger, M., Shah, M., Tan, N.C., Howard, K.L., Xu, H.Y., Lamoureux, E.L. and Finkelstein, E.A.

Abstract

Many people with diabetes have suboptimal glycaemic control due to not being adherent to their treatment regimen. Behavioural economic theory suggests that the lack of adherence results from the disconnect between the timing of when costs and benefits accrue. One strategy to address this discontinuity is to offer patients a near-term benefit, such as a financial reward. Whereas there is evidence that rewards can improve treatment adherence and sometimes health outcomes, further research is needed to determine whether rewards are more effective when targeting processes or intermediary health outcomes. In the Trial to Incentivise Adherence for Diabetes (TRIAD) we test whether adding financial incentives to usual care can improve HbA1c levels among people with diabetes and whether the financial incentives work better when targeting processes (adherence to blood glucose testing, medication, and daily physical activity) or the primary intermediary health outcome of self-monitored blood glucose within an acceptable range. TRIAD is a randomised, controlled, open-label, single-centre superiority trial with three parallel arms. A total of 240 patients with suboptimally controlled diabetes (HbA1c ≥ 8%) from a polyclinic in Singapore are block-randomised (blocking factor: current vs. new glucometer users) into three arms, namely (1) usual care (UC) only, (2) UC with process incentive and (3) UC with outcome incentive, in a 2:3:3 ratio. Masking the arm allocation will be precluded by the behavioural nature of the intervention but blocking size will not be disclosed to protect concealment. The primary outcome (change in HbA1c level at month 6) will be measured by a laboratory that is independent from the study team. Secondary outcomes (at month 6) include the number of blood glucose testing days, glucose readings within the normal range (between 4 to 7 mmol/L), medication-adherent days, physically active days, and average incentives earned and time spent administrating the incentives. This study will provide evidence on whether financial incentives can cost-effectively improve glycaemic control. It will also provide evidence on the benefit incidence of interventions involving financial incentives. By comparing process to outcome incentives, this study will inform the design of future incentive strategies in chronic disease management and beyond.

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Types of Social Support and Weight Change among Overweight Adults (2017)

Medicine & Science in Sports & Exercise

Authors: Monroe, C.M., Larsen, C. and West, D.

Abstract

Engaging social support has been found to be an effective strategy to promote weight loss. Yet, little is known about the specific types of social support that may be the most influential. PURPOSE: The aim of this study was to examine the association between weight change and the types of social support adults participating in a behavioral weight loss intervention identified as the most helpful for their weight loss efforts. METHODS: Overweight adults (N=36) were randomized to one of two, 16-week behavioral weight loss interventions. Both treatments consisted of weekly, in-person group counseling sessions, Fitbit Zips for monitoring physical activity, and scales for monitoring body weight. One group also received two extra Fitbit Zips and scales to share with up to two persons in their social circle. There were no significant differences between conditions, so analyses collapsed groups and examined those who started the intervention (N=35). Participants completed an online survey at the end of each intervention week, which asked them to select the most helpful type of social support they received (informational; tangible; network; emotional; esteem). The support type identified the most frequently as the most helpful type over time was determined for each participant and used in Fisher’s exact tests to measure the frequencies with which each type of support was reported between those who lost > 5% of their initial body weight and those who did not. RESULTS: Participants were obese at baseline (M BMI = 36.1 + 7.3 kg/m2), and 43% lost > 5% of their initial weight by 16 weeks. Only emotional, esteem, and tangible support emerged as the most frequently reported most helpful types of support among all participants across the intervention period. A greater proportion of those who lost > 5% of their baseline weight identified esteem support as the most helpful type of support versus those who lost < 5% of their initial weight (47% vs 10%, p = .02). No significant differences between weight change groups were found for other support types (ps > .05). CONCLUSION: These findings suggest that esteem support may be especially influential for fostering weight loss. However, future studies should employ designs that allow for the direct comparison and more robust evaluation of the effectiveness of different types of support on weight loss in adults.

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Use It And Lose It: Fitbit Use, Daily Steps, And Weight Change Among Overweight Adults (2017)

Medicine & Science in Sports & Exercise

Authors: Larsen, C.A., Monroe, C.M. and West, D.S.

Abstract

Despite the increasing proliferation of advanced wearable physical activity tracking devices (e.g., Fitbit Zip), their value as tools for physical activity promotion and weight loss remains unclear. PURPOSE: As part of a pilot intervention trial that examined the efficacy of a novel social support approach for enhancing weight loss, participants were provided with a Fitbit Zip to monitor their physical activity. The current study examined the relationships between Fitbit use and change in weight and daily steps over 4 months. METHODS: Overweight adults (N=36) were randomized to either a standard or social support-enhanced, 16-week behavioral weight loss intervention. In addition to a Fitbit Zip, both groups received weekly, in-person group counseling sessions and digital body weight scales. Participants in the social-support enhanced group received two extra Fitbits and scales to share with up to two persons in their social circle. There were no significant differences between conditions, so analyses collapsed groups and examined the full sample. Paired t-tests were used to evaluate changes in weight and daily steps from baseline to post-treatment. Spearman rank correlation coefficients were calculated to test the associations between the total number of days the Fitbit was used (out of 112 days) and changes in daily steps and weight. Fitbit use was objectively established by weekly monitoring of synced data from the Fitbit website. RESULTS: At baseline, participants were obese (M BMI= 36.1 + 7.3 kg/m2) and low active (M=5546 + 2390 steps/d). Weight losses averaged -3.5+4.3 kg (p<.0001) and daily steps increased an average of 1101+2395 (p=.009) over baseline. Participants used the Fitbit an average of 5.9+2.5 days/wk. A significant correlation between total number of days the Fitbit was used and weight loss such that there was greater use of Fitbit was associated with greater weight loss (rs = -.60, p<.0001). A significant, positive correlation was found between the change in daily steps and the number of days the Fitbit was used (rs=.43, p=.008). CONCLUSION: These preliminary findings suggest that advanced wearable physical activity trackers hold promise as tools for assisting with physical activity promotion and weight loss in adults within the context of a multi-component behavioral weight loss program.

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Use of a Fitness Tracking Device to Monitor Physical Activity and Sleep Patterns during Hospitalization for Hematopoietic Stem Cell Transplant. Results of a Prospective Observational Study (2017)

Blood

Authors: El Jurdi, N.H., Cotton, M.J., Pinto, R., Galloway, E., Kolke, S., Cooper, B.W., Tomlinson, B.K., Metheny, L., Malek, E., Nock, N., Kolk, M., Lee, R., De Lima, M. and Caimi, P.

Abstract

Background The prolonged hospitalization often associated with hematopoietic stem cell transplant (HSCT) increases risk of immobility and inactivity-associated complications. There is limited information on the daily activity and sleep patterns of patients undergoing HSCT and their effect on transplant related outcomes, functional recovery and length of hospital stay. We conducted a prospective observational study to determine the feasibility of using a fitness tracking device to monitor the physical activity and sleep patterns of patients undergoing HSCT. Methods Patients undergoing autologous (autoHSCT) or allogeneic (alloHSCT) were consented to wear a Fitbit HR ® activity tracking device. The device was placed on the patients' wrist within 48 hours of admission and was removed on discharge. Patients were followed for 100 days post-HCT. Daily activity parameters measured by the Fitbit HR® device included steps, distance, time spent in physical activity, active calories burned, minimum and maximum heart rate. Sleep parameters included: total sleep duration and number of times patients were awake or restless. All patients were evaluated by a Physical Therapist upon admission. Comparisons between groups were done using the Mann-Whitney test for continuous variables and Fisher's exact test for qualitative variables; correlations were evaluated with Pearson's and Spearman's correlation tests; modeling was done with linear regression for quantitative variable pairs and one-way ANOVA for qualitative and quantitative variable pairs. Results 31 patients were consented, 4 were removed from the study (2 patients withdrew consent; 2 patients were not compliant). The baseline characteristics of 27 subjects with available activity and sleep data are summarized in table 1. There were no statistically significant differences in baseline characteristics between subjects receiving autoHSCT and alloHSCT. All patients undergoing alloHSCT received reduced intensity conditioning regimens. Transplant outcomes and results from activity and sleep pattern measurements are presented in table 2. As expected, longer length of hospitalization, longer time to neutrophil engraftment, infectious complications and readmissions were more common in subjects undergoing alloHSCT. While the number of steps at admission was comparable between both groups, alloHCT subjects had a more intense decrease in their physical activity, manifested by a lower number of steps at nadir (249 vs 697, p=0.03) as well as by a larger percentage decrease in physical activity from admission (89% vs 68%, p=0.02) and a decrease compared to their peak performance during admission (92% vs 82%, p =0.02). Among baseline characteristics, age and presence of cardiovascular risk factors correlated with number of steps at admission (Pearson R =-0.43, p=0.03 and biserial correlation R=0.39, p=0.04, respectively); BMI showed a positive correlation with the decrease in activity from peak to nadir (Pearson R=0.54, p=0.005) and ECOG PS of 1 (vs 0) correlated with the absolute decrease in steps from admission to discharge (Spearman R -0.47, p=0.02). ANOVA showed that infectious complications were associated with changes in activity from peak to nadir (R2=0.18, p=0.03), while linear regression identified an association between time from transplant to discharge and both the decrease in activity from admission and peak to nadir (R2=0.15, p=0.05 and R2=0.16,p=0.04). Conclusions This study demonstrates the feasibility of monitoring activity and sleep patterns in HSCT patients with a commercially available fitness tracking device. Approximately 90% of patients remained compliant with the use of the device. The fitness data obtained showed correlation with known transplant outcomes, and the patterns observed highlighted differences within the patient population. Use of a fitness tracking device in patients undergoing HCT represents an objective method for measuring physical activity during hospitalization, and potentially identifies patients in which interventions such as intensified physical therapy could improve outcomes. Studies comparing the quality of data of Fitbit HR® devices with other instruments such as Actigraph® are underway at our institution. Future studies evaluating the effect physical activity devices have on patient's activity during hospitalization and in the post-transplant recovery period are planned.

Use of a mobile social networking intervention for weight management: a mixed-methods study protocol (2017)

BMJ Open

Authors: Laranjo, L., Lau, A.Y.S., Martin, P., Tong, H.L. and Coiera, E.

Abstract

Introduction Obesity and physical inactivity are major societal challenges and significant contributors to the global burden of disease and healthcare costs. Information and communication technologies are increasingly being used in interventions to promote behaviour change in diet and physical activity. In particular, social networking platforms seem promising for the delivery of weight control interventions. We intend to pilot test an intervention involving the use of a social networking mobile application and tracking devices (Fitbit Flex 2 and Fitbit Aria scale) to promote the social comparison of weight and physical activity, in order to evaluate whether mechanisms of social influence lead to changes in those outcomes over the course of the study. Methods and analysis Mixed-methods study involving semi-structured interviews and a pre–post quasi-experimental pilot with one arm, where healthy participants in different body mass index (BMI) categories, aged between 19 and 35 years old, will be subjected to a social networking intervention over a 6-month period. The primary outcome is the average difference in weight before and after the intervention. Secondary outcomes include BMI, number of steps per day, engagement with the intervention, social support and system usability. Semi-structured interviews will assess participants' expectations and perceptions regarding the intervention. Ethics and dissemination Ethics approval was granted by Macquarie University's Human Research Ethics Committee for Medical Sciences on 3 November 2016 (ethics reference number 5201600716). The social network will be moderated by a researcher with clinical expertise, who will monitor and respond to concerns raised by participants. Monitoring will involve daily observation of measures collected by the fitness tracker and the wireless scale, as well as continuous supervision of forum interactions and posts. Additionally, a protocol is in place to monitor for participant misbehaviour and direct participants-in-need to appropriate sources of help.

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Using Wrist-Worn Actigraphic Devices to Measure Sleep in People with Huntington's Disease (2017)

Sleep

Authors: Dao, P., Maskevich, S., Jumabhoy, R., Drummond, S. and Stout, J.

Abstract

Introduction: Sleep disturbances are an early symptom of Huntington's disease (HD), and may be linked to the cognitive, motor and psychiatric symptoms of HD. Long-term collection of HD ambulatory sleep data can show the impact of sleep disturbances as HD symptoms progress. Actigraphy provides an objective measure of sleep well suited to long-term ambulatory data collection, but is cost prohibitive for large-scale studies. Commercial actigraphy devices may be a good alternative. This study aimed to validate research and commercial actigrapy in people with HD. Methods: Seven people with the gene for Huntington's disease (Age=54.1?±?6.4, 6F) completed an overnight sleep study using polysomnography, research-grade (Actiwatch Spectrum Pro), and consumer-grade (Fitbit One) actigraphy to measure sleep. For each actigraph, sensitivity and specificity compared to polysomnography were calculated. Intraclass correlations (ICCs) and Bland-Altman analyses (BAA) were used to compare the actigraphs to polysomnography on total sleep time (TST), sleep efficiency (SE), sleep latency (SL), and wake after sleep onset (WASO). Results: The sensitivity of the research-grade and consumer-grade actigraphs were 97.13% and 98.90% respectively, and specificities were 31.32% and 27.05% respectively. The only significant ICC was the correspondence between the consumer-grade actigraph and polysomnography for TST (r=0.52, p=.03). Using BAA, both actigraphs overestimated TST (Research-grade - Avg.dif=74.3?±?54.1min; Consumer-grade - Avg.dif=94.3?±?50.2min) and SE (Research-grade - Avg.dif=14.8?±?11.0%; Consumer-grade - Avg.dif=17.5?±?9.8%), and showed good agreement for SL (Research-grade - Avg.dif=-27.9?±?28.0min; Consumer-grade - Avg.dif=-22.0?±?24.7?min). The research-grade actigraph showed good agreement with polysomnography on WASO (Avg.dif=-20.0?±?32.2min), whilst the consumer-grade actigraph underestimated WASO (Avg.dif=-39.0?±?29.1min). Conclusion: In people with HD, neither actigraph showed sufficient agreement with polysomnography to be a suitable replacement for ambulatory sleep measurement, particularly considering the very low specificity values. Our research-grade actigraphy performed notably worse than what is typically seen in patient populations. The development of a HD specific actigraphy algorithm would greatly improve the agreement between actigraphy and polysomnography.

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Validation of Three Wearable Fitness Trackers for Measuring Physical Activity in College Students (2017)

Medicine & Science in Sports & Exercise

Authors: Witmer, C., Zhang, P., Godin, S. and Che, D.

Abstract

Many wearable fitness trackers have a function measuring physical activity such as energy expenditure but the accuracy of the measures is unclear. PURPOSE: The aim of the study was to validate the energy expenditure estimation of three fitness trackers: LT, FB, and AW for treadmill walking and running. METHODS: The participants of the study were 30 college students (17 males and 13 females) from a public university in Pennsylvania. All participants completed six trials of 10-minute walking and running activities on a treadmill at speeds of 54, 80, 107, 134, 161, & 188 m•min-. Participants were wearing all the fitness trackers and connected to indirect calorimetry during the exercise protocol. All devices provided caloric expenditure while the indirect calorimetry was used as a criterion measure. Resting Metabolic Rate was collected along with a familiarization trial prior to the execution of the exercise protocol. Two-way ANOVA with repeated measures and Pearson Correlation were used to compare the caloric expenditure estimates between the criterion and three fitness trackers. RESULTS: There were no significant differences in energy expenditure estimates between the criterion and AW (mean difference 4.6 kcal, p textgreater 0.05), nor criterion and LT (mean difference 0.8 kcal, p textgreater 0.05). However there was a significant difference between the criterion measure and FB (mean difference 18.2 kcal, p = 0.001). Pearson correlation coefficients (r): the criterion of indirect calorimetry-derived activity energy expenditure yielded the strongest positive correlations with activity energy expenditure estimated from the AW at all speed levels (range from .55 to .85, all ps textless0.01). FB was positively correlated to the criterion measure at five speed levels (range from .46 to .67, ps textless0.05). No positive correlation was found between the criterion and LT measures (range from -.40 to .26). CONCLUSION: AW and FB demonstrated a moderate to high level of validity on measuring physical activity while LT had a low level of validity.

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Validity of Different Activity Monitors to Count Steps in an Inpatient Rehabilitation Setting. (2017)

Physical Therapy

Authors: Treacy, D., Hassett, L., Schurr, K., Chagpar, S., Paul, S.S. and Sherrington, C.

Abstract

Background Commonly used activity monitors have been shown to be accurate in counting steps in active people, however, further validation is needed in slower walking populations. Objectives To determine the validity of activity monitors for measuring step counts in rehabilitation inpatients compared to visually-observed step counts. To explore the influence of gait parameters, activity monitor position and use of walkers on activity monitor accuracy. Methods 166 inpatients admitted to a rehabilitation unit with an average walking speed of 0.4 m/s (SD 0.2) wore 16 activity monitors (seven different devices in different positions) simultaneously during 6-minute and 6-metre walks. The number of steps taken during the tests was also counted by a physiotherapist. Gait parameters were assessed using the GAITRite system. To analyse the influence of different gait parameters, the percentage accuracy for each monitor was graphed against various gait parameters for each activity monitor. Results The StepWatch , Fitbit One worn on the ankle and the ActivPAL showed excellent agreement with observed step count (ICC 2,1 0.98; 0.92; 0.78 respectively). Other devices ( Fitbit Charge , Fitbit One worn on hip, G-Sensor , Garmin Vivofit , Actigraph ) showed poor agreement with the observed step count (ICC 2,1 0.12-0.40). Percentage agreement with observed step count was highest for the StepWatch (mean 98%). The StepWatch and the Fitbit One worn on the ankle maintained accuracy in individuals who walked more slowly and with shorter strides but other devices were less accurate in these individuals. Limitations There were small numbers of participants for some gait parameters. Conclusions The StepWatch showed the highest accuracy and closest agreement with observed step count. This device can be confidently used by researchers for accurate measurement of step counts in inpatient rehabilitation in individuals who walk slowly. If immediate feedback is desired, the Fitbit One when worn on the ankle would be the best choice for this population.

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Validity, reliability and feasibility of commercially available activity trackers in physical therapy for people with a chronic disease: a study protocol of a mixed methods research (2017)

Pilot and Feasibility Studies

Authors: Beekman, E., Braun, S.M., Ummels, D., van Vijven, K., Moser, A. and Beurskens, A.J.

Abstract

For older people and people with a chronic disease, physical activity provides health benefits. Patients and healthcare professionals can use commercially available activity trackers to objectively monitor (alterations in) activity levels and patterns and to support physical activity. However, insight in the validity, reliability, and feasibility of these trackers in people with a chronic disease is needed. In this article, a study protocol is described in which the validity, reliability (part A), and feasibility from a patient and therapist's point of view (part B) of commercially available activity trackers in daily life and health care is investigated. In part A, a quantitative cross-sectional study, an activity protocol that simulates everyday life activities will be used to determine the validity and reliability of nine commercially available activity trackers. Video recordings will act as the gold standard. In part B, a qualitative participatory action research study will be performed to gain insight in the use of activity trackers in peoples' daily life and therapy settings. Objective feasibility of the activity trackers will be measured with questionnaires, and subjective feasibility (experiences) will be explored in a community of practice. Physical therapists (n = 8) will regularly meet during 6 months to learn from each other regarding the actual use of activity trackers in therapy. Therapists and patients (n = 48) will decide together which tracker will be used in therapy and for which purpose (e.g., monitoring, goal setting). Data from the therapist' and patients' experiences will be collected by interviews (individual and focus groups) and analyzed by a directed content analysis. At the time of submission, selection of activity trackers, development of the activity protocol, and the ethical approval process are finished. Data collection and data processing are ongoing. The relevance of the study as well as the advantages and disadvantages of several aspects of the chosen design are discussed. The results acquired from both study parts can be used to create decision aids that may assist therapists and people with a chronic disease in choosing a suitable activity tracker, and to facilitate use of these activity trackers in health care settings. Ethical approval has been obtained from two medical-ethical committees (nr. 15-N-109, 15-N-48 and MEC-15-07).

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Varying Exercise Intensities: The Accuracy of Three Self-Monitoring Heart Rate and Physical Activity Wearable Devices (2017)

Medicine & Science in Sports & Exercise

Authors: Dooley, E.E., Golaszewski, N.M. and Bartholomew, J.B.

Abstract

Physical activity tracking wearables have emerged as a popular method for consumers to assess their daily activity, calories expended and heart rate. However, less is known if these health measures are valid at various levels of exercise intensity. PURPOSE: To examine heart rate (HR) and energy expenditure (EE) validity of three popular wrist-worn activity monitors at different exercise intensities. METHODS: 62 participants (36 females, 46.8% non-white) wore the Apple Watch (AW), Fitbit Charge HR (FCHR) and Garmin Forerunner 225 (GF). Validity was assessed by 2 criterion devices: HR chest strap and a metabolic cart. Participants completed a 10-min seated baseline; separate 4-min stages of light, moderate and vigorous-intensity treadmill exercises; and a 10-min seated recovery. Data from devices were compared to each criterion via two-way RM-ANOVA and Bland-Altman analysis. Differences were expressed in mean absolute percentage error values (MAPE). RESULTS: AW - HR MAPE between 1.14-6.70%. HR not significantly different at the start (p = .13), baseline (p = .76) or vigorous intensity (p = .84). Lower HR readings during light (p textless .05), moderate (p < .01) and recovery (p textless .01). EE MAPE between 14.07-210.84%. Measured higher EE at all stages (p textless .01). FCHR - HR MAPE between 2.38-16.99%. HR not significantly different at start (p = .43) or moderate intensity (p = .34). Lower HR readings during baseline, vigorous and recovery (p textless .001) and higher HR in light (p textless .001). EE MAPE between 16.85-84.98%. Measured higher EE at baseline (p textless .05), light (p textless .001) and moderate (p < .001). GF - HR MAPE between 7.87-24.38%. HR not significantly different at vigorous intensity (p = .35). Measured higher HR readings start, baseline, light, moderate (p textless .001) and recovery (p < .05). EE MAPE between 30.77-155.05%. Measured higher EE at all stages (p < .001). CONCLUSION: This study provides one of the first validation assessments for the Fitbit Charge HR, Apple Watch and Garmin Forerunner 225. An advantage and novel approach of the study is the examination of HR and EE at specific PA intensities. Establishing validity of wearables is of particular interest as these devices are being used in weight loss interventions and could impact findings. Future research should investigate why differences between exercise intensities and the devices exist.

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Virtual weight loss program for African-American breast cancer survivors: Preliminary results. (2017)

Journal of Clinical Oncology

Authors: Ferrante, J.M., Doose, M., Bator, A., Devine, K., Ohman Strickland, P., Angelino, A., Lee, J., Koransky, A., Hwang, K. and Bandera, E.

Abstract

Background: Obesity is associated with higher breast cancer recurrence and death, and poorer health and quality of life. African-American (AA) women have the highest prevalence of obesity, obesity-related comorbidities, and breast cancer mortality compared with other racial/ethnic groups. Weight loss after breast cancer diagnosis may lower rates of recurrence and improve fitness, fatigue, and quality of life. Methods: This 6-month randomized controlled trial pilot-tests the use of a Fitbit activity tracker (Fitbit only group) versus Fitbit plus SparkPeople, a free web-based weight loss program (combined group) among 70 AA breast cancer survivors. Paired t-tests assess changes from baseline to 6-months among each participant in primary (weight, body mass index [BMI], percent body fat) and secondary (24-hour caloric intake, daily number of steps, quality of life, self-monitoring strategies, self-efficacy) outcomes. Two-group t-tests assess differences in outcomes between the two groups. Results: Currently, 36 of 46 (78.3%) eligible participants have enrolled and completed baseline assessments. Mean age of participants is 61.7 years (SD 8.7) and mean BMI is 36.9 (SD 7.0). Analyses of the first 25 participants who completed 3-month assessments (Fitbit only N = 12; combined group N = 13) show significant weight loss in both groups; Fitbit only: mean weight change -6.73 pounds, SD 4.61, p textless 0.001; mean BMI change -0.96 kg/m2, SD 0.84, p = 0.002; combined group: mean weight change -5.95 pounds, SD 5.84, p = 0.003; mean BMI change -1.03 kg/m2, SD 0.77, p textless 0.001. All participants significantly increased tracking of diet (Fitbit only p = 0.016; combined group p textless 0.001) and physical activity (Fitbit only p textless 0.001; combined group p = 0.001). Though not significant, combined group participants showed greater increases in self-efficacy for eating healthy and reducing fat and calories, and increases in daily steps (+1308 vs. +285 for Fitbit only group). Preliminary analyses show no statistically significant difference in changes in outcomes from baseline to 3 months between the two groups. Conclusions: Both programs show potential as convenient and efficient weight loss methods for African-American breast cancer survivors. Clinical trial information: NCT02699983.

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Wellness, sleep and exercise in emergency medicine residents: an observational study (2017)

Canadian Journal of Emergency Medicine

Authors: Poonja, Z., O'Brien, P., Cross, E., Desrochers, C., Jaggi, P., Dance, E., Krentz, J. and Thoma, B.

Abstract

Introduction: Burnout is well documented in residents and emergency physicians. Wellness initiatives are becoming increasingly prevalent, but there is a lack of data supporting their efficacy. In some populations, a relationship between sleep, exercise and wellness has been documented, but this relationship has not been established in emergency medicine (EM) residents or physicians. We aim to determine whether exercise and sleep quality and quantity as measured by a Fitbit are associated with greater perceived wellness in EM residents. Methods: Fifteen EM residents from two training sites wore a Fitbit during a 4-week EM rotation. The Fitbit recorded data on sleep quantity (minutes sleeping)/quality (sleep disruptions) and exercise quantity (daily step count)/quality (daily active minutes performing activity of 3-6 and >6 metabolic equivalents). Participants completed an end-of-rotation Perceived Wellness Survey (PWS) which provided information on six domains of personal wellness (psychological, emotional, social, physical, spiritual and intellectual). Associations between PWS scores and the Fitbit markers were evaluated using a Mann-Whitney-U statistical analysis. Results: Preliminary results indicate that residents who scored =50th percentile for sleep quantity had significantly higher PWS scores than those who scored =50th percentile (median PWS 17.0 vs 13.0 respectively, p=0.04). There was no significant correlation between PWS scores, sleep interruptions, daily step count and average daily active minutes. Postgraduate Year PGY1 and PGY2-5 report median PWS scores of 13.9 and 17.2 respectively. Conclusion: To our knowledge, this is the first study to objectively measure the quality and quantity of sleep as well as exercise habits of EM residents using a Fitbit device. Our data indicates a significant relationship between better sleep quantity and higher wellness scores in this population. We aim to enroll 30 residents in order to obtain a more robust data set. A larger sample size will increase statistical power and allow us to more extensively evaluate the use of exercise and sleep monitoring devices in the efficacy assessment of wellness initiatives.

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What Matters in Weight Loss? An In-Depth Analysis of Self-Monitoring. (2017)

Journal of Medical Internet Research

Authors: Painter, S.L., Ahmed, R., Hill, J.O., Kushner, R.F., Lindquist, R., Brunning, S. and Margulies, A.

Abstract

BACKGROUND Using technology to self-monitor body weight, dietary intake, and physical activity is a common practice used by consumers and health companies to increase awareness of current and desired behaviors in weight loss. Understanding how to best use the information gathered by these relatively new methods needs to be further explored. OBJECTIVE The purpose of this study was to analyze the contribution of self-monitoring to weight loss in participants in a 6-month commercial weight-loss intervention administered by Retrofit and to specifically identify the significant contributors to weight loss that are associated with behavior and outcomes. METHODS A retrospective analysis was performed using 2113 participants enrolled from 2011 to 2015 in a Retrofit weight-loss program. Participants were males and females aged 18 years or older with a starting body mass index of =25 kg/m2, who also provided a weight measurement at the sixth month of the program. Multiple regression analysis was performed using all measures of self-monitoring behaviors involving weight measurements, dietary intake, and physical activity to predict weight loss at 6 months. Each significant predictor was analyzed in depth to reveal the impact on outcome. RESULTS Participants in the Retrofit Program lost a mean -5.58% (SE 0.12) of their baseline weight with 51.87% (1096/2113) of participants losing at least 5% of their baseline weight. Multiple regression model (R(2)=.197, P<0.001) identified the following measures as significant predictors of weight loss at 6 months: number of weigh-ins per week (P<.001), number of steps per day (P=.02), highly active minutes per week (P,.001), number of food log days per week (P<.001), and the percentage of weeks with five or more food logs (P<.001). Weighing in at least three times per week, having a minimum of 60 highly active minutes per week, food logging at least three days per week, and having 64% (16.6/26) or more weeks with at least five food logs were associated with clinically significant weight loss for both male and female participants. CONCLUSIONS The self-monitoring behaviors of self-weigh-in, daily steps, high-intensity activity, and persistent food logging were significant predictors of weight loss during a 6-month intervention.

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When a Step Is Not a Step! Specificity Analysis of Five Physical Activity Monitors (2017)

PLOS ONE

Authors: O’Connell, S., ÓLaighin, G. and Quinlan, L.R.

Abstract

Introduction: Physical activity is an essential aspect of a healthy lifestyle for both physical and mental health states. As step count is one of the most utilized measures for quantifying physical activity it is important that activity-monitoring devices be both sensitive and specific in recording actual steps taken and disregard non-stepping body movements. The objective of this study was to assess the specificity of five activity monitors during a variety of prescribed non-stepping activities. Methods: Participants wore five activity monitors simultaneously for a variety of prescribed activities including deskwork, taking an elevator, taking a bus journey, automobile driving, washing and drying dishes; functional reaching task; indoor cycling; outdoor cycling; and indoor rowing. Each task was carried out for either a specific duration of time or over a specific distance. Activity monitors tested were the ActivPAL micro™, NL-2000™ pedometer, Withings Smart Activity Monitor Tracker (Pulse O2)™, Fitbit One™ and Jawbone UP™. Participants were video-recorded while carrying out the prescribed activities and the false positive step count registered on each activity monitor was obtained and compared to the video. Results: All activity monitors registered a significant number of false positive steps per minute during one or more of the prescribed activities. The Withings™ activity performed best, registering a significant number of false positive steps per minute during the outdoor cycling activity only (P = 0.025). The Jawbone™ registered a significant number of false positive steps during the functional reaching task and while washing and drying dishes, which involved arm and hand movement (P < 0.01 for both). The ActivPAL™ registered a significant number of false positive steps during the cycling exercises (P < 0.001 for both). Conclusion: As a number of false positive steps were registered on the activity monitors during the non-stepping activities, the authors conclude that non-stepping physical activities can result in the false detection of steps. This can negatively affect the quantification of physical activity with regard to step count as an output. The Withings™ activity monitor performed best with regard to specificity during the activities of daily living tested.

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Wrist-Worn Activity Monitoring Devices Overestimate Sleep Duration and Efficiency in Healthy Adults (2017)

Sleep

Authors: Jumabhoy, R., Dao, P., Maskevich, S., Stout, J. and Drummond, S.

Abstract

ntroduction: The use of activity monitors for sleep measurement purposes has increased in research and consumer settings. However, validation of such monitors is lacking. This study examined agreement on total sleep time (TST) and sleep efficiency (SE) between polysomnography and three activity monitors - Actiwatch Spectrum Pro (ACT), Fitbit One (FB) and Jawbone UP2 (JB). Differences between polysomnography and each activity monitor, and differences between research-grade ACT and commercial devices FB and JB, were examined. Methods: Twenty-two healthy adults (Mage =29.3, SDage=11.4) had one night of sleep measured by polysomnography and each activity monitor simultaneously in a laboratory. Minute-by-minute data were extracted and compared. Wilcoxon signed-ranks tests assessed statistical differences between measures, and Bland-Altman analyses examined clinically meaningful differences between measures, using cut-offs of ±30 minutes for TST and ±5% for SE. Results: Compared to polysomnography, all activity monitors significantly overestimated TST and SE. Differences between polysomnography and each monitor were also clinically meaningful, as Bland-Altman upper and lower limits of agreement for TST exceeded clinical cut-offs for ACT (-64.7min-+166.1min), FB (-66.1min-+189.2min), and JB (-103.6min-+186.2min). Similarly, upper and lower limits of agreement for SE exceeded clinical cut-offs for ACT (-13.0%-+34.0%), FB (-13.1%-+38.5%), and JB (-20.7%-+37.9%). Compared to ACT, only FB significantly overestimated TST and SE. However, differences between ACT and each of FB and JB were clinically meaningful. For FB, Bland-Altman upper limits of agreement exceeded clinical cut-offs for TST (-18.7min-+40.2min) and SE (-3.8%-+8.1%). For JB, upper and lower limits of agreement exceeded clinical cut-offs for TST (-100.4min-+79.3min) and SE (-20.1%-+16.0%). Agreement between devices decreased as TST and SE decreased. All monitors demonstrated poor specificity (18.8–35.6%), but high sensitivity (94.2–99.2%). Conclusion: Results suggest these models of ACT, FB, and JB cannot be used interchangeably with polysomnography. When activity monitors must be used, such as in field settings, FB and JB cannot replace research-grade ACT. Overall, users should account for each monitor's potential to overestimate or underestimate TST and SE to an unacceptable degree. Future research should examine within-subject variability over time to determine whether monitors can be used to track long-term sleep patterns.

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Zero Cadence as a Proxy Indicator of Sitting Behaviors in Objective Monitoring (2017)

Medicine & Science in Sports & Exercise

Authors: Han, H., Aguiar, E.J., Ducharme, S., Lim, J., Moore, C., Busa, M.A., Sirard, J.R., Chipkin, S.R., Staudenmayer, J. and Tudor-Locke, C.

Abstract

Consistent evidence has been presented regarding the potentially deleterious health consequences of prolonged sitting time independent of physical activity level. Zero cadence (0 steps/min) determined using accelerometers may be a suitable proxy measure of sitting behaviors since theoretically no steps should be registered in this position. PURPOSE: The purpose of the current study was to determine the capability of accelerometer-determined zero cadence to predict seated activities of daily living. METHODS: A total of 80 young adults (mean age 29.8±6.7 years), 10 men and 10 women representing each 5-year age-group category between 21-40 years (21-25, 26-30, 31-35, 36-40) performed lab-based simulated daily living activities (i.e., seated rest, watching a movie, computer work, folding laundry while standing, vacuuming, stair stepping and a self-paced over-ground walk) while concurrently wearing multiple (n=7) research-grade (e.g., ActiGraph, ActivPAL, ActiCal and StepWatch) and consumer-grade (e.g., Fitbit One and Vivofit2) accelerometers on manufacturer-indicated locations (i.e., hip, wrist, thigh or ankle). Receiver Operating Characteristic (ROC) analyses were conducted to examine the accuracy of zero cadence for classifying sitting behaviors (e.g., seated rest, watching a movie and computer work) among the performed activities. Sensitivity, specificity, accuracy and area under the ROC curve (AUC) values were compared for each device. RESULTS: All devices demonstrated the capability of using zero cadence to determine sitting activities with high combined sensitivity and specificity (e.g., ranges between 75-98%). AUC values of all devices were above 0.8 (p<.001) indicating good or excellent discrimination ability of zero cadence. Vivofit2 and wrist-worn ActiGraph provided the highest (93%) and lowest (75%) accuracy, respectively. CONCLUSION: In agreement with zero cadence, both research- and consumer-grade activity monitors provided valid capacity for discriminating seated activities from common daily living activities. Based on this preliminary analysis it appears that accumulated time spent at zero cadence obtained by activity monitors can be used as a proxy indicator of time spent sitting.

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A comparison of wearable fitness devices. (2016)

BMC Public Health

Authors: Kaewkannate, K. and Kim, S.

Abstract

BACKGROUND: Wearable trackers can help motivate you during workouts and provide information about your daily routine or fitness in combination with your smartphone without requiring potentially disruptive manual calculations or records. This paper summarizes and compares wearable fitness devices, also called "fitness trackers" or "activity trackers." These devices are becoming increasingly popular in personal healthcare, motivating people to exercise more throughout the day without the need for lifestyle changes. The various choices in the market for wearable devices are also increasing, with customers searching for products that best suit their personal needs. Further, using a wearable device or fitness tracker can help people reach a fitness goal or finish line. Generally, companies display advertising for these kinds of products and depict them as beneficial, user friendly, and accurate. However, there are no objective research results to prove the veracity of their words. This research features subjective and objective experimental results, which reveal that some devices perform better than others. METHODS: The four most popular wristband style wearable devices currently on the market (Withings Pulse, Misfit Shine, Jawbone Up24, and Fitbit Flex) are selected and compared. The accuracy of fitness tracking is one of the key components for fitness tracking, and some devices perform better than others. This research shows subjective and objective experimental results that are used to compare the accuracy of four wearable devices in conjunction with user friendliness and satisfaction of 7 real users. In addition, this research matches the opinions between reviewers on an Internet site and those of subjects when using the device. RESULTS: Withings Pulse is the most friendly and satisfactory from the users' viewpoint. It is the most accurate and repeatable for step and distance tracking, which is the most important measurement of fitness tracking, followed by Fitbit Flex, Jawbone Up24, and Misfit Shine. In contrast, Misfit Shine has the highest score for design and hardware, which is also appreciated by users. CONCLUSIONS: From the results of experiments on four wearable devices, it is determined that the most acceptable in terms of price and satisfaction levels is the Withings Pulse, followed by the Fitbit Flex, Jawbone Up24, and Misfit Shine.

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A Leisure-Time Physical Activity Intervention for Adolescents With Visual Impairments (2016)

Research Quarterly for Exercise and Sport

Authors: Haegele, J.A. and Porretta, D.

Abstract

Background/Purpose: School-aged individuals with visual impairments tend to be less physically active than their non-visually impaired peers (Kozub & Oh, 2004). However, a recent literature review revealed only 7 physical activity intervention studies targeting this population during a recent 30-year period (Haegele & Porretta, 2015). Of those studies, 1 utilized a theoretical framework. Therefore, the purpose of this study was to examine the effects of a social-cognitive theory-based physical education intervention on leisure-time physical activity of adolescents with visual impairments. Method: Six adolescents with visual impairments attending a Midwestern residential school for the blind received a 9-lesson physical activity intervention during in-school physical education. Lessons were designed to assist participants in developing individual activity programs while addressing social-cognitive theory constructs. Each lesson included curricular concepts, in-class activities, and homework. A multiple-baseline across-participants design was used, and physical activity behavior was measured by steps taken using Fitbit Zips. Questionnaires were used to collect data (i.e., change scores) on the social-cognitive theory constructs of self-efficacy, self-regulation, social support, and outcome expectancy. Data were analyzed through visual analysis, effect size estimates (percentage of nonoverlapping data [PND]), and descriptive statistics. A treatment integrity checklist was developed, and 2 trained observers completed them independently (99.8% agreement). Analysis/Results: Results did not demonstrate a functional relation between physical activity (i.e., number of steps taken) and the intervention. PND scores ranged from 0% to 48%. However, positive changes in mean steps per day for all participants were found from baseline to final intervention (Participant 1, 2,225–4,178 [87%]; Participant 2, 1,328–2,632 [98%]; Participant 3, 1,137– 2,111 [86%]; Participant 4, 1,151–1,740 [51%]; Participant 5, 521–588 [13%]; and Participant 6, 2,751–3,858 [40%]). Relative to the social-cognitive theory constructs, all 6 participants demonstrated positive changes in selfregulation (37%–203%), 5 demonstrated positive changes in outcome expectancy (6%–69%), and 4 demonstrated positive changes in social support (15%–42%). Three of 6 participants demonstrated increases in each of 2 selfefficacy questionnaires. Conclusion: The intervention did not exert functional control of the participants' physical activity (i.e., steps taken). Results may have been directly influenced by several study limitations, such as seasonality and program truncation for 3 participants. Therefore, the results may not represent the full intervention effect. With the lack of physical activity intervention research related to adolescent-aged individuals with visual impairments (Haegele & Porretta, 2015) and the influence physical activity has on health-related outcomes (e.g., obesity), further research is needed.

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A Technology-Mediated Behavioral Weight Gain Prevention Intervention for College Students: Controlled, Quasi-Experimental Study. (2016)

Journal of Medical Internet Research

Authors: West, D.S., Monroe, C.M., Turner-McGrievy, G., Sundstrom, B., Larsen, C., Magradey, K., Wilcox, S. and Brandt, H.M.

Abstract

BACKGROUND: Both men and women are vulnerable to weight gain during the college years, and this phenomenon is linked to an increased risk of several chronic diseases and mortality. Technology represents an attractive medium for the delivery of weight control interventions focused on college students, given its reach and appeal among this population. However, few technology-mediated weight gain prevention interventions have been evaluated for college students. OBJECTIVE: This study examined a new technology-based, social media-facilitated weight gain prevention intervention for college students. METHODS: Undergraduates (n =58) in two sections of a public university course were allocated to either a behavioral weight gain prevention intervention (Healthy Weight, HW; N=29) or a human papillomavirus (HPV) vaccination awareness intervention (control; N=29). All students were enrolled, regardless of initial body weight or expressed interest in weight management. The interventions delivered 8 lessons via electronic newsletters and Facebook postings over 9 weeks, which were designed to foster social support and introduce relevant educational content. The HW intervention targeted behavioral strategies to prevent weight gain and provided participants with a Wi-Fi-enabled scale and an electronic physical activity tracker to facilitate weight regulation. A repeated-measures analysis of variance was conducted to examine within- and between-group differences in measures of self-reported weight control practices and objectively measured weight. Use of each intervention medium and device was objectively tracked, and intervention satisfaction measures were obtained. RESULTS: Students remained weight stable (HW: -0.48+1.9 kg; control: -0.45+1.4 kg), with no significant difference between groups over 9 weeks (P =.94). However, HW students reported a significantly greater increase in the number of appropriate weight control strategies than did controls (2.1+4.5 vs -1.1+3.4, respectively; P =.003) and there was no increase in inappropriate weight control behaviors (P =.11). More than 90% of students in the HW arm opened the electronic newsletters each week, and the average number of Facebook interactions (comments and likes) per student each week was 3.3+1.4. Each self-monitoring device was initialized by 90% of HW students. On average, they used their physical activity tracker for 23.7+15.2 days and their Wi-Fi scale for 14.1+13.1 days over the 9 weeks. HW students rated the intervention favorably. CONCLUSIONS: The short-term effect of this technology-based weight gain prevention intervention for college students is promising and merits evaluation over a longer duration to determine whether engagement and behavioral improvements positively affect weight outcomes and can be maintained.

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Acceptance of Commercially Available Wearable Activity Trackers Among Adults Aged Over 50 and With Chronic Illness: A Mixed-Methods Evaluation. (2016)

JMIR mHealth and uHealth

Authors: Mercer, K., Giangregorio, L., Schneider, E., Chilana, P., Li, M. and Grindrod, K.

Abstract

BACKGROUND: Physical inactivity and sedentary behavior increase the risk of chronic illness and death. The newest generation of "wearable" activity trackers offers potential as a multifaceted intervention to help people become more active. OBJECTIVE: To examine the usability and usefulness of wearable activity trackers for older adults living with chronic illness. METHODS: We recruited a purposive sample of 32 participants over the age of 50, who had been previously diagnosed with a chronic illness, including vascular disease, diabetes, arthritis, and osteoporosis. Participants were between 52 and 84 years of age (mean 64); among the study participants, 23 (72%) were women and the mean body mass index was 31 kg/m(2). Participants tested 5 trackers, including a simple pedometer (Sportline or Mio) followed by 4 wearable activity trackers (Fitbit Zip, Misfit Shine, Jawbone Up 24, and Withings Pulse) in random order. Selected devices represented the range of wearable products and features available on the Canadian market in 2014. Participants wore each device for at least 3 days and evaluated it using a questionnaire developed from the Technology Acceptance Model. We used focus groups to explore participant experiences and a thematic analysis approach to data collection and analysis. RESULTS: Our study resulted in 4 themes: (1) adoption within a comfort zone; (2) self-awareness and goal setting; (3) purposes of data tracking; and (4) future of wearable activity trackers as health care devices. Prior to enrolling, few participants were aware of wearable activity trackers. Most also had been asked by a physician to exercise more and cited this as a motivation for testing the devices. None of the participants planned to purchase the simple pedometer after the study, citing poor accuracy and data loss, whereas 73% (N=32) planned to purchase a wearable activity tracker. Preferences varied but 50% felt they would buy a Fitbit and 42% felt they would buy a Misfit, Jawbone, or Withings. The simple pedometer had a mean acceptance score of 56/95 compared with 63 for the Withings, 65 for the Misfit and Jawbone, and 68 for the Fitbit. To improve usability, older users may benefit from devices that have better compatibility with personal computers or less-expensive Android mobile phones and tablets, and have comprehensive paper-based user manuals and apps that interpret user data. CONCLUSIONS: For older adults living with chronic illness, wearable activity trackers are perceived as useful and acceptable. New users may need support to both set up the device and learn how to interpret their data.

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Accuracy of Commercial Activity Trackers to Measure Energy Expenditure During a Controlled Exercise Trial (2016)

Medicine & Science in Sports & Exercise

Authors: Hargens, T.A., Deyarmin, K.N., Snyder, K.M., Mihalik, A.G. and Sharpe, L.E.

Abstract

Commercially available activity trackers are increasingly popular for the general public in measuring physical activity. Daily energy expenditure (EE) is one of the primary measures provided to the public by these devices. Whether these devices can accurately estimate EE is not clear. PURPOSE: To compare the EE values obtained from two commercially available devices (Fitbit Charge and Fitbit One) to that measured by the Actigraph GT3X and indirect calorimetry (IC). METHODS: Seventeen men (n = 4) and women (n = 13) (Age: Mean ± SD = 27.8 ± 9.0; BMI = 24.7 ± 4.2 kg/m2) completed a submaximal treadmill exercise trial while wearing a Fitbit Charge, a Fitbit One, and an Actigraph GT3X. Oxygen consumption and EE (in kcals) was measured via breath-by-breath IC system. The exercise trial consisted of four, 5-minute stages (2.0 mph/0% grade; 2.0 mph/5%; 3.0 mph/0%; 3.0 mph/5%). To approximate the EE reported by the Fitbit devices, an estimated resting metabolic rate was added to the EE reported by the Actigraph. Repeated measures ANOVA was used to asses the main effects for measurement device and stage. RESULTS: There was a significant main effect for measurement device (P < 0.01) and stage (P < 0.01). Post-hoc analysis determined that the Fitbit Charge (P < 0.01), the Fitbit One (P textless 0.01), and the Actigraph (P < 0.01), all differed from IC in measuring EE. The Fitbit Charge (P < 0.01) overestimated EE across all stages (25.3 ± 4.7, 31.0 ± 3.7, 33.0 ± 5.8 and 34.2 ± 6.1 vs 13.2 ± 2.3, 18.8 ± 3.0, 20.5 ± 2.8 and 26.9 ± 5.0 for Fitbit One and IC, respectively). The Fitbit One (14.4 ± 2.7, 15.3 ± 2.7, 19.9 ± 3.4 and 21.1 ± 4.6; P < 0.01) and the Actigraph (6.7 ± 3.8, 7.4 ± 25.4 ± 8.5 and 26.4 ± 7.9; P textless 0.01) underestimated EE compared to IC across all stages. Significant interactions between IC and the Fitbit One (P < 0.01), and IC and the Actigraph (P < 0.01), however, indicate that they are less sensitive to grade changes than IC. CONCLUSION: Results show that the wrist-worn Fitbit Charge overestimates EE, which may negatively impact the fitness goals of the wearer, particularly as it relates to energy balance and weight loss. The hip worn devices appear to be closer to IC in EE measures, but do not accurately reflect changes in treadmill grade, impacting those who use this exercise mode.

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Accuracy of the Fitbit for Measuring Preschoolers' Physical Activity (2016)

Medicine & Science in Sports & Exercise

Authors: Byun, W., Barry, A. and Lee, J.-M.

Abstract

Identifying an accurate and feasible measurement tool for assessing physical activity (PA) is a priority in epidemiologic research. Although wearable activity monitors yields high potentials for being utilized in research, little information is available on the accuracy of those monitors in young children. PURPOSE: To evaluate the accuracy of the Fitbit Flex (FF) activity monitor for assessing preschooler' PA and sedentary behavior (SED) in free-living conditions, using the previously validated accelerometer-based monitor, ActiGraph GT3X+ (AG), as a criterion measure. METHODS: 27 preschool age children (Girl: 41%, Age: 4.9 ± 1.1 yrs, BMI: 16.5 ± 1.6 kgtextperiodcenteredm2) wore AG (on dominant hip) and FF (on the non-dominant wrist) simultaneously for 24 hours. Using age-appropriate cutpoints for AG (Pate's 2006) and manufacturer-specific algorithms for FF, data from AG (15-sec epoch) and FF (60-sec epoch) were reduced in terms of time spent (min/day) in SED, moderate-to-vigorous PA (MVPA), and Total PA (TPA). Pearson correlations was used examine agreement between the estimates from AG and FF. Mean absolute percent errors (MAPEs) were computed as measurement errors. Equivalence test using SAS PROC MIXED procedure was used to compare the 85% confidence intervals (CI) of the estimates from the FF with the respective equivalence zone (EZ; ± 15% of the mean estimates) from the AG. RESULTS: The FF yielded significantly equivalent estimates of SED (FF: Mean (M) = 673 min, 85% CI: 632-714 min vs. AG: M = 631, EZ: 537-726 min) and TPA (FF: M = 337 min, 85% CI: 309-365 min vs. AG: M = 379 min, EZ: 303-435 min) as the AG. However, the estimate of MVPA from the FF was not equivalent to that from the AG. Correlations between FF and AG were consistently high for SED (r = 0.86, P textless.01) and TPA (r = 0.70, P textless.01), but moderate for MVPA (r = 0.59, P textless.01). MAPEs were 9.2, 70.1, and 14.5% for SED, MVPA, and TPA, respectively. CONCLUSIONS: The accuracy of the FF for estimating SED and TPA was supported by the high correlations and significant equivalence to AG. However, relatively large MAPEs and results from equivalence test suggest that the MVPA estimates from the FF were not equivalent to those from AG. Future studies utilizing FF in preschool age children should be aware of these findings. Efforts to replicate our findings with longer monitoring in larger samples are warranted

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Accuracy of Wrist and Hip-worn Commercial Physical Activity Monitors In Free Living Conditions (2016)

Medicine & Science in Sports & Exercise

Authors: Deyarmin, K.N., Snyder, K.M., Mihalik, A.G. and Hargens, T.A.

Abstract

It is recommended that individuals participate in 150 minutes of moderate intensity physical activity or 75 minutes of vigorous physical activity each week. Commercially-available PA monitors are becoming popular for everyday use. These PA monitors provide feedback on steps, energy expenditure, moderate-to-vigorous intensity physical activity (MVPA), and sleep quality, with new models introduced to the public at an increasing rate. Whether these devices provide the consumer with accurate information is not well understood. PURPOSE: To examine the accuracy of a wrist worn commercial device (Fitbit Charge) and a hip worn device (Fitbit One) in regard to steps and MVPA under free living conditions, compared to a research-grade accelerometer (Actigraph GT3X). METHODS: Participants (n=17, Mean SD, Age: 27.8 9.0; BMI: 24.7 4.2) wore 3 devices (Actigraph GT3X, Fitbit Charge and Fitbit One) for 7 consecutive days. Participants were told to go about their regular daily activities while wearing all 3 devices at the same time. The GT3X was worn on the right hip. RESULTS: Paired t-tests showed that mean steps per day between the Actigraph (10510.6 2443.7) and the Fitbit Charge (12537.7 3936.2) differed significantly (P = 0.016). Mean steps per day between the Actigraph and the Fitbit One (11726.7 11726.7) also differed (P = 0.001). Steps between the Fitbit Charge and Fitbit One did not differ (P = 0.195). No significant differences were found in active minutes recorded between any of the devices (53.0 15.2, 52.0 42.9 and 52.8 28.9) for the Actigraph, Charge and One, respectively). Bland-Altman analysis concluded that the Actigraph and Charge (P = 0.02) and the Actigraph and One (P textless 0.01) did not agree for steps, whereas the Charge and the One did agree (P = 0.2). All three devices showed good agreement with regard to MVPA. CONCLUSION: Results showed that the 2 commercial devices did not agree with the Actigraph, a widely used PA monitor for research purposes, in mean step data. However, the devices did show good agreement with regard to MVPA, suggesting that these commercial devices may provide useful feedback for individuals seeking to achieve the current public health PA guidelines for MVPA.

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Accuracy Of Wrist-worn Activity Monitors At Three Walking Speeds On The Treadmill (2016)

Medicine & Science in Sports & Exercise

Authors: Smith, J.D.

Abstract

Wrist-worn activity monitors are becoming increasingly popular with many manufacturers offering such devices. PURPOSE: To assess the accuracy of wrist-worn activity monitors at three walking speeds on a treadmill. METHODS: Seventy-seven participants (age = 24.9±3.5 yrs, ht = 170.0±8.9 cm, wt = 78.6±19.9 kg) were fitted with a Fitbit Flex (FF) on the right wrist, a Movband Model 2 (MV), Lifetrak C200 (LT), Garmin Vivofit (GV), Polar Loop (PL) on the left wrist, and an Omron HJ-113 (HJ) on the right waist. Each participant walked for two minutes at 53.6 m/min (2.0 mph), 80.5 m/min (3.0 mph), and 107.3 m/min (4.0 mph). At the end of each trial monitor counts and actual step counts from a hand tally (AC) were recorded. A repeated measures ANOVA was used to determine significant differences between the counts. Single measure intraclass correlation (ICC) from a two-way random effects ANOVA was used to assess the agreement between AC and monitor counts. Pedometer error was calculated as [(monitor steps-actual steps)/actual steps] * 100. RESULTS: For all speeds, monitor counts were significantly lower than AC (ptextless.05) except for GV and HJ at 53.6 m/min and 80.5 m/min, and for LT and HJ at 107.3 m/min, none of which were significantly different than AC (ptextgreater.05). Agreement according to ICC was highest with HJ for all speeds (0.68, 0.97, and 0.82 during 53.6 m/min, 80.5 m/min, and 107.3 m/min, respectively). Agreement among the wrist worn monitors was highest with GV (0.71) and lowest with FF (0.18) at the slowest speed, highest with GV (0.67) and lowest with LT (0.03) at 80.7 m/min, and highest with PL (0.28) and lowest with LT (0.0) at the fastest speed. Error was greatest with LT at 40.6% while walking at 53.6 m/min, 19.6% with PL at 80.5 m/min, and 19.0% with PL at 107.3 m/min. Error was least with GV at 3.2% while walking at 53.6 m/min. Although error was least with HJ during 53.6 m/min and 107.3 m/min (1.2% and 1.2%, respectively), GV was 3.2% and LT was 7.7% during 80.5 m/min and 107.3 m/min, respectively. CONCLUSION: The hip-worn pedometer (HJ) provides the most accurate step count across all speeds. Among the wrist-worn monitors, GV seems to provide the most accurate measure of step count in this laboratory-controlled study. Weaver, A.L., Stutzman, S.E., Supnet, C. and Olson, D.M.

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An Exercise Intervention for South Asian Mothers with Risk Factors for Diabetes (2016)

Translational Journal of the American College of Sports Medicine

Authors: Kandula, Namratha R.; Dave, Swapna S.; De Chavez, Peter John D.; Marquez, David X.; Bharucha, Himali; Mammen, Shinu M.; Dunaif, Andrea; Ackermann, Ronald T.; Kumar, Santosh; Siddique, J.

Abstract

South Asians (Indians, Pakistanis, Bangladeshis, Sri Lankans, Nepalis, and Bhutanese) in the United States have a very high prevalence of type 2 diabetes mellitus (DM). This pilot study evaluated a culturally tailored exercise intervention among South Asian immigrant mothers with DM risk factors. Through an academic–community partnership, South Asian women with risk factors for DM and who had at least one child between 6 and 14 yr were enrolled into this single-arm study. The intervention for the mothers included 16 wk of twice weekly exercise classes, self-monitoring with activity trackers, goal setting, and classes on healthy eating. Based on prior community-based participatory research, children were offered exercise classes during the mothers' classes. The primary efficacy outcomes were change in mothers' moderate/vigorous physical activity and body weight pre- and postintervention (16 wk). Program adherence, clinical, and psychosocial outcomes were measured. A qualitative process evaluation was conducted to understand participant perspectives. Participants' (n = 30) average age was 40 yr (SD, 5), 57% had a high school education or less, and all were overweight/obese. At baseline, women were not meeting the recommended physical activity guidelines. Overall, participants attended 75% of exercise classes. Compared with baseline, participants' weight decreased by 3.2 lb (95% confidence interval, -5.5 to -1.0) postintervention. Among women who attended at least 80% of classes (n = 17), weight change was -4.8 lb (95% confidence interval, -7.7 to -1.9). Change in accelerometer-measured physical activity was not significant; however, exercise-related confidence increased from baseline (P textless 0.01). Women described multiple physical and psychosocial benefits from the intervention. In conclusion, this pilot study suggests that a culturally tailored exercise intervention that included exercise classes for children was feasible and had physical and psychosocial benefits in South Asian mothers with risk factors for DM.

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Assessment, Assurance, and Actuation: The Use of Activity Trackers to Monitor Physical Activity in a Pediatric Population with Congenital Heart Disease (2016)

Canadian Journal of Cardiology

Authors: Dean, P., Voss, C., De Souza, A. and Harris, K.

Abstract

BACKGROUND: Physical activity (PA) trackers have demonstrated the potential to improve the PA habits of pediatric patients with congenital heart disease (CHD). This study was designed to reach patients across the province of British Columbia in order to assess levels of PA in a pediatric CHD population, provide assurance to patients and families regarding exercise capacity, and actuate an increase in PA. METHODS: Eligible patients (9-18 years old with a diagnosis of CHD) were recruited during their regular clinic appointments. Baseline testing involved PA measurement using an accelerometer (GT3X+ or GT9X ActiGraph LLC). Participants were then given an activity tracker (FitBit Charge HRTM) to wear for 16 weeks (late October-early February). Their activity was monitored during this intervention by an exercise physiologist who would interact with participants on a bi-weekly basis. Introduction to the exercise physiologist was carried out over SkypeTM; subsequent interaction was conducted by email in order to eliminate geography as a barrier to participation. PA was re-assessed after 16 weeks with an accelerometer. RESULTS: Sixty-six subjects are currently enrolled and 21 subjects (8M, 13F) have completed the intervention thus far; recruitment success rate is 97%. There were no significant changes between baseline and follow-up daily step count (8384`2544 vs. 7524`1908, respectively) or moderate-to- vigorous PA (54`21 vs. 48`15 mins respectively; all p>0.05). The mean temperature ranged from 6 C at the beginning of the study period to 0 C at the end of the study period; mean snow cover ranged from 0.0cm to 9.0cm over the same time points. Participant compliance with the activity tracker remained high throughout the intervention; wear-time averaged 5.7 days per week. Of those (n1/416) who completed a voluntary feedback survey 63% found the activity tracker useful as a motivational tool. CONCLUSION: It is difficult to comment on the motivational power of the intervention because changes in weather likely acted as a confounding variable in this cohort. However, use of an activity tracker inspired interest in PA over the winter months and may have blunted the seasonal decline in PA that has been previously established in this age group. Subjects currently enrolled will provide the opportunity to compare the efficacy of the intervention across various seasons. The success of recruitment and high rates of compliance indicate that pediatric patients (and their families) are aware of the importance of PA and are seeking assurance regarding current activity habits and, for some, actuation to improve upon them.

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Balanced: a randomised trial examining the efficacy of two self-monitoring methods for an app-based multi-behaviour intervention to improve physical activity, sitting and sleep in adults. (2016)

BMC Public Health

Authors: Duncan, M.J., Vandelanotte, C., Trost, S.G., Rebar, A.L., Rogers, N., Burton, N.W., Murawski, B., Rayward, A., Fenton, S. and Brown, W.J.

Abstract

BACKGROUND: Many adults are insufficiently physically active, have prolonged sedentary behaviour and report poor sleep. These behaviours can be improved by interventions that include education, goal setting, self-monitoring, and feedback strategies. Few interventions have explicitly targeted these behaviours simultaneously or examined the relative efficacy of different self-monitoring methods. METHODS/DESIGN: This study aims to compare the efficacy of two self-monitoring methods in an app-based multi-behaviour intervention to improve objectively measured physical activity, sedentary, and sleep behaviours, in a 9 week 2-arm randomised trial. Participants will be adults (n?=?64) who report being physically inactive, sitting textgreater8 h/day and frequent insufficient sleep (=14 days out of last 30). The "Balanced" intervention is delivered via a smartphone 'app', and includes education materials (guidelines, strategies to promote change in behaviour), goal setting, self-monitoring and feedback support. Participants will be randomly allocated to either a device-entered or user-entered self-monitoring method. The device-entered group will be provided with a activity tracker to self-monitor behaviours. The user-entered group will recall and manually record behaviours. Assessments will be conducted at 0, 3, 6, and 9 weeks. Physical activity, sedentary behaviour and sleep-wake behaviours will be measured using the wrist worn Geneactiv accelerometer. Linear mixed models will be used to examine differences between groups and over time using an alpha of 0.01. DISCUSSION: This study will evaluate an app-based multi-behavioural intervention to improve physical activity, sedentary behaviour and sleep; and the relative efficacy of two different approaches to self-monitoring these behaviours. Outcomes will provide information to inform future interventions and self-monitoring targeting these behaviours.

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Biosensors to assess performance status in cancer (BioAPS Study). (2016)

Journal of Clinical Oncology

Authors: Shinde, A.M., Gresham, G.K., Hendifar, A.E., Tuli, R., Spiegel, B. and Figlin, R.A.

Abstract

Background: Oncologists assess patient (Pt) performance status (PS) to inform appropriate chemotherapy (Ct) decisions. Eastern Cooperative Oncology Group PS (ECOG-PS, range 0-5) and Karnofsky PS (KPS; range 0-100%), are subjective scales of function and ability for self-care, and are the primary scales used in oncologic research and practice. Higher ECOG-PS/Lower KPS scores are associated with poorer survival outcomes and Ct tolerance. Despite its prognostic importance, ECOG-PS/KPS have been criticized for being biased and incomplete resulting in inappropriate Ct decisions that are costly and potentially harmful. They also do not capture a Pts ?free range? activity outside of the clinic. Wearable biometric sensors, such as Fitbit Charge HR (FC), can provide objective data regarding activity (number of steps, stairs climbed, heart rate (HR)) outside the the four walls of the clinic. Longitudinally collected patient reported outcomes (PROs) around function and activity may provide a better understanding of Pt PS. We hypothesize that combining objective data from FC with PROs could provide a more accurate assessment of patient PS. Furthermore, longitudinally collected biometric data may allow for real-time detection of Pt distress. Methods: We will recruit 30 Pts with stage 3/4 cancer, = 18yrs, English speaking, ambulatory, with a smartphone, and prognosis of textgreater 3 months. Subjects will wear a FC for 2 weeks, and complete online NIH PROMIS tools (Physical Function, Pain, Sleep, Fatigue, and Emotional Distress) on D1, 8, and 15. At Pt visits, MDs/RNs will score ECOG-PS/KPS History, physical exam and assessment for frailty phenotype will be completed at baseline. An exit interview will capture Pt experience with FC. Ct toxicity and survival will be recorded at 3- and 6-month follow-up. Primary Objective: Assess the association between FC data, and PROMIS PROs versus validated ECOG-PS/KPS scales. Secondary Objectives: Assess 1) the association between FC data and PROMIS indicators of distress, 2) the correlation of frailty phenotype with biosensor activity data, 3) the feasibility of collecting biometric data and PROMIS tools in cancer pts, and 4) the relationship between FC data and Ct toxicity and survival outcomes. Clinical trial information: NCT02659358.

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Can a Home-based Cardiac Rehabilitation Program Improve the Physical Function Quality of Life in Children With Fontan Circulation? (2016)

Congenital Heart Disease

Authors: Jacobsen, R.M., Danduran, M., Mussatto, K., Neubauer, J. and Ginde, S.

Abstract

Objective: Patients after Fontan operation for complex congenital heart disease (CHD) have decreased exercise capacity and report reduced health-related quality of life (HRQOL). Studies suggest hospital-based cardiac physical activity programs can improve HRQOL and exercise capacity in patients with CHD; however, these programs have variable adherence rates. The impact of a home-based cardiac physical activity program in Fontan survivors is unclear. This pilot study evaluated the safety, feasibility, and benefits of an innovative home-based physical activity program on HRQOL in Fontan patients. Methods: A total of 14 children, 8–12 years, with Fontan circulation enrolled in a 12-week moderate/high intensity home-based cardiac physical activity program, which included a home exercise routine and 3 formalized in-person exercise sessions at 0, 6, and 12 weeks. Subjects and parents completed validated questionnaires to assess HRQOL. The Shuttle Test Run was used to measure exercise capacity. A Fitbit Flex Activity Monitor was used to assess adherence to the home activity program. Results: Of the 14 patients, 57% were male and 36% had a dominant left ventricle. Overall, 93% completed the program. There were no adverse events. Parents reported significant improvement in their child's overall HRQOL (P?<?.01), physical function (P?<?.01), school function (P?=?.01), and psychosocial function (P?<?.01). Patients reported no improvement in HRQOL. Exercise capacity, measured by total shuttles and exercise time in the Shuttle Test Run and calculated VO2max, improved progressively from baseline to the 6 and 12 week follow up sessions. Monthly Fitbit data suggested adherence to the program. Conclusion: This 12-week home-based cardiac physical activity program is safe and feasible in preteen Fontan patients. Parent proxy-reported HRQOL and objective measures of exercise capacity significantly improved. A 6-month follow up session is scheduled to assess sustainability. A larger study is needed to determine the applicability and reproducibility of these findings in other age groups and forms of complex CHD.

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Cardiac Patients' Walking Activity Determined by a Step Counter in Cardiac Telerehabilitation: Data From the Intervention Arm of a Randomized Controlled Trial. (2016)

Journal of Medical Internet Research

Authors: Thorup, C., Hansen, J., Grønkjær, M., Andreasen, J.J., Nielsen, G., Sørensen, E.E. and Dinesen, B.I.

Abstract

BACKGROUND: Walking represents a large part of daily physical activity. It reduces both overall and cardiovascular diseases and mortality and is suitable for cardiac patients. A step counter measures walking activity and might be a motivational tool to increase and maintain physical activity. There is a lack of knowledge about both cardiac patients' adherence to step counter use in a cardiac telerehabilitation program and how many steps cardiac patients walk up to 1 year after a cardiac event. OBJECTIVE: The purpose of this substudy was to explore cardiac patients' walking activity. The walking activity was analyzed in relation to duration of pedometer use to determine correlations between walking activity, demographics, and medical and rehabilitation data. METHODS: A total of 64 patients from a randomized controlled telerehabilitation trial (Teledi@log) from Aalborg University Hospital and Hjoerring Hospital, Denmark, from December 2012 to March 2014 were included in this study. Inclusion criteria were patients hospitalized with acute coronary syndrome, heart failure, and coronary artery bypass grafting or valve surgery. In Teledi@log, the patients received telerehabilitation technology and selected one of three telerehabilitation settings: a call center, a community health care center, or a hospital. Monitoring of steps continued for 12 months and a step counter (Fitbit Zip) was used to monitor daily steps. RESULTS: Cardiac patients walked a mean 5899 (SD 3274) steps per day, increasing from mean 5191 (SD 3198) steps per day in the first week to mean 7890 (SD 2629) steps per day after 1 year. Adherence to step counter use lasted for a mean 160 (SD 100) days. The patients who walked significantly more were younger (P=.01) and continued to use the pedometer for a longer period (P=.04). Furthermore, less physically active patients weighed more. There were no significant differences in mean steps per day for patients in the three rehabilitation settings or in the disease groups. CONCLUSIONS: This study indicates that cardiac telerehabilitation at a call center can support walking activity just as effectively as telerehabilitation at either a hospital or a health care center. In this study, the patients tended to walk fewer steps per day than cardiac patients in comparable studies, but our study may represent a more realistic picture of walking activity due to the continuation of step counter use. Qualitative studies on patients' behavior and motivation regarding step counter use are needed to shed light on adherence to and motivation to use step counters.

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Consumer-based Physical Activity Monitors and Research-grade Accelerometers Underestimate Physical Activity in a Semi-structured Setting (2016)

Circulation

Authors: Montoye, A.H., Tuttle, M.S., Nelson, M.B., Steeves, J.A. and Kaminsky, L.A.

Abstract

Introduction: Consumer-based physical activity (PA) monitors have become popular tools to track PA (steps and energy expenditure [EE]), but little is known about their accuracy and comparability to research-grade PA monitors. Hypothesis: We hypothesized that consumer-based PA monitors would have lower PA measurement accuracy than a research-grade PA monitor. Methods: Healthy adults (n=30 [n=15 male], aged 18-79 years) were fitted with three Fitbit PA monitors (One and Zip, left hip; Flex, non-dominant wrist), one Jawbone PA monitor (UP24, non-dominant wrist), and one research-grade, accelerometer-based PA monitor (ActiGraph Link; right hip). Subjects performed =12 activities from a list of 21 sedentary, household, and ambulatory activities during an 80-minute, semi-structured protocol while wearing all five monitors and a portable metabolic analyzer. Steps and EE were recorded from PA monitors at the beginning and end of the protocol. A previously validated EE prediction equation (Freedson) was used to estimate EE from PA (PAEE) using ActiGraph data. A previous lab visit by subjects was used to estimate resting EE; resting EE was added to PAEE to estimate total EE from the ActiGraph. Criterion measures included a trained research assistant counting total steps (with a hand tally counter) and the metabolic analyzer for measurement of total EE and PAEE (total EE - resting EE). Repeated measures analysis of variance was used to assess step, total EE, and PAEE measures among the consumer-based PA monitors, ActiGraph, and criterion methods. Results: Participants averaged 3,231±104 steps, 294±10 kcals for total EE, and 235±9 kcals for PAEE according to criterion measures. Consumer-based PA monitors and the ActiGraph significantly underestimated steps (mean difference [MD]: 714-1,047 steps [22.1-32.4%], p<0.01), total EE (MD: 37-109 kcals [12.6-37.1%], p<0.05), and PAEE (MD: 35-107 kcals [14.9-45.5%], p<0.05) compared to criterion measures. The Fitbit One, Zip, and Flex monitors estimated significantly higher steps than the ActiGraph (MD: 199-302 steps [9.1-13.8%], p<0.05), but there was no significant difference in steps estimated by the UP24 compared to the ActiGraph (MD: 144 steps [6.6%], p=0.21). All consumer-based monitors estimated significantly higher total EE and PAEE than the ActiGraph (MD: 23-60 kcals [12.6-32.7%] and 22-53 kcals [17.3.0-41.2%], respectively; p<0.05). Conclusions: All PA monitors underestimated steps, total EE, and PAEE compared to the criterion measures. Large variability existed in the step and EE estimates from the PA monitors tested. Contrary to our hypothesis, the research-grade ActiGraph monitor (using Freedson EE prediction equation) had more severe PA underestimates than the consumer-based PA monitors. In conclusion, estimates of PA between studies using consumer-based vs. research-grade PA monitors should be interpreted with caution.

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Development of a Mobile Phone-Based Weight Loss Lifestyle Intervention for Filipino Americans with Type 2 Diabetes: Protocol and Early Results From the PilAm Go4Health Randomized Controlled Trial (2016)

JMIR Research Protocols

Authors: Bender, M.S., Santos, G.-M., Villanueva, C. and Arai, S.

Abstract

Background: Filipino Americans are the second largest Asian subgroup in the United States, and were found to have the highest prevalence of obesity and type 2 diabetes (T2D) compared to all Asian subgroups and non-Hispanic whites. In addition to genetic factors, risk factors for Filipinos that contribute to this health disparity include high sedentary rates and high fat diets. However, Filipinos are seriously underrepresented in preventive health research. Research is needed to identify effective interventions to reduce Filipino diabetes risks, subsequent comorbidities, and premature death. Objective: The overall goal of this project is to assess the feasibility and potential efficacy of the Filipino Americans Go4Health Weight Loss Program (PilAm Go4Health). This program is a culturally adapted weight loss lifestyle intervention, using digital technology for Filipinos with T2D, to reduce their risk for metabolic syndrome. Methods: This study was a 3-month mobile phone-based pilot randomized controlled trial (RCT) weight loss intervention with a wait list active control, followed by a 3-month maintenance phase design for 45 overweight Filipinos with T2D. Participants were randomized to an intervention group (n=22) or active control group (n=23), and analyses of the results are underway. The primary outcome will be percent weight change of the participants, and secondary outcomes will include changes in waist circumference, fasting plasma glucose, glycated hemoglobin A1c, physical activity, fat intake, and sugar-sweetened beverage intake. Data analyses will include descriptive statistics to describe sample characteristics and a feasibility assessment based on recruitment, adherence, and retention. Chi-square, Fisher's exact tests, t-tests, and nonparametric rank tests will be used to assess characteristics of randomized groups. Primary analyses will use analysis of covariance and linear mixed models to compare primary and secondary outcomes at 3 months, compared by arm and controlled for baseline levels. Results: Recruitment was completed in January, 2016, and participant follow-up continued through June, 2016. At baseline, mean age was 57 years, 100% (45/45) of participants self-identified as Filipinos, and the cohort was comprised of 17 males and 28 females. Overall, participants were obese with a baseline mean body mass index of 30.2 kg/m2 (standard deviation 4.9). The majority of participants were immigrants (84%, 38/45), with 47% (21/45) living in the United States for more than 10 years. One third of all participants (33%, 15/45) had previously used a pedometer. Conclusions: This study will provide preliminary evidence to determine if the PilAm Go4Health weight loss lifestyle intervention is feasible, and if the program demonstrates potential efficacy to reduce risks for metabolic syndrome in Filipinos with T2D. Positive results will lend support for a larger RCT to evaluate the effectiveness of the PilAm Go4Health intervention for Filipinos.

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Devices for Self-Monitoring Sedentary Time or Physical Activity: A Scoping Review. (2016)

Journal of Medical Internet Research

Authors: Sanders, J.P., Loveday, A., Pearson, N., Edwardson, C., Yates, T., Biddle, S.J.H. and Esliger, D.W.

Abstract

BACKGROUND: It is well documented that meeting the guideline levels (150 minutes per week) of moderate-to-vigorous physical activity (PA) is protective against chronic disease. Conversely, emerging evidence indicates the deleterious effects of prolonged sitting. Therefore, there is a need to change both behaviors. Self-monitoring of behavior is one of the most robust behavior-change techniques available. The growing number of technologies in the consumer electronics sector provides a unique opportunity for individuals to self-monitor their behavior. OBJECTIVE: The aim of this study is to review the characteristics and measurement properties of currently available self-monitoring devices for sedentary time and/or PA. METHODS: To identify technologies, four scientific databases were systematically searched using key terms related to behavior, measurement, and population. Articles published through October 2015 were identified. To identify technologies from the consumer electronic sector, systematic searches of three Internet search engines were also performed through to October 1, 2015. RESULTS: The initial database searches identified 46 devices and the Internet search engines identified 100 devices yielding a total of 146 technologies. Of these, 64 were further removed because they were currently unavailable for purchase or there was no evidence that they were designed for, had been used in, or could readily be modified for self-monitoring purposes. The remaining 82 technologies were included in this review (73 devices self-monitored PA, 9 devices self-monitored sedentary time). Of the 82 devices included, this review identified no published articles in which these devices were used for the purpose of self-monitoring PA and/or sedentary behavior; however, a number of technologies were found via Internet searches that matched the criteria for self-monitoring and provided immediate feedback on PA (ActiGraph Link, Microsoft Band, and Garmin Vivofit) and sedentary time (activPAL VT, the Lumo Back, and Darma). CONCLUSIONS: There are a large number of devices that self-monitor PA; however, there is a greater need for the development of tools to self-monitor sedentary time. The novelty of these devices means they have yet to be used in behavior change interventions, although the growing field of wearable technology may facilitate this to change.

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Does Non-Running Physical Activity Contribute to the Risk of Developing a Running Related Overuse Injury? (2016)

Medicine & Science in Sports & Exercise

Authors: Gruber, A.H., Murphy, S.P., Vollmar, J.E., Kennedy-Armbruster, C. and Chomistek, A.K.

Abstract

Running related overuse injury (RROI) affects a significant proportion of runners annually. To date, only running mileage has been considered when quantifying the amount of loading that may elicit tissue micro-damage and injury, while the loading that occurs from activities of daily living and non-running physical activity has been ignored. By ignoring non-running physical activity (PA), we may be severely underestimating the amount of loading that leads to RROI. PURPOSE: To determine the role of daily non-running PA on the risk of RROI development among recreational and competitive runners. METHODS: As part of a larger prospective running injury pilot study, 50 recreational and competitive male and female runners will be enrolled and complete questionnaires regarding running history, injury history, and all forms of non-running daily PA. Participants will receive a FitBit Charge activity monitor to track PA for 24 hrs/day over 12 months. To date, questionnaires and a typical running gait analysis had been completed by 21 participants (9 male, 12 female; 27.5±6.3 years; BMI = 22.6±2.0 kg/mˆ2). RESULTS: Participants had mean±SD running experience of 8.6±5.6 years and run 24.1±15.2 mi/wk. Among n = 21 participants, RROI occurred within the past year in n = 4, within the past two years in n = 11, and in their lifetime in n = 16. Current mi/wk was 54% greater in those that had sustained a RROI in their lifetime compared with those that had not (No RROI = 15.3±4.5 mi/wk; Yes RROI 26.9±16.4 mi/wk, P=0.02). Total PA was not different between those who had and had not sustained a RROI in their lifetime or in the past 1-2 years (Ptextgreater0.05). Non-running PA was greater in those that did not sustain a RROI in each time period, but the differences were not significant with this initial sample size (No RROI vs Yes RROI: lifetime 11.8±8.3 vs 7.1±7.2 hrs/wk, Ptextgreater0.05; 1 yr: 8.7±8.2 vs 6.1±3.9 hrs/wk, Ptextgreater0.05; 2 yr: 9.2±8.6 vs 7.3±6.8 hrs/wk, Ptextgreater0.05). CONCLUSIONS: Results from the first 21 participants enrolled in this study support previous reports that running mi/wk may increase RROI risk. Given that total PA was the same between injured and non-injured runners in this sample, more hrs/wk spent in non-running PA vs running PA may reduce RROI risk. Continuous monitoring of PA collected in this 12 month study will provide evidence to support or reject this hypothesis.

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Effect of affordable technology on physical activity levels and mobility outcomes in rehabilitation: a protocol for the Activity and MObility UsiNg Technology (AMOUNT) rehabilitation trial. (2016)

BMJ Open

Authors: Hassett, L., van den Berg, M., Lindley, R.I., Crotty, M., McCluskey, A., van der Ploeg, H.P., Smith, S.T., Schurr, K., Killington, M., Bongers, B., Howard, K., Heritier, S., Togher, L., Hackett, M., Treacy, D., Dorsch, S., Wong, S., Scrivener, K., Chagpar, S., Weber, H., Pearson, R. and Sherrington, C.

Abstract

NTRODUCTION People with mobility limitations can benefit from rehabilitation programmes that provide a high dose of exercise. However, since providing a high dose of exercise is logistically challenging and resource-intensive, people in rehabilitation spend most of the day inactive. This trial aims to evaluate the effect of the addition of affordable technology to usual care on physical activity and mobility in people with mobility limitations admitted to inpatient aged and neurological rehabilitation units compared to usual care alone. METHODS AND ANALYSIS A pragmatic, assessor blinded, parallel-group randomised trial recruiting 300 consenting rehabilitation patients with reduced mobility will be conducted. Participants will be individually randomised to intervention or control groups. The intervention group will receive technology-based exercise to target mobility and physical activity problems for 6 months. The technology will include the use of video and computer games/exercises and tablet applications as well as activity monitors. The control group will not receive any additional intervention and both groups will receive usual inpatient and outpatient rehabilitation care over the 6-month study period. The coprimary outcomes will be objectively assessed physical activity (proportion of the day spent upright) and mobility (Short Physical Performance Battery) at 6 months after randomisation. Secondary outcomes will include: self-reported and objectively assessed physical activity, mobility, cognition, activity performance and participation, utility-based quality of life, balance confidence, technology self-efficacy, falls and service utilisation. Linear models will assess the effect of group allocation for each continuously scored outcome measure with baseline scores entered as a covariate. Fall rates between groups will be compared using negative binomial regression. Primary analyses will be preplanned, conducted while masked to group allocation and use an intention-to-treat approach.

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Effectiveness of activity trackers with and without incentives to increase physical activity (TRIPPA): a randomised controlled trial (2016)

The Lancet Diabetes & Endocrinology

Authors: Finkelstein, E.A., Haaland, B.A., Bilger, M., Sahasranaman, A., Sloan, R.A., Nang, E.E.K. and Evenson, K.R.

Abstract

Background: Despite the increasing popularity of activity trackers, little evidence exists that they can improve health outcomes. We aimed to investigate whether use of activity trackers, alone or in combination with cash incentives or charitable donations, lead to increases in physical activity and improvements in health outcomes. Methods: In this randomised controlled trial, employees from 13 organisations in Singapore were randomly assigned (1:1:1:1) with a computer generated assignment schedule to control (no tracker or incentives), Fitbit Zip activity tracker, tracker plus charity incentives, or tracker plus cash incentives. Participants had to be English speaking, full-time employees, aged 21–65 years, able to walk at least ten steps continuously, and non-pregnant. Incentives were tied to weekly steps, and the primary outcome, moderate-to-vigorous physical activity (MVPA) bout min per week, was measured via a sealed accelerometer and assessed on an intention-to-treat basis at 6 months (end of intervention) and 12 months (after a 6 month post-intervention follow-up period). Other outcome measures included steps, participants meeting 70?000 steps per week target, and health-related outcomes including weight, blood pressure, and quality-of-life measures. This trial is registered at ClinicalTrials.gov, number NCT01855776. Findings: Between June 13, 2013, and Aug 15, 2014, 800 participants were recruited and randomly assigned to the control (n=201), Fitbit (n=203), charity (n=199), and cash (n=197) groups. At 6 months, compared with control, the cash group logged an additional 29 MVPA bout min per week (95% CI 10–47; p=0·0024) and the charity group an additional 21 MVPA bout min per week (2–39; p=0·0310); the difference between Fitbit only and control was not significant (16 MVPA bout min per week [–2 to 35; p=0·0854]). Increases in MVPA bout min per week in the cash and charity groups were not significantly greater than that of the Fitbit group. At 12 months, the Fitbit group logged an additional 37 MVPA bout min per week (19–56; p=0·0001) and the charity group an additional 32 MVPA bout min per week (12–51; p=0·0013) compared with control; the difference between cash and control was not significant (15 MVPA bout min per week [–5 to 34; p=0·1363]). A decrease in physical activity of -23 MVPA bout min per week (95% CI -42 to -4; p=0·0184) was seen when comparing the cash group with the Fitbit group. There were no improvements in any health outcomes (weight, blood pressure, etc) at either assessment. Interpretation: The cash incentive was most effective at increasing MVPA bout min per week at 6 months, but this effect was not sustained 6 months after the incentives were discontinued. At 12 months, the activity tracker with or without charity incentives were effective at stemming the reduction in MVPA bout min per week seen in the control group, but we identified no evidence of improvements in health outcomes, either with or without incentives, calling into question the value of these devices for health promotion. Although other incentive strategies might generate greater increases in step activity and improvements in health outcomes, incentives would probably need to be in place long term to avoid any potential decrease in physical activity resulting from discontinuation.

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Effects of an mHealth Adaptive Intervention on Vascular Health and Cardiorespiratory Fitness (2016)

Circulation

Authors: Jarrett, C.L., Tucker, W.J., Hurley, J.C., Todd, M., Bhuiyan, N., Fernandez, J.A., Adams, M.A. and Angadi, S.S.

Abstract

ntroduction: Behavioral economics-based interventions for increasing steps/day may improve cardiorespiratory fitness (CRF; Peak O2 uptake - VO2peak), central/aortic blood pressure, and vascular stiffness. The purpose of this study was to examine the effects of adaptive (Ad) physical activity (PA) goals (daily step goals based on prior 10-day window and a percentile algorithm) vs. static (St) PA goals (10,000 steps/day) combined with either immediate (Im) financial micro-incentives or delayed (De) incentives (Groups: Ad+Im; Ad+De; St+Im; St+De) on VO2peak, blood pressure and vascular stiffness. We hypothesized that participants randomized to adaptive goals with immediate reinforcement (Ad+Im) would have greater improvements in cardiovascular health measures than participants assigned to static goals and/or delayed reinforcement conditions (active controls). Methods: Inactive adults (Age = 41.8 ± 6.7yrs; BMI = 34.5 ± 6 kg/m2) were randomized to an adaptive/static goal intervention with either immediate micro-incentives or delayed incentives in a 4-month factorial RCT to improve steps/day. Additionally, all four groups received daily text-message prompts-to-action and Fitbit ZipTM activity monitors. Pre and post VO2peak (n=81) were estimated using a modified, sub-maximal Balke treadmill protocol while central blood pressures, augmentation index (Aix@75) (n=70) and carotid-femoral pulse wave velocity (cf-PWV) (n=64) were assessed with the Sphygmocor XCELTM device. Between- and within-group differences were examined using linear mixed models, adjusted for sex, age, race/ethnicity, and smoking history. Alpha was set at 0.05, and data are presented as estimated marginal means ± standard errors (SE). Results: All groups improved from pre to post, but we found no significant between-group differences in the degree of improvement. Across all groups, we found the following: VO2peak and all vascular markers improved significantly pre to post intervention (ptextless0.05). VO2peak improved by ˜5% (pre = 24.9 ± 0.65 vs. post = 26.3 ± 0.66 ml/kg/min). Central systolic blood pressures (cSBP) decreased (cSBP pre = 117.5 ± 2.1 vs. post = 113.1 ± 2.2 mmHg). Cf-PWV (pre = 7.5 ± 0.18 vs. post = 7.3 ± 0.18 m/sec) and AIX@75 (pre =14.1 ± 2.2 vs. post = 11.4 ± 2.2) decreased. Conclusion: Cardiorespiratory fitness and markers of vascular health improved when participants were simply provided a Fitbit and prompted daily to be more physically active, regardless of incentive or goal-setting approach. Implications for designing behavioral interventions for cardiovascular risk reduction will be discussed.

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Effects of Charitable Versus Monetary Incentives on the Acceptance of and Adherence to a Pedometer-Based Health Intervention: Study Protocol and Baseline Characteristics of a Cluster-Randomized Controlled Trial (2016)

JMIR Research Protocols

Authors: Kowatsch, T., Kramer, J.-N., Kehr, F., Wahle, F., Elser, N. and Fleisch, E.

Abstract

Background: Research has so far benefited from the use of pedometers in physical activity interventions. However, when public health institutions (eg, insurance companies) implement pedometer-based interventions in practice, people may refrain from participating due to privacy concerns. This might greatly limit the applicability of such interventions. Financial incentives have been successfully used to influence both health behavior and privacy concerns, and may thus have a beneficial effect on the acceptance of pedometer-based interventions. Objective: This paper presents the design and baseline characteristics of a cluster-randomized controlled trial that seeks to examine the effect of financial incentives on the acceptance of and adherence to a pedometer-based physical activity intervention offered by a health insurance company. Methods: More than 18,000 customers of a large Swiss health insurance company were allocated to a financial incentive, a charitable incentive, or a control group and invited to participate in a health prevention program. Participants used a pedometer to track their daily physical activity over the course of 6 months. A Web-based questionnaire was administered at the beginning and at the end of the intervention and additional data was provided by the insurance company. The primary outcome of the study will be the participation rate, secondary outcomes will be adherence to the prevention program, physical activity, and health status of the participants among others. Results: Baseline characteristics indicate that residence of participants, baseline physical activity, and subjective health should be used as covariates in the statistical analysis of the secondary outcomes of the study. Conclusions: This is the first study in western cultures testing the effectiveness of financial incentives with regard to a pedometer-based health intervention offered by a large health insurer to their customers. Given that the incentives prove to be effective, this study provides the basis for powerful health prevention programs of public health institutions that are easy to implement and can reach large numbers of people in need.

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Effects of Playing a Serious Computer Game on Body Mass Index and Nutrition Knowledge in Women (2016)

JMIR Serious Games

Authors: Shiyko, M., Hallinan, S., Seif El-Nasr, M., Subramanian, S. and Castaneda-Sceppa, C.

Abstract

Background: Obesity and weight gain is a critical public health concern. Serious digital games are gaining popularity in the context of health interventions. They use persuasive and fun design features to engage users in health-related behaviors in a non-game context. As a young field, research about effectiveness and acceptability of such games for weight loss is sparse. Objective: The goal of this study was to evaluate real-world play patterns of SpaPlay and its impact on body mass index (BMI) and nutritional knowledge. SpaPlay is a computer game designed to help women adopt healthier dietary and exercise behaviors, developed based on Self-Determination theory and the Player Experience of Need Satisfaction (PENS) model. Progress in the game is tied to real-life activities (e.g., eating a healthy snack, taking a flight of stairs). Methods: We recruited 47 women to partake in a within-subject 90-day longitudinal study, with assessments taken at baseline, 1-, 2-, and 3- months. Women were on average, 29.8 years old (±7.3), highly educated (80.9% had BA or higher), 39% non-White, baseline BMI 26.98 (±5.6), who reported at least contemplating making changes in their diet and exercise routine based on the Stages of Change Model. We computed 9 indices from game utilization data to evaluate game play. We used general linear models to examine inter-individual differences between levels of play, and multilevel models to assess temporal changes in BMI and nutritional knowledge. Results: Patterns of game play were mixed. Participants who reported being in the preparation or action stages of behavior change exhibited more days of play and more play regularity compared to those who were in the contemplation stage. Additionally, women who reported playing video games 1-2 hours per session demonstrated more sparse game play. Brief activities, such as one-time actions related to physical activity or healthy food, were preferred over activities that require a longer commitment (e.g., taking stairs every day for a week). BMI decreased significantly (P<.001) from baseline to 3-month follow-up, yielding a large effect size of 1.28. Nutritional knowledge increased significantly (P<.001) from first to third month follow-ups, with an effect size of .86. The degree of change in both outcomes was related to game play, baseline readiness to change, and the extent of video game play in general. Conclusions: This work demonstrates initial evidence of success for using a serious game as an intervention for health behavior change in real world settings. Our findings also highlight the need to understand not only game effectiveness but also inter-individual differences. Individualizing content and the intervention medium appears to be necessary for a more personalized and long-lasting impact.

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Efficacy, feasibility, and acceptability of a novel technology-based intervention to support physical activity in cancer survivors (2016)

Supportive Care in Cancer

Authors: Gell, N.M., Grover, K.W., Humble, M., Sexton, M. and Dittus, K.

Abstract

Purpose: Physical activity is known to minimize the long-term side effects of cancer treatment. Yet, rates of physical activity participation by cancer survivors are significantly lower compared to the general population. The purpose of this pilot study was to examine the efficacy, feasibility, and acceptability of a technology-based intervention to promote maintenance of physical activity after completing an exercise-based oncology rehabilitation program. Methods: The pre-post 4-week intervention included support delivered through tailored text messages, Fitbit® self-monitoring, and brief health coaching sessions. The primary outcome measure was accelerometer-assessed physical activity levels. Self-efficacy, self-regulation, social support, fatigue, sleep disturbance, depression, and Fitbit® step counts were assessed as secondary outcomes. Results: Twenty-four participants (20 females; mean age = 57.9 years ± 10.4) completed the intervention. Mean daily step counts and weekly minutes of moderate-to-vigorous intensity physical activity were maintained after the intervention, as compared to baseline levels achieved at the end of 12 weeks of exercise-based oncology rehabilitation. Both self-regulation (goal setting, relapse prevention) and fatigue severity increased significantly post intervention as compared to baseline (p = 0.05 and p = 0.02, respectively). Qualitative responses demonstrated overall satisfaction with intervention components. Conclusions: Results demonstrate efficacy of the intervention for maintenance of physical activity levels achieved during exercise-based oncology rehabilitation. Low attrition and high satisfaction provide evidence for both the acceptability and feasibility of the intervention components. Exercise interventions post oncology treatment provide multiple benefits for cancer survivors, yet continued maintenance after program completion is challenging. Technological options offer low-cost, accessible modes to deliver continued monitoring and support beyond traditional facility-based programs.

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Estimating Physical Activity and Sedentary Behavior in a Free-Living Context: A Pragmatic Comparison of Consumer-Based Activity Trackers and ActiGraph Accelerometry (2016)

Journal of Medical Internet Research

Authors: Gomersall, S.R., Ng, N., Burton, N.W., Pavey, T.G., Gilson, N.D. and Brown, W.J.

Abstract

Background: Activity trackers are increasingly popular with both consumers and researchers for monitoring activity and for promoting positive behavior change. However, there is a lack of research investigating the performance of these devices in free-living contexts, for which findings are likely to vary from studies conducted in well-controlled laboratory settings. Objective: The aim was to compare Fitbit One and Jawbone UP estimates of steps, moderate-to-vigorous physical activity (MVPA), and sedentary behavior with data from the ActiGraph GT3X+ accelerometer in a free-living context. Methods: Thirty-two participants were recruited using convenience sampling; 29 provided valid data for this study (female: 90%, 26/29; age: mean 39.6, SD 11.0 years). On two occasions for 7 days each, participants wore an ActiGraph GT3X+ accelerometer on their right hip and either a hip-worn Fitbit One (n=14) or wrist-worn Jawbone UP (n=15) activity tracker. Daily estimates of steps and very active minutes were derived from the Fitbit One (n=135 days) and steps, active time, and longest idle time from the Jawbone UP (n=154 days). Daily estimates of steps, MVPA, and longest sedentary bout were derived from the corresponding days of ActiGraph data. Correlation coefficients and Bland-Altman plots with examination of systematic bias were used to assess convergent validity and agreement between the devices and the ActiGraph. Cohen's kappa was used to assess the agreement between each device and the ActiGraph for classification of active versus inactive (=10,000 steps per day and =30 min/day of MVPA) comparable with public health guidelines. Results: Correlations with ActiGraph estimates of steps and MVPA ranged between .72 and .90 for Fitbit One and .56 and .75 for Jawbone UP. Compared with ActiGraph estimates, both devices overestimated daily steps by 8% (Fitbit One) and 14% (Jawbone UP). However, mean differences were larger for daily MVPA (Fitbit One: underestimated by 46%; Jawbone UP: overestimated by 50%). There was systematic bias across all outcomes for both devices. Correlations with ActiGraph data for longest idle time (Jawbone UP) ranged from .08 to .19. Agreement for classifying days as active or inactive using the =10,000 steps/day criterion was substantial (Fitbit One: ?=.68; Jawbone UP: ?=.52) and slight-fair using the criterion of =30 min/day of MVPA (Fitbit One: ?=.40; Jawbone UP: ?=.14). Conclusions: There was moderate-strong agreement between the ActiGraph and both Fitbit One and Jawbone UP for the estimation of daily steps. However, due to modest accuracy and systematic bias, they are better suited for consumer-based self-monitoring (eg, for the public consumer or in behavior change interventions) rather than to evaluate research outcomes. The outcomes that relate to health-enhancing MVPA (eg, “very active minutes” for Fitbit One or “active time” for Jawbone UP) and sedentary behavior (“idle time” for Jawbone UP) should be used with caution by consumers and researchers alike.

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Evaluation of pedometry as a patient-centered outcome in patients undergoing hematopoietic cell transplant (HCT): a comparison of pedometry and patient reports of symptoms, health, and quality of life (2016)

Quality of Life Research

Authors: Bennett, A.V., Reeve, B.B., Basch, E.M., Mitchell, S.A., Meeneghan, M., Battaglini, C.L., Smith-Ryan, A.E., Phillips, B., Shea, T.C. and Wood, W.A.

Abstract

Aims: We evaluated pedometry as a novel patient-centered outcome because it enables passive continuous assessment of activity and may provide information about the consequences of symptomatic toxicity complementary to self-report. Methods: Adult patients undergoing hematopoietic cell transplant (HCT) wore pedometers and completed PRO assessments during transplant hospitalization (4 weeks) and 4 weeks post-discharge. Patient reports of symptomatic treatment toxicities (single items from PRO-CTCAE, http://healthcaredelivery.cancer.gov/pro-ctcae) and symptoms, physical health, mental health, and quality of life (PROMIS® Global-10, http://nih.promis.org), assessed weekly with 7-day recall on Likert scales, were compared individually with pedometry data, summarized as average daily steps per week, using linear mixed models. Results: Thirty-two patients [mean age 55 (SD = 14), 63 % male, 84 % white, 56 % autologous, 43 % allogeneic] completed a mean 4.6 (SD = 1.5, range 1–8) evaluable assessments. Regression model coefficients (ß) indicated within-person decrements in average daily steps were associated with increases in pain (ß = -852; 852 fewer steps per unit increase in pain score, p < 0.001), fatigue (ß = -886, p < 0.001), vomiting (ß = -518, p < 0.01), shaking/chills (ß = -587, p < 0.01), diarrhea (ß = -719, p < 0.001), shortness of breath (ß = -1018, p < 0.05), reduction in carrying out social activities (ß = 705, p < 0.01) or physical activities (ß = 618, p < 0.01), and global physical health (ß = 101, p < 0.001), but not global mental health or quality of life. Conclusions: In this small sample of HCT recipients, more severe symptoms, impaired physical health, and restrictions in the performance of usual daily activities were associated with statistically significant decrements in objectively measured daily steps. Pedometry may be a valuable outcome measure and validation anchor in clinical research.

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Evidence of Convergent Validity for Measuring Free-Living Walking Using Wearable Devices (2016)

Medicine & Science in Sports & Exercise

Authors: Lee, M., Choi, J.-Y., Lee, K., Min, J., Kim, J. and Choi, M.C.

Abstract

PURPOSE: To determine the convergent validity of consumer-based wearable devices for assessing walking during free-living activities. METHODS: A total of 48 healthy adults (10 males, 50.3±10.6 yrs & BMI 24.9±2.5; 38 females, 53.3±7.4 yrs & BMI 24.4±2.9) participated. The consumer-based wearable devices included Actigraph GT3X+(AT), BodyMedia Armband (BM), Fitbit Charge (FC), Fitbit One (FO), Jawbone up (JB), Misfit (MF), and the Nike Fuelband (NF) worn on wrist, waist, or upper arm. The Omron HJ720IT pedometer served as the reference measure. While simultaneously wearing all devices, walking time (6.64±.80min), steps (13.28±1.22), and speed (1.43±.20m/sec) were assessed (10 m walk). Participants also completed selected free-living activities including moving boxes, cleaning desks, mopping, walking up & down stairs, and outdoor walking on hills. On average these activities took 40min to complete. Descriptive statistics, correlation coefficients (r) and paired t-test among the wearable devices and the Omron pedometer were calculated using SPSS 20. RESULTS: It was unable to examine the accuracy of the JB due to constant synchronizing errors. Walking Time, Steps, and Speed showed moderate correlations with the Omron (r = .39, .55, & .43, respectively); but low correlations with wearable devices r = .11 to .23(Time), -.10 to .37(Steps), and -.08 to -.23(Speed). Step counts measured by the devices during free-living were as follows: FC=178±238, NF=1595±156, MF=1628±283, BM=1667±191, FO=1735±174, and AT=1778±180. The Omron (reference) recorded 1749±169 steps. The correlation coefficients between the step counts from the wearable devices and the Omron during free-living were AT=.91, FO=.91, NF =.61, FC=.59, BM=.44, and MF=-.15. All wearable devices showed statistically significant differences when compared to the Omron (t = -2.2 to -14.3, p textless0.05). CONCLUSIONS: : Of the devices examined, AT and FO were the most valid for measuring walking steps during free-living activities. On the other hand, quality control and measurement error associated with JB and MF suggest they should not be used.

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Examining The Validity Of Fitbit Charge HR For Measuring Heart Rate In Free-living Conditions (2016)

Medicine & Science in Sports & Exercise

Authors: Lee, J.-M.M., An, H., Kang, S.-k., Kim, Y. and Dinkel, D.

Abstract

Optical blood flow sensors (i.e. photoplethysmographic techniques) have recently been utilized in wearable activity trackers. The Fitbit Charge HRTM (FBHR) is one of the widely recognized wearable activity trackers that utilizes Fitbit's proprietary PurePulse optical heart rate (HR) technology to automatically measure wrist-based HR. Despite its increasing popularity, however, no study to date has addressed the validity of FBHR for measuring HR in free-living conditions. PURPOSE: The purpose of this study was to examine the validity of FBHR for measuring HR using a chest strap Polar HR monitor (PHR) as a reference measure in free-living conditions. METHODS: Ten healthy college students (8 males; mean age = 26.5 ± 5.4 years; mean body mass index (BMI) = 24.5 ± 3.23 kgtextperiodcenteredm2) participated in the study. The participants were asked to perform normal daily activities for 8 hours in a day while wearing the PHR (model RS400) on their chest and two FBHRs on their dominant and non-dominant wrists, respectively. HR was recorded every minute and the minute-by-minute HR data from each monitor were synchronized by time of day. Pearson correlation was used to examine the linearity of average beats-per-minute (bpm) estimated from FBHRs with respect to the PHR. Mean differences in average bpm between the monitors were examined by a general linear model for repeated measures. Lastly, mean absolute percentage error (MAPE) of minute-by-minute bpm estimated from the FBHRs were calculated against the PHR. RESULTS: Average HRs (mean ± SD) for PHR, FBHR non-dominant, and FBHR dominant were 75.6 ± 18.5 bpm, 72.8 ± 16.7 bpm, and 73.9 ± 17.06 bpm, respectively. Pearson correlation coefficients (r) between the PHR and FBHR non-dominant and dominant were r=.805 and r=.793, respectively. MAPE were 9.17 ± 10.9% for FBHR non-dominant and 9.71 ± 12.4% for FBHR HR dominant. ANOVA and post-hoc analyses with Bonferroni revealed significant differences in estimating HR from FBHR non-dominant wrist (p=.001) and FBHR dominant wrist (p=.001) compared to PHR monitor. CONCLUSION: The results indicated that the wrist-oriented Fitbit Charge HRTM device does not provide an accurate measurement of HR during free-living condition in this study. However, further research is needed to validate these monitors with a larger sample with different population groups.

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Feasibility and Effectiveness of Using Wearable Activity Trackers in Youth: A Systematic Review (2016)

JMIR mHealth and uHealth

Authors: Ridgers, N.D., McNarry, M.A. and Mackintosh, K.A.

Abstract

Background: The proliferation and popularity of wearable activity trackers (eg, Fitbit, Jawbone, Misfit) may present an opportunity to integrate such technology into physical activity interventions. While several systematic reviews have reported intervention effects of using wearable activity trackers on adults' physical activity levels, none to date have focused specifically on children and adolescents. Objective: The aim of this review was to examine the effectiveness of wearable activity trackers as a tool for increasing children's and adolescents' physical activity levels. We also examined the feasibility of using such technology in younger populations (age range 5-19 years). Methods: We conducted a systematic search of 5 electronic databases, reference lists, and personal archives to identify articles published up until August 2016 that met the inclusion criteria. Articles were included if they (1) specifically examined the use of a wearable device within an intervention or a feasibility study; (2) included participants aged 5-19 years old; (3) had a measure of physical activity as an outcome variable for intervention studies; (4) reported process data concerning the feasibility of the device in feasibility studies; and (5) were published in English. Data were analyzed in August 2016. Results: In total, we identified and analyzed 5 studies (3 intervention, 2 feasibility). Intervention delivery ranged from 19 days to 3 months, with only 1 study using a randomized controlled trial design. Wearable activity trackers were typically combined with other intervention approaches such as goal setting and researcher feedback. While intervention effects were generally positive, the reported differences were largely nonsignificant. The feasibility studies indicated that monitor comfort and design and feedback features were important factors to children and adolescents. Conclusions: There is a paucity of research concerning the effectiveness and feasibility of wearable activity trackers as a tool for increasing children's and adolescents' physical activity levels. While there are some preliminary data to suggest these devices may have the potential to increase activity levels through self-monitoring and goal setting in the short term, more research is needed to establish longer-term effects on behavior.

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Fitbit Provides Valid Measures of Sedentary and Physical Activity in Preschool Children (2016)

Circulation

Authors: Byun, W., Barry, A., Lee, J.-M. and Kim, Y.

Abstract

Introduction: Both monitoring and promoting PA in children, two important areas in epidemiologic research, require the use of accurate and feasible measurement tools. The Fitbit activity monitor is one of the most widely commercialized, consumer-based activity monitors and its validity and reliability has been determined in adults; however, little research has determined the validity of Fitbit activity monitor in measuring sedentary behavior and PA in preschool-age children. Hypothesis: We hypothesized that, when comparing to the direct observation (DO), the Fitbit Flex (FF) activity monitor would accurately measure the time spent in sedentary, moderate-to-vigorous PA (MVPA), and Total (light-to-vigorous) PA in preschool-age children. Methods: A total of 28 preschool age children (Female: 46%, Age: 4.6 ± 1.0 yrs, BMI: 16.4 ± 1.5 kg·m2) wore the FF (on the wrist) and were directly observed while performing a set of unstructured and structured activities with varying intensity levels such as watching TV, drawing, playing with toys, playing soccer, and shooting basket. Breath-by-breath oxygen consumption were also measured using Oxycon Mobile indirect calorimetry (OM). Data from the FF (PA counts) and the OM (VO2 ml·kg·min-1) were summarized in terms of minute-by-minute basis. The validity of FF for measuring the time spent in sedentary behavior, MVPA, and Total PA against DO was examined using three ways: (1) Pearson correlation examining the relatively agreement between FF and DO; (2) Mean absolute percent error (MAPE) examining the measurement errors of FF; and (3) One-sided equivalence test examining the absolute agreement between FF and DO by comparing the 90% confidence intervals (CI) of the estimates from the FF with the respective equivalence zone (EZ; ± 10% of the mean estimates from the DO). Results: On average, oxygen consumptions for sedentary, light, MVPA were 9.0 ± 1.6, 14.9 ± 3.9, 23.5 ± 5.5, and 33.8 ± 5.6 ml·kg·min-1, respectively. Correlations between FF and DO were consistently high for sedentary (r = 0.81, P <.001), MVPA (r = 0.62, P <.001), and Total PA (r = 0.81, P <.001). MAPEs were 8.2%, 21.1%, and 8.2% for sedentary, MVPA, and Total PA, respectively. The estimates from the FF were not significantly equivalent to those from the DO; sedentary (FF: Mean (M) = 7.8 min, 90% CI: 7.3 - 8.3 min vs. DO: M = 6 min, EZ: 5.4 - 6.6 min), MVPA (FF: M = 7.2 min, 90% CI: 6.2 - 8.2 min vs. DO: M = 12 min, EZ: 10.8 - 13.2 min), and Total PA (FF: M = 14.0 min, 90% CI: 13.6 - 14.4 min vs. DO: M = 16 min, EZ: 14.4 - 17.6 min). Conclusions: The validity of the FF was supported by the consistently high correlations with the criterion measure. However, inconsistent results from equivalence testing warrants subsequent assessment of the validity of the FF as it has a high potential for replacing research-based PA monitors in preschool-age children.

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Health coaching and pedometers to enhance physical activity and prevent falls in community-dwelling people aged 60 years and over: study protocol for the Coaching for Healthy AGEing (CHAnGE) cluster randomised controlled trial (2016)

BMJ Open

Authors: Tiedemann, A., Rissel, C., Howard, K., Tong, A., Merom, D., Smith, S., Wickham, J., Bauman, A., Lord, S.R., Vogler, C., Lindley, R.I., Simpson, J.M., Allman-Farinelli, M. and Sherrington, C.

Abstract

INTRODUCTION Prevention of falls and promotion of physical activity are essential for maximising well-being in older age. However, there is evidence that promoting physical activity among older people without providing fall prevention advice may increase fall rates. This trial aims to establish the impact of a physical activity and fall prevention programme compared with a healthy eating programme on physical activity and falls among people aged 60+ years. METHODS AND ANALYSIS This cluster randomised controlled trial will involve 60 groups of community-dwelling people aged 60+ years. Participating groups will be randomised to: (1) a physical activity and fall prevention intervention (30 groups), involving written information, fall risk assessment and prevention advice, a pedometer-based physical activity tracker and telephone-based health coaching; or (2) a healthy eating intervention (30 groups) involving written information and telephone-based dietary coaching. Primary outcomes will be objectively measured physical activity at 12 months post-randomisation and self-reported falls throughout the 12-month trial period. Secondary outcomes include: the proportion of fallers, the proportion of people meeting the Australian physical activity guidelines, body mass index, eating habits, mobility goal attainment, mobility-related confidence, quality of life, fear of falling, risk-taking behaviour, mood, well-being, self-reported physical activity, disability, and health and community service use. The between-group difference in the number of falls per person-year will be analysed using negative binomial regression models. For the continuously scored primary and secondary outcome measures, linear regression adjusted for corresponding baseline scores will assess the effect of group allocation. Analyses will be preplanned, conducted while masked to group allocation, will take into account cluster randomisation, and will use an intention-to-treat approach.

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Impact of Digital Health Methods for Weight Management on Atherosclerotic Cardiovascular Disease Risk in “at-risk” Women (2016)

Canadian Journal of Cardiology

Authors: Ball, C., Carter, K., Yeung, C., Abdelmoneim, S., Bauman, J., Huang, R., Mankad, R., Iftikar, S., Jain, S., Lopez-Jimenez, F. and Mulvagh, S.

Abstract

BACKGROUND: The LEARN (Lifestyle-Exercise-AttitudesRelationships-Nutrition) program is an established weight loss program that may have positive impact on atherosclerotic cardiovascular disease (ASCVD) risk, but can be limited in application due to requirement of weekly meetings. We examine the changes in lipid profiles and 10-year ASCVD risk score in a prospective study of a novel format of the LEARN program utilizing digital health (DH) tools compared to a traditional meeting format. METHODS: Eighty-nine women (age: 55.59.3 years, BMI: 34.35.2 kg/m2) with 2 CVD risk factors were prospectively randomized to a 3-month duration LEARN program delivered either through a DH approach using internet-based podcasts with an online interactive message board and FitBit (San Francisco, CA) activity trackers (DH group), or traditional weekly meetings (Control group¼C). Lipids (total cholesterol, LDL, HDL, triglycerides, NMR lipoprofile patterns) were analyzed at baseline and 3 months (LabCorp, Burlington, NC). Statistical analysis was performed (ANOVA and matched pairs). S9 CWHHS Abstracts RESULTS: Fifty-eight women (DH¼30, C¼28) completed baseline and 3-month testing. At baseline there were no differences in hypertension (52%), fasting glucose impairment (29%), or smoking history (31%). However, DH women were younger than C (52 vs 59 years, p¼0.007), and had lower 10-year ASCVD risk scores (6.25.1% vs 3.73.7, p¼0.042). Upon LEARN program completion, mean weight loss (2.94.1 kg), was similar in both groups (p¼0.773), and there was no change in SBP or ASCVD risk scores for either group. Lipid profile parameters showed favorable trends for both groups. A significant reduction was seen only for triglycerides in DH group (11940 at baseline vs 9826 at 3 months, p¼0.0009). Similarly, NMR lipoprofile analysis showed a significant reduction in large VLDL particles for DH group (5.33.6 at baseline vs 3.42.2 at 3 months, p¼0.0188). CONCLUSION: In women with ASCVD risk completing a 3 month LEARN program, Digital Health administration resulted in similar decreases in weight loss as traditional methods, but more favorable cardiometabolic results. This study demonstrates the feasibility and effectiveness of novel Digital Health methods for a weight loss program with immediate beneficial impact on weight loss and triglyceride levels. 19 C

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Individual Differences in Diurnal Preference and Time-of-Exercise Interact to Predict Exercise Frequency (2016)

Annals of Behavioral Medicine

Authors: Hisler, G.C., Phillips, A.L. and Krizan, Z.

Abstract

Background Diurnal preference (and chronotype more generally) has been implicated in exercise behavior, but this relation has not been examined using objective exercise measurements nor have potential psychosocial mediators been examined. Furthermore, time-of-day often moderates diurnal preference’s influence on outcomes, and it is unknown whether time-of-exercise may influence the relation between chronotype and exercise frequency. Purpose: The current study examined whether individual differences in diurnal preference (“morningness-eveningness”) predict unique variance in exercise frequency and if commonly studied psychosocial variables mediate this relation (i.e., behavioral intentions, internal exercise control, external exercise control, and conscientiousness). Moreover, the study sought to test whether individuals’ typical time-of-exercise moderated the impact of diurnal preference on exercise frequency. Methods: One hundred twelve healthy adults (mean age = 25.4; SD = 11.6 years) completed baseline demographics and then wore Fitbit Zips® for 4 weeks to objectively measure exercise frequency and typical time-of-exercise. At the end of the study, participants also self-reported recent exercise. Results: Diurnal preference predicted both self-reported exercise and Fitbit-recorded exercise frequency. When evaluating mediators, only conscientiousness emerged as a partial mediator of the relation between diurnal preference and self-reported exercise. In addition, time-of-exercise moderated diurnal preference’s relation to both self-reported exercise and Fitbit-recorded exercise frequency such that diurnal preference predicted higher exercise frequency when exercise occurred at a time that was congruent with one’s diurnal preference. Conclusion: Based on these findings, diurnal preference is valuable, above and beyond other psychological constructs, in predicting exercise frequency and represents an important variable to incorporate into interventions seeking to increase exercise.

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Integrating Mobile health and Physical Activity to reduce the burden of Chronic low back pain Trial (IMPACT): a pilot trial protocol (2016)

BMC Musculoskeletal Disorders

Authors: Amorim, A.B., Pappas, E., Simic, M., Ferreira, M.L., Tiedemann, A., Jennings, M. and Ferreira, P.H.

Abstract

It is well recognised that low back pain is a significant public health problem and engagement in moderate levels of physical activity is associated with positive outcomes. Conservative active care, such as exercise, is effective in reducing pain and disability associated with chronic low back pain. However, a rapid decline in clinical outcomes is commonly seen after discharge from treatment. We will conduct a randomised controlled trial to investigate the effectiveness of a mobile health supported physical activity intervention (compared to standard care) in care-seeking, pain and disability in people with chronic low back pain after discharge from treatment. We will recruit 68 patients with chronic low back pain following discharge from an outpatient hospital program, who will be randomly allocated to the physical activity intervention (n?=?34) or the standard care group (n?=?34) and monitored for 6 months. The physical activity intervention will involve a physical activity advice booklet, a face-to-face health coaching session and 12 fortnightly follow-up telephone-based health coaching sessions. This intervention will be supported by provision of a specifically designed web app and a physical activity monitoring device (FitBit). The standard care group will receive the physical activity advice booklet only. This pilot trial will investigate a new model to prevent clinical decline in people following conservative treatment for chronic low back pain. If proven to be effective, this approach will constitute a major advance in the management of low back pain. Chronic patients who experience recurrent pain and disability after treatment are prone to seek additional care in the form of physiotherapy, medication, emergency department attendance, specialist consultation or spinal surgery. This model aims to maintain functional levels and reduce care-seeking empowering patients to self-manage their low back pain by offering them a contemporary patient-centered physical activity program with the support of mobile health technology. The outcomes of this trial will have immediate implications for clinical practice.

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Is There an Association of Physical Activity with Brain Volume, Behavior, and Day-to-day Functioning? A Cross Sectional Design in Prodromal and Early Huntington Disease. (2016)

PLoS Currents

Authors: Wallace, M., Downing, N., Lourens, S., Mills, J., Kim, J.-I., Long, J., Paulsen, J. and Predict-Hd Investigators And Coordinators Of The Huntington Study Group

Abstract

BACKGROUND: Huntington disease (HD) is a genetic neurodegenerative disease leading to progressive motor, cognitive, and behavioral decline. Subtle changes in these domains are detectable up to 15 years before a definitive motor diagnosis is made. This period, called prodromal HD, provides an opportunity to examine lifestyle behaviors that may impact disease progression. THEORETICAL FRAMEWORK: Physical activity relates to decreased rates of brain atrophy and improved cognitive and day-to-day functioning in Alzheimer disease and healthy aging populations. Previous research has yielded mixed results regarding the impact of physical activity on disease progression in HD and paid little attention to the prodromal phase. METHODS: We conducted analyses of associations among current physical activity level, current and retrospective rate of change for hippocampus and striatum volume, and cognitive, motor, and day-to-day functioning variables. Participants were 48 gene-expanded cases with prodromal and early-diagnosed HD and 27 nongene-expanded control participants. Participants wore Fitbit Ultra activity monitors for three days and completed the self-reported International Physical Activity Questionnaire (IPAQ). Hippocampal and striatal white matter volumes were measured using magnetic resonance imaging. Cognitive tests included the Stroop Color and Word Test, and the Symbol Digit Modalities Test (SDMT). Motor function was assessed using the Unified Huntington's Disease Rating Scale total motor score (TMS). Day-to-day functioning was measured using the World Health Organization Disability Assessment Schedule (WHODAS) version 2.0. RESULTS: Higher Fitbit activity scores were significantly related to better scores on the SDMT and WHODAS in case participants but not in controls. Fitbit activity scores tracked better with TMS scores in the group as a whole, though the association did not reach statistical significance in the case participants. Higher Fitbit activity scores related to less day-to-day functioning decline in retrospective slope analyses. Fitbit activity scores did not differ significantly between cases and controls. CONCLUSIONS: This is the first known study examining the associations between activity level and imaging, motor, cognitive, and day-to-day functioning outcomes in prodromal and early HD. Preliminary results suggest physical activity positively correlates with improved cognitive and day-to-day functioning and possibly motor function in individuals in the prodromal and early phase of the condition.

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Older Adults' Experiences Using a Commercially Available Monitor to Self-Track Their Physical Activity. (2016)

JMIR mHealth and uHealth

Authors: McMahon, S.K., Lewis, B., Oakes, M., Guan, W., Wyman, J.F. and Rothman, A.J.

Abstract

BACKGROUND: Physical activity contributes to older adults' autonomy, mobility, and quality of life as they age, yet fewer than 1 in 5 engage in activities as recommended. Many older adults track their exercise using pencil and paper, or their memory. Commercially available physical activity monitors (PAM) have the potential to facilitate these tracking practices and, in turn, physical activity. An assessment of older adults' long-term experiences with PAM is needed to understand this potential. OBJECTIVE: To assess short and long-term experiences of adults textgreater70 years old using a PAM (Fitbit One) in terms of acceptance, ease-of-use, and usefulness: domains in the technology acceptance model. METHODS: This prospective study included 95 community-dwelling older adults, all of whom received a PAM as part of randomized controlled trial piloting a fall-reducing physical activity promotion intervention. Ten-item surveys were administered 10 weeks and 8 months after the study started. Survey ratings are described and analyzed over time, and compared by sex, education, and age. RESULTS: Participants were mostly women (71/95, 75%), 70 to 96 years old, and had some college education (68/95, 72%). Most participants (86/95, 91%) agreed or strongly agreed that the PAM was easy to use, useful, and acceptable both 10 weeks and 8 months after enrolling in the study. Ratings dropped between these time points in all survey domains: ease-of-use (median difference 0.66 points, P=.001); usefulness (median difference 0.16 points, P=.193); and acceptance (median difference 0.17 points, P=.032). Differences in ratings by sex or educational attainment were not statistically significant at either time point. Most participants 80+ years of age (28/37, 76%) agreed or strongly agreed with survey items at long-term follow-up, however their ratings were significantly lower than participants in younger age groups at both time points. CONCLUSIONS: Study results indicate it is feasible for older adults (70-90+ years of age) to use PAMs when self-tracking their physical activity, and provide a basis for developing recommendations to integrate PAMs into promotional efforts.

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Pedometer use and self-determined motivation for walking in a cardiac telerehabilitation program: a qualitative study (2016)

BMC Sports Science, Medicine and Rehabilitation

Authors: Thorup, C.B., Grønkjær, M., Spindler, H., Andreasen, J.J., Hansen, J., Dinesen, B.I., Nielsen, G. and Sørensen, E.E.

Abstract

Exercise-based cardiac rehabilitation reduces morbidity and mortality. Walking is a convenient activity suitable for people with cardiac disease. Pedometers count steps, measure walking activity and motivate people to increase physical activity. In this study, patients participating in cardiac telerehabilitation were provided with a pedometer to support motivation for physical activity with the purpose of exploring pedometer use and self-determined motivation for walking experienced by patients and health professionals during a cardiac telerehabilitation program. A qualitative research design consisting of observations, individual interviews and patient documents made the basis for a content analysis. Data was analysed deductively using Self Determination Theory as a frame for analysis and discussion, focusing on the psychological needs of autonomy, competence and relatedness. Twelve cardiac patients, 11 health professionals, 6 physiotherapists and 5 registered nurses were included. The pedometer offered independence from standardised rehabilitation since the pedometer supported tailoring, individualised walking activity based on the patient's choice. This led to an increased autonomy. The patients felt consciously aware of health benefits of walking, and the pedometer provided feedback on walking activity leading to an increased competence to achieve goals for steps. Finally, the pedometer supported relatedness with others. The health professionals' surveillance of patients' steps, made the patients feel observed, yet supported, furthermore, their next of kin appeared to be supportive as walking partners. Cardiac patients' motivation for walking was evident due to pedometer use. Even though not all aspects of motivation were autonomous and self determined, the patients felt motivated for walking. The visible steps and continuous monitoring of own walking activity made it possible for each individual patient to choose their desired kind of activity and perform ongoing adjustments of walking activity. The immediate feedback on step activity and the expectations of health benefits resulted in motivation for walking. Finally, pedometer supported walking made surveillance possible, giving the patients a feeling of being looked after and supported. Current study is a part of The Teledi@log project.

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Physical Activity Assessment Between Consumer- and Research-Grade Accelerometers: A Comparative Study in Free-Living Conditions (2016)

JMIR Mhealth Uhealth

Authors: Dominick, M.G., Winfree, N.K., Pohlig, T.R. and Papas, A.M.

Abstract

Background: Wearable activity monitors such as Fitbit enable users to track various attributes of their physical activity (PA) over time and have the potential to be used in research to promote and measure PA behavior. However, the measurement accuracy of Fitbit in absolute free-living conditions is largely unknown. Objective: To examine the measurement congruence between Fitbit Flex and ActiGraph GT3X for quantifying steps, metabolic equivalent tasks (METs), and proportion of time in sedentary activity and light-, moderate-, and vigorous-intensity PA in healthy adults in free-living conditions. Methods: A convenience sample of 19 participants (4 men and 15 women), aged 18-37 years, concurrently wore the Fitbit Flex (wrist) and ActiGraph GT3X (waist) for 1- or 2-week observation periods (n=3 and n=16, respectively) that included self-reported bouts of daily exercise. Data were examined for daily activity, averaged over 14 days and for minutes of reported exercise. Average day-level data included steps, METs, and proportion of time in different intensity levels. Minute-level data included steps, METs, and mean intensity score (0 = sedentary, 3 = vigorous) for overall reported exercise bouts (N=120) and by exercise type (walking, n=16; run or sports, n=44; cardio machine, n=20). Results: Measures of steps were similar between devices for average day- and minute-level observations (all P values > .05). Fitbit significantly overestimated METs for average daily activity, for overall minutes of reported exercise bouts, and for walking and run or sports exercises (mean difference 0.70, 1.80, 3.16, and 2.00 METs, respectively; all P values < .001). For average daily activity, Fitbit significantly underestimated the proportion of time in sedentary and light intensity by 20% and 34 respectively, and overestimated time by 3% in both moderate and vigorous intensity (all P values < .001). Mean intensity scores were not different for overall minutes of exercise or for run or sports and cardio-machine exercises (all P values > .05). Conclusions: Fitbit Flex provides accurate measures of steps for daily activity and minutes of reported exercise, regardless of exercise type. Although the proportion of time in different intensity levels varied between devices, examining the mean intensity score for minute-level bouts across different exercise types enabled interdevice comparisons that revealed similar measures of exercise intensity. Fitbit Flex is shown to have measurement limitations that may affect its potential utility and validity for measuring PA attributes in free-living conditions.

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Piece it Together: Comprehensive Wellness for Teens and Young Adults with Autism and Neurodevelopment Disorders (2016)

Journal of the American Academy of Child & Adolescent Psychiatry

Authors: Spratt, E.G., Flynn, K., Newton, J., Papa, C., Harris, K., Serpe, A., O'Connor, A., Blackmon, L. and Eckert, M.

Abstract

Objectives: Adults and youth with neurodevelopmental disabilities are at increased risk of poor health and obesity as a result of restricted diets, sensory deficits, limited interests, sedentary lifestyles, and medications. Traditional fitness programs do not address socialization and stress reduction strategies that help to promote the likelihood of success with individualized goals for this unique population. Methods: A 6-week summer Piece it Together (PIT) Wellness program (2015) brought together teenagers and young adults with ASD and other mild neurodevelopmental disabilities for a comprehensive wellness program to improve fitness, nutritional habits, and socialization; reduce stress; and encourage individuals to get out of their comfort zone. Classes included opportunities for socialization, fitness activities, group exercise, stress reduction, yoga, mindfulness, and discussion groups on lessons learned. Assessments were completed before and after session for 12 youth (ages 15–27) via Patient Health Questionnaire-9 depression scale, nutrition and lifestyle questionnaires, a self-satisfaction scale, and InBody 570 Analyzer©2014. Results: Appropriate individualized goals were made, new friendships were made, a Facebook group was established, and most became online Fitbit buddies. Average PHQ-9 depression scores decreased from 7.67 to 3.42 (from mild to minimal depression; P = 0.000063). Self-report data revealed more fruits and veggies in the diet at time 2 (t = 2.39, P = 0.038) and modest improvement in self-efficacy-related questions (e.g., I like the way I look/I am a good worker/I have good friends; t = 2.46, P = 0.032). There was a small decrease in body fat, an increase in skeletal muscle mass, and a decrease in carbonated drink consumption (P = not significant). Volunteers have included health professional students, and this has enhanced their knowledge about youth with ASD. Results of the 2016 summer program, which includes twice the number of participants, pre- and post behavioral markers, and biological markers, as well as the success of technology supports, will be shared. Conclusions: Comprehensive wellness programs with a multidisciplinary team can help to address the unique fitness, nutrition, socialization, and stress reduction needs of this population and are needed to help prevent obesity. Components of this program have been individualized and adapted as a model to promote overall brain health.

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Pilot and Feasibility Test of a Mobile Health-Supported Behavioral Counseling Intervention for Weight Management Among Breast Cancer Survivors (2016)

JMIR Cancer

Authors: Quintiliani, L.M., Mann, D.M., Puputti, M., Quinn, E. and Bowen, D.J.

Abstract

Background: Health behavior and weight management interventions for cancer survivors have the potential to prevent future cancer recurrence and improve long-term health; however, their translation can be limited if the intervention is complex and involves high participant burden. Mobile health (mHealth) offers a delivery modality to integrate interventions into daily life routines. Objective: The objective of this study was to evaluate the effects of a one-group trial with a pre-post evaluation design on engagement (use and acceptability), physiological (weight), behavioral (diet and physical activity), and other secondary outcomes. Methods: The 10-week intervention consisted of mHealth components (self-monitoring of selected diet behaviors via daily text messages, wireless devices to automatically track weight and steps) and 4 motivational interviewing–based technology-assisted phone sessions with a nonprofessionally trained counselor. Participants were overweight breast cancer survivors who had completed treatment and owned a smartphone. Weight was measured objectively; diet and physical activity were measured with brief self-reported questionnaires. Results: Ten women participated; they had a mean age of 59 years (SD 6), 50% belonged to a racial or ethnic minority group, 50% had some college or less, and 40% reported using Medicaid health insurance. Engagement was high: out of 70 days in total, the mean number of days recording steps via the wristband pedometer was 64 (SD 7), recording a weight via the scale was 45 (SD 24), and responding to text messages was 60 (SD 13); 100% of participants completed all 4 calls with the counselor. Most (90%) were very likely to participate again and recommend the program to others. Mean weight in pounds decreased (182.5 to 179.1, mean change -3.38 [SD 7.67]), fruit and vegetable daily servings increased (2.89 to 4.42, mean change 1.53 [SD 2.82]), and self-reported moderate physical activity increased in metabolic equivalent of task (MET) minutes per week (2791 to 3336, mean change 545 [SD 1694]). Conclusions: Findings support the conduct of a fully powered trial to evaluate the efficacy of mHealth as a feasible intervention modality for breast cancer survivors. Future research should employ accelerometer-based physical activity assessment and consider development of an all-in-one app to integrate devices, messaging, and educational content and other mHealth approaches to support behavioral counselors conducting weight management interventions.

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Real-World Walking Performance of Individuals with Lower-Limb Amputation Classified as Medicare Functional Classification Level 2 and 3 (2016)

Journal of Prosthetics and Orthotics

Authors: Arch, E.S., Erol, O., Bortz, C., Madden, C., Galbraith, M., Rossi, A., Lewis, J., Higginson, J.S., Buckley, J.M. and Horne, J.

Abstract

Introduction: Lower-limb prostheses are prescribed based on each patient's individual needs. However, there is no standardized method to identify a patient's needs, which results in difficulty and variability in making prosthetic recommendations. Using measures of real-world walking performance in conjunction with clinical measures and the clinician's expertise may be an ideal way to ensure that patients receive the optimal prosthetic treatment. Currently, there is only limited understanding of the relationship among in-clinic performance-based measures, real-world walking performance, and K-level. Therefore, the purpose of this study was to investigate outcomes of in-clinic performance-based evaluations and real-world walking performance measures for individuals with unilateral lower-limb amputation classified as K2 and K3. Materials and Methods: Twenty-seven individuals with unilateral lower-limb amputation classified as K2 or K3 functional levels underwent a clinical assessment visit that included a 10-m walk test and a 6-minute walk test. After the assessment, the individuals were equipped with an activity monitor, which they wore for a 7-day observation period. From these data, participants' self-selected walking speed, total distance walked in 6 minutes, total number of steps taken during the observation period, total number of active minutes during the observation period, and percentage of time spent in low-, moderate-, and high-intensity activity during the observation period were calculated. Results: Individuals classified as K2 had, on average, a significantly slower self-selected walking speed, significantly shorter distance walked in 6 minutes, significantly lower total step count, and a significantly fewer number of active minutes when compared with those classified as K3. Although not significant, trends in activity intensity were seen with individuals classified as K2, spending a larger percentage of time in low-intensity activity and less percentage of time in high-intensity activity when compared with those classified as K3. Conclusions: This study quantified real-world walking performance, in conjunction with in-clinic performance-based data, for individuals classified as K2 and K3 and showed significant differences between the 2 groups. This study is a step forward toward developing an objective and standardized method to classify an individual's functional ability and make prosthetic recommendations.

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Retrofit Weight-Loss Outcomes at 6, 12, and 24 Months and Characteristics of 12-Month High Performers: A Retrospective Analysis (2016)

JMIR mHealth and uHealth

Authors: Painter, S., Ditsch, G., Ahmed, R., Hanson, N.B., Kachin, K. and Berger, J.

Abstract

Background: Obesity is the leading cause of preventable death costing the health care system billions of dollars. Combining self-monitoring technology with personalized behavior change strategies results in clinically significant weight loss. However, there is a lack of real-world outcomes in commercial weight-loss program research. Objective: Retrofit is a personalized weight management and disease-prevention solution. This study aimed to report Retrofit’s weight-loss outcomes at 6, 12, and 24 months and characterize behaviors, age, and sex of high-performing participants who achieved weight loss of 10% or greater at 12 months. Methods: A retrospective analysis was performed from 2011 to 2014 using 2720 participants enrolled in a Retrofit weight-loss program. Participants had a starting body mass index (BMI) of >25 kg/m² and were at least 18 years of age. Weight measurements were assessed at 6, 12, and 24 months in the program to evaluate change in body weight, BMI, and percentage of participants who achieved 5% or greater weight loss. A secondary analysis characterized high-performing participants who lost =10% of their starting weight (n=238). Characterized behaviors were evaluated, including self-monitoring through weigh-ins, number of days wearing an activity tracker, daily step count average, and engagement through coaching conversations via Web-based messages, and number of coaching sessions attended. Results: Average weight loss at 6 months was -5.55% for male and -4.86% for female participants. Male and female participants had an average weight loss of -6.28% and -5.37% at 12 months, respectively. Average weight loss at 24 months was -5.03% and -3.15% for males and females, respectively. Behaviors of high-performing participants were assessed at 12 months. Number of weigh-ins were greater in high-performing male (197.3 times vs 165.4 times, P=.001) and female participants (222 times vs 167 times, P<.001) compared with remaining participants. Total activity tracker days and average steps per day were greater in high-performing females (304.7 vs 266.6 days, P<.001; 8380.9 vs 7059.7 steps, P<.001, respectively) and males (297.1 vs 255.3 days, P<.001; 9099.3 vs 8251.4 steps, P=.008, respectively). High-performing female participants had significantly more coaching conversations via Web-based messages than remaining female participants (341.4 vs 301.1, P=.03), as well as more days with at least one such electronic message (118 vs 108 days, P=.03). High-performing male participants displayed similar behavior. Conclusions: Participants on the Retrofit program lost an average of -5.21% at 6 months, -5.83% at 12 months, and -4.09% at 24 months. High-performing participants show greater adherence to self-monitoring behaviors of weighing in, number of days wearing an activity tracker, and average number of steps per day. Female high performers have higher coaching engagement through conversation days and total number of coaching conversations.

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Shaffer, J.A., Ma, Y., Goldsmith, J., Schwartz, J.E. and Davidson, K.W. Validation of the Fitbit One® for physical activity measurement at an upper torso attachment site (2016)

BMC Research Notes

Authors: Diaz, K.M., Krupka, D.J., Chang, M.J., Shaffer, J.A., Ma, Y., Goldsmith, J., Schwartz, J.E. and Davidson, K.W.

Abstract

Background: The upper torso is recommended as an attachment site for the Fitbit One®, one of the most common wireless physical activity trackers in the consumer market, and could represent a viable alternative to wrist- and hip-attachment sites. The objective of this study was to provide evidence concerning the validity of the Fitbit One® attached to the upper torso for measuring step counts and energy expenditure among female adults. Results: Thirteen female adults completed a four-phase treadmill exercise protocol (1.9, 3.0, 4.0, and 5.2 mph). Participants were fitted with three Fitbit® trackers (two Fitbit One® trackers: one on the upper torso, one on the hip; and a wrist-based Fitbit Flex®). Steps were assessed by manual counting of a video recording. Energy expenditure was measured by gas exchange indirect calorimetry. Concordance correlation coefficients of Fitbit-estimated step counts to observed step counts for the upper torso-attached Fitbit One®, hip-attached Fitbit One® and wrist-attached Fitbit Flex® were 0.98 (95 % CI 0.97–0.99), 0.99 (95 % CI 0.99–0.99), and 0.75 (95 % CI 0.70–0.79), respectively. The percent error for step count estimates from the upper torso attachment site was =3 % for all walking and running speeds. Upper torso step count estimates showed similar accuracy relative to hip attachment of the Fitbit One® and were more accurate than the wrist-based Fitbit Flex®. Similar results were obtained for energy expenditure estimates. Energy expenditure estimates for the upper torso attachment site yielded relative percent errors that ranged from 9 to 19 % and were more accurate than the wrist-based Fitbit Flex®, but less accurate than hip attachment of the Fitbit One®. Conclusions: Our study shows that physical activity measures obtained from the upper torso attachment site of the Fitbit One® are accurate across different walking and running speeds in female adults. The upper torso attachment site of the Fitbit One® outperformed the wrist-based Fitbit Flex® and yielded similar step count estimates to hip-attachment. These data support the upper torso as an alternative attachment site for the Fitbit One®.

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Smartwomantm: Feasibility of a Mobile Application to Improve Cardiovascular Risk Factors in Indigent Diabetic Women (2016)

Circulation: Cardiovascular Quality and Outcomes

Authors: Parashar, S., Williams, O. and Wenger, N.

Abstract

Introduction: Cardiovascular disease disparately affects women with diabetes mellitus. Among women with diabetes, cardiovascular disease prevention, including risk factor monitoring and lifestyle modification is important but underutilized. Mobile health strategies are emerging communication technologies to improve self management and health behaviours. However, the feasibility of mobile health technology (m-health) to enhance health behaviors in an indigent population is unknown. We developed and examined the feasibility of m-health to improve health behaviors and self-management regarding coronary risk factors in indigent women with diabetes. Methods: We developed a smartphone application based on the AHA's “Life's Simple 7” prevention module. Mobile technology was integrated into the overall program, with communication enabled devices (weight scales, glucometers, and sphygmomanometers) synchronized to the smartphone. FitBit was used to monitor activity level. We tested the feasibility of the mobile application in the SMARTWOMANTM project which enrolled women with diabetes, without known CVD at an inner city hospital;,these women had suboptimal access to care, limited transportation and resources, and limited health literacy. Results: Fourteen women, all African-American were enrolled in SMARTWOMANTM (mean age 52 yrs, 86% with hypertension, hypercholesterolemia and obesity). The overall weekly mobile-application reporting was 85% for blood glucose, 83% for daily steps, and 77% for systolic blood pressure. The majority reported the text messages to be useful (92%) and appropriate in frequency (92%). Participants found positive text messages as a strong reinforcement to healthy behaviors. They indicated that study participation increased their motivation in taking charge of their health, and increased understanding of their health condition and self-management. Conclusions: Among indigent African-American women with diabetes and no known CVD, the development and use of mobile health application was feasible and resulted in increased patient satisfaction and positive reinforcement to healthy behaviors.

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Strength in numbers: group fitness programming for children with cerebral palsy (2016)

Developmental Medicine & Child Neurology

Authors: Schmit, J. and Miros, J.

Abstract

Background and Objective(s) Children with cerebral palsy should engage, to the extent they are able, in aerobic, anaerobic, and muscle-strengthening activities (Maltais, 2014). This is a particularly challenging professional charge for physical therapists; across ages and levels of motor function, young people with CP participated in 13% to 53% less habitual physical activity than their peers (Carlon, 2013). These levels of physical activity are approximately 30% lower than public health guidelines and double the maximum recommended sedentary time. Fortunately, studies by Duncan and colleagues (2005) indicate that positive correlates of physical activity in youth do exist. Peers appear to serve as a particularly important social and emotional support for increased physical activity. The purpose of this multicenter pilot effort was to examine the effect of a group fitness program on changes in functional strength, activity, and participation in adolescents with cerebral palsy. Study Design: Cross-sectional, multicenter study. Study Participants & Setting: A total of 8 males and 3 females with Cerebral Palsy (age range 10–22 y; GMFCS levels I–III) who were currently receiving outpatient therapy services for gross motor deficits were recruited for participation in Fitness programming. Materials/Methods: We implemented an 8 week program that was piloted in two outpatient pediatric physical therapy clinics. Participants completed weight training, cardiovascular exercises, stretching, balance, and coordination activities at each 90 minute session. Physical assessments were conducted at the beginning and completion of the program. Outcome measures included Timed Up and Go (TUG), Pediatric Berg Balance Scale (PBS), and 6 Minute Walk Test (6MWT). A subset of participants were equipped with accelerometry in order to monitor physical activity change over the course of the 8 week period. A questionnaire addressing satisfaction with care was also administered to this participant subset. Results: All participants demonstrated improvements in exercise tolerance, including increased repetition and weight, and tolerance to longer periods of cardiovascular activity. Subjects also demonstrated significant improvement on the PBS (p textless 0.05). TUG times reflected a trend toward improvement in functional strength. Submaximal aerobic capacity, measured by the 6MWT, was also enhanced following intervention. Although not statistically significant, TUG and 6MWT changes did exceed thresholds for clinically important differences. Data retrieved from FitBit Charge HR devices was widely variable, but seem to reflect an increase in daily step count over the 8 week period. All of children surveyed at program completion indicated that they enjoyed the group class and that they “got better at working out”; 2/3rds of responders noted that they felt capable of continuing to exercise independently. Conclusions/Significance: We propose that a group-based fitness program may be a pragmatic approach to targeted gains in cardiorespiratory function and strength. Given the critical need for increased physical activity in this at risk-population, we feel encouraged by the feasibility of this initial effort and remarkably positive responses collected in semi-structured interviews following the intervention period. We will continue to study aspects of group-based fitness in future work, including identification of best responders and types of social support that are most associated with improvement, and the inclusion of measures that characterize changes in participation.

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The Electronic CardioMetabolic Program (eCMP) for Patients With Cardiometabolic Risk: A Randomized Controlled Trial. (2016)

Journal of Medical Internet Research

Authors: Azar, K.M., Koliwad, S., Poon, T., Xiao, L., Lv, N., Griggs, R. and Ma, J.

Abstract

BACKGROUND Effective lifestyle interventions targeting high-risk adults that are both practical for use in ambulatory care settings and scalable at a population management level are needed. OBJECTIVE Our aim was to examine the potential effectiveness, feasibility, and acceptability of delivering an evidence-based Electronic Cardio-Metabolic Program (eCMP) for improving health-related quality of life, improving health behaviors, and reducing cardiometabolic risk factors in ambulatory care high-risk adults. METHODS We conducted a randomized, wait-list controlled trial with 74 adults aged =18 years recruited from a large multispecialty health care organization. Inclusion criteria were (1) BMI =35 kg/m(2) and prediabetes, previous gestational diabetes and/or metabolic syndrome, or (2) BMI =30 kg/m(2) and type 2 diabetes and/or cardiovascular disease. Participants had a mean age of 59.7 years (SD 11.2), BMI 37.1 kg/m(2) (SD 5.4) and were 59.5% female, 82.4% white. Participants were randomized to participate in eCMP immediately (n=37) or 3 months later (n=37). eCMP is a 6-month program utilizing video conferencing, online tools, and pre-recorded didactic videos to deliver evidence-based curricula. Blinded outcome assessments were conducted at 3 and 6 months postbaseline. Data were collected and analyzed between 2014 and 2015. The primary outcome was health-related quality of life. Secondary outcomes included biometric cardiometabolic risk factors (eg, body weight), self-reported diet and physical activity, mental health status, retention, session attendance, and participant satisfaction. RESULTS Change in quality of life was not significant in both immediate and delayed participants. Both groups significantly lost weight and reduced waist circumference at 6 months, with some cardiometabolic factors trending accordingly. Significant reduction in self-reported anxiety and perceived stress was seen in the immediate intervention group at 6 months. Retention rate was 93% at 3 months and 86% at 6 months post-baseline. Overall eCMP attendance was high with 59.5-83.8% of immediate and delayed intervention participants attending 50% of the virtual stress management and behavioral lifestyle sessions and 37.8-62.2% attending at least 4 out of 7 in-person physical activity sessions. The intervention received high ratings for satisfaction. CONCLUSIONS The technology-assisted eCMP is a feasible and well-accepted intervention and may significantly decrease cardiometabolic risk among high-risk individuals.

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The monitoring of activity at home after total hip arthroplasty (2016)

The Bone & Joint Journal

Authors: Toogood, P.A., Abdel, M.P., Spear, J.A., Cook, S.M., Cook, D.J. and Taunton, M.J.

Abstract

Aims: Total hip arthroplasty (THA) has well known subjective benefits, but little is known objectively about the recovery of mobility in the early post-operative period. Patients and Methods: A total of 33 patients aged textgreater 60 years who underwent elective primary THA had their activity monitored for 30 days post-operatively using an at-home (Fitbit) ankle accelerometer. Their mean age was 70.7 years (61 to 86); 15 (45.5%) were female. The rate of compliance and the mean level of activity were determined. Comparisons between subgroups based on age, body mass index (BMI), surgical approach, and the destination of the patients when discharged were also performed. Results: The mean compliance over the 30 days was 26.7 days (16 to 30; 89%) of use. The mean number of steps increased from 235 (5 to 1152) to 2563 (87 to 7280) (p textless 0.001) between the first and the 30th post-operative day. Age textless 70 years and an anterior surgical approach were significantly associated with higher levels of activity (1600 to 2400 (p = 0.016 to 0.031) and 1000 to 1800 (p = 0.017 to 0.037) more steps per day, respectively) between the second and the fourth week post-operatively. There was also a trend towards higher levels of activity in those who were discharged to their home rather than to a nursing facility (a mean of 1500 more steps per day, p = 0.02). BMI greater or less than 30 kg/m2 was not predictive of activity (p = 0.45 to 0.98). Conclusion: At-home remote mobility monitoring using existing commercially available technology is feasible in patients who have undergone THA. It showed a clear trend towards increased activity with the passage of time. Additionally, the remote device was able to detect differences in levels of activity clearly between patients in relation to variables of interest including age, BMI, surgical approach, and the destination of the patient at the time of discharge from hospital. Such monitoring may allow for the early identification and targeted intervention in patients who recover slowly.

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These Shoes Are Made for Walking: Sensitivity Performance Evaluation of Commercial Activity Monitors under the Expected Conditions and Circumstances Required to Achieve the International Daily Step Goal of 10,000 Steps. (2016)

PLOS ONE

Authors: O'Connell, S., ÓLaighin, G., Kelly, L., Murphy, E., Beirne, S., Burke, N., Kilgannon, O. and Quinlan, L.R.

Abstract

INTRODUCTION: Physical activity is a vitally important part of a healthy lifestyle, and is of major benefit to both physical and mental health. A daily step count of 10,000 steps is recommended globally to achieve an appropriate level of physical activity. Accurate quantification of physical activity during conditions reflecting those needed to achieve the recommended daily step count of 10,000 steps is essential. As such, we aimed to assess four commercial activity monitors for their sensitivity/accuracy in a prescribed walking route that reflects a range of surfaces that would typically be used to achieve the recommended daily step count, in two types of footwear expected to be used throughout the day when aiming to achieve the recommended daily step count, and in a timeframe required to do so. METHODS: Four commercial activity monitors were worn simultaneously by participants (n = 15) during a prescribed walking route reflective of surfaces typically encountered while achieving the daily recommended 10,000 steps. Activity monitors tested were the Garmin Vivofit ™, New Lifestyles' NL-2000 ™ pedometer, Withings Smart Activity Monitor Tracker (Pulse O2) ™, and Fitbit One ™. RESULTS: All activity monitors tested were accurate in their step detection over the variety of different surfaces tested (natural lawn grass, gravel, ceramic tile, tarmacadam/asphalt, linoleum), when wearing both running shoes and hard-soled dress shoes. CONCLUSION: All activity monitors tested were accurate in their step detection sensitivity and are valid monitors for physical activity quantification over the variety of different surfaces tested, when wearing both running shoes and hard-soled dress shoes, and over a timeframe necessary for accumulating the recommended daily step count of 10,000 steps. However, it is important to consider the accuracy of activity monitors, particularly when physical activity in the form of stepping activities is prescribed as an intervention in the treatment or prevention of a disease state.

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Unravelling the potential mechanisms behind hospitalization-associated disability in older patients; the Hospital-Associated Disability and impact on daily Life (Hospital-ADL) cohort study protocol. (2016)

BMC Geriatrics

Authors: Reichardt, L.A., Aarden, J.J., van Seben, R., van der Schaaf, M., Engelbert, R.H.H., Bosch, J.A., Buurman, B.M.

Abstract

BACKGROUND: Over 30 % of older patients experience hospitalization-associated disability (HAD) (i.e., loss of independence in Activities of Daily Living (ADLs)) after an acute hospitalization. Despite its high prevalence, the mechanisms that underlie HAD remain elusive. This paper describes the protocol for the Hospital-Associated Disability and impact on daily Life (Hospital-ADL) study, which aims to unravel the potential mechanisms behind HAD from admission to three months post-discharge. METHODS/DESIGN: The Hospital-ADL study is a multicenter, observational, prospective cohort study aiming to recruit 400 patients aged =70 years that are acutely hospitalized at departments of Internal Medicine, Cardiology or Geriatrics, involving six hospitals in the Netherlands. Eligible are patients hospitalized for at least 48 h, without major cognitive impairment (Mini Mental State Examination score =15), who have a life expectancy of more than three months, and without disablement in all six ADLs. The study will assess possible cognitive, behavioral, psychosocial, physical, and biological factors of HAD. Data will be collected through: 1] medical and demographical data; 2] personal interviews, which includes assessment of cognitive impairment, behavioral and psychosocial functioning, physical functioning, and health care utilization; 3] physical performance tests, which includes gait speed, hand grip strength, balance, bioelectrical impedance analysis (BIA), and an activity tracker (Fitbit Flex), and; 4] analyses of blood samples to assess inflammatory and metabolic markers. The primary endpoint is additional disabilities in ADLs three months post-hospital discharge compared to ADL function two weeks prior to hospital admission. Secondary outcomes are health care utilization, health-related quality of life (HRQoL), physical performance tests, and mortality. There will be at least five data collection points; within 48 h after admission (H1), at discharge (H3), and at one (P1; home visit), two (P2; by telephone) and three months (P3; home visit) post-discharge. If the patient is admitted for more than five days, additional measurements will be planned during hospitalization on Monday, Wednesday, and Friday (H2). DISCUSSION: The Hospital-ADL study will provide information on cognitive, behavioral, psychosocial, physical, and biological factors associated with HAD and will be collected during and following hospitalization. These data may inform new interventions to prevent or restore hospitalization-associated disability.

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Using a Community Wellness Program Pairing People with Shelter Dogs to Increase Physical Activity (2016)

Medicine & Science in Sports & Exercise

Authors: Becofsky, K., Lynch, L., Evans, E.W. and Wing, R.

Abstract

FosterFit™ is a community wellness program centered on the pairing of people with shelter dogs (Savannah, GA). Participants are matched with a shelter dog for 10 weeks and encouraged to 1) walk with their dog for at least 30 min/d and 2) consume a plant-based diet. Participants meet regularly for group sessions and events. PURPOSE: We examined whether this community program led to change in objectively measured physical activity (PA). We also examined program acceptability and change in psychosocial outcomes. METHODS: Steps/d and moderate-to-vigorous PA min/d were assessed via the FitBit Flex™ pre- and post-program. Participants rated their satisfaction (‘Overall, how would you rate the FosterFit wellness program?') and success with the exercise and diet components (‘Over the past 10 weeks, how much success have you had in following the exercise plan [healthy eating plan] set out by FosterFit?'). Surveys (stress, depressive symptoms, exercise self-efficacy) were also collected pre- and post-program. RESULTS: Nine participants (6 female, mean age 37 yrs, all non-Hispanic white or mixed race) joined the program and completed a baseline assessment. Program completion rate was 78% (7/9). Despite a small sample size, the program led to medium effect sizes for change in steps (d=0.41) and exercise self-efficacy (d=0.48), Average daily steps increased by 1,494, with increases in four of six participants with complete PA data. There were also small effect sizes for change in depressive symptoms (d=-0.20) and perceived stress (d=-0.19) and five of seven participants saw improvements in at least one psychosocial outcome. Of participants completing a program evaluation (n=8), 75% rated the program as ‘good' or ‘excellent', 86% reported ‘some success' or ‘a lot of success' following the exercise plan, and 75% reported ‘some success' or ‘a lot of success' following the healthy eating plan. and. Additionally, 6 participants permanently adopted their foster dog. CONCLUSION: These data demonstrate the feasibility of pairing people with shelter dogs for 10 weeks, and provide preliminary evidence that fostering a dog increases PA and mental wellbeing. Community-based interventions centered on dog fostering could be a novel approach to wellness promotion with added humanitarian benefits.

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Using High-Tech and High-Touch Methods for Effective Population Health Management (2016)

Iproceedings

Authors: Padarthy, S., Crespo, C., Rich, K. and Srivatsan, N.

Abstract

Background: Healthcare consumers today are more engaged and empowered than ever before. Social, mobile, and in-home self-monitoring tools now enable health consumers to manage their health conditions and receive advice, support, and care without leaving home. Consumers are increasingly buying biometric devices such the Fitbit and Apple Watch to monitor their health. Many payers and employers are providing fitness devices to encourage consumers to be healthy, often offering discounts to their healthcare premiums. These devices create a sense of euphoria initially, but they do not yield sustainable health results and necessary behavioral changes in consumers to sustain it in the long-term. According to BJ Fogg, Stanford professor, sustainable behavior change (B) is a function of the motivation of the individual (M) × ability of the individual to do the task (A) × Trigger (T); B=MAT. Objective: Our hypothesis was that self-managed digital triggers alone would not yield sustainable change, but a combination of digital biometrics devices that automatically monitor health supplemented by weekly contact with a health coach would deliver sustainable changes to consumer behavior. Methods: During the 6-month pilot in 2014 and 12-month program in 2015, Cognizant wanted to test this hypothesis by providing appropriate triggers to motivate individuals to achieve their goals and ensure sustainable change in behavior. We provided Fitbit devices to participants and shared their digital information with our health coach. The coach worked with the individuals in setting individual goals, reviewed their progress, and helped with better food and exercise choices. The coach also used gamification to motivate the group into friendly competitions. Results: At the end of the pilot, participants averaged 70,000 steps per week. This was well above the average US baseline of 36,000 steps and Fitbit average of 42,000 steps. Pilot participants also lost over an average of 10 pounds each. However, during the pilot we determined coaching needed more focus on incremental, sustainable goals to lead toward long-term behavior changes. During a 6 month period between the pilot ending and the 2015 program initiation where pilot participants did not have access to a coach, participants' activity level decreased, and weight lost during the pilot was gained back. During the 2015 program, participants sustained on average 66,000 steps per week (well above both the US and Fitbit average). Obese 1 participants normalized steps at 70,000 per week and increased activity from baseline almost 30%. This group started at the very bottom of “Somewhat Active” and transitioned into the “Active” category. Obese 2 participants normalized steps at 60,000 per week and increased activity from baseline almost 33%, which transitioned them from “Low Active” to “Somewhat Active.” This was the largest increase by any group from baseline. Our control group, who did not have access to coaches, averaged only 43,000 steps per week. Conclusions: Coach influence and participant change is most effective in the first 6 months. After that, coaches concentrate on incrementally increasing activity in a sustainable manner. Effective population health management and high value personalized services can be achieved by weight loss from increasing physical activity and better food choices brought about by direct consumer engagement that combines “high tech” with “high touch.” [iproc 2016;2(1):e17]

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Validating The Latest Commercial Physical Activity Monitors (2016)

Medicine & Science in Sports & Exercise

Authors: Chow, J.J., Ward, R.E., Thom, J.M. and Parmenter, B.J.

Abstract

PURPOSE: Completing 10,000 steps per day is recommended by the World Health Organisation, the US Centre for Disease Control and the Australian National Heart Foundation. Physical activity monitors (PAM) are popular and have become increasingly available, marketed for their ability to count steps. However, limited data is available on the newer monitors (Fitbits/Jawbone) in comparison to the Actigraph, a validated research-based accelerometer, or a visual step counts, at multiple speeds and placement sites. This study aimed to compare these newer PAMs to the Actigraph and a visual count 1) across different speeds; and 2) at different placement sites in a lab based treadmill test. METHODS: Participants wore an Actigraph wGT3X-BT and Fitbit One around the waist and each wrist, as well as a Fitbit Flex, Fitbit Charge HR and Jawbone UP24 on each wrist while performing 5 x 3 minute bouts on a treadmill at multiple speeds (5.0, 6.5, 8.0, 10.0 and 12.0km/h). A video of their lower limbs was recorded for a visual count (criterion measure) to be completed in duplicate. Paired sample t-tests to test for any significant differences and Spearman's correlations for associations, between the device and visual count were completed. RESULTS: 31 participants (61% male) aged 24.3±5.2yrs ranging in BMI (18.6kg/m2 to 29.9kg/m2) were recruited. Across all speeds the Actigraph (waist) and Fitbit One (waist) were accurate when compared to visual counts (p,0.001), with the Fitbit One (waist) being the most accurate PAM at slower speeds (5.0, 6.5km/h). All PAMs worn around the wrist became more accurate at the faster speeds with the strongest associations at 8.0km/h=Fitbit Charge (r=0.87, p,0.01); 10.0km/h=Fitbit One (r=0.91, p<0.01) and 12.0km/h=Jawbone (r=0.90, p<0.01). Most PAMS, excluding the Fitbit One significantly undercounted at 5.0 and 6.5km/h (p>0.05). At the higher speeds (10.0, 12.0kph) there were no significant differences (p<0.05) between step counts for all devices. CONCLUSION: The step count accuracy of PAMs was affected by speed and placement site. The Fitbit One (waist) was the most accurate PAM across all speeds. Other PAMs worn on the wrist were accurate at the faster speeds only. Future studies should look at the effect of body mass index and outdoor free living environments on the accuracy of these newer PAMs.

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Validation And Accuracy Of Fitbit Charge (2016)

Medicine & Science in Sports & Exercise

Authors: Leininger, L.J., Cook, B.J., Jones, V., Bellumori, M. and Adams, K.J.

Abstract

URPOSE: Wearable activity monitors (e.g., Fitbit®) have become increasingly popular for both researchers and lay people alike. Recent studies have reported several Fitbit® models correlate with research grade monitors; however none to date have examined the Fitbit® Charge model. Furthermore, none have reported on the accuracy of Fitbit® devices. The primary purpose of this study was to compare step counts assessed by Fitbit® Charge and a research grade accelerometer (i.e., Actigraph®). The secondary purpose of this study was to compare the Fitbit® Charge algorithms for physical activity intensity with an algorithm validated for research purposes. METHODS: Participants (n=8) wore Fitbit® Charge and Actigraph® monitors for 7 days. First, correlations were run to examine the concordance of step counts and physical activity intensity levels derived from Fitbit® Charge and Actigraph® algorithms. Next, accuracy was investigated by paired sample t-tests comparing each device's assessment of step counts and minutes spent in light, moderate and vigorous intensity activity. RESULTS: Significant correlations were found for all study outcomes (p's textless .05). Significant differences were observed for step counts on all days and weekly total step count (p's textless .05). Analyses of each intensity level revealed significant differences on most days for light and moderate intensity (p's textless.05). For vigorous intensity, only day 6 (p = .007) and accumulated weekly total of minutes were different (p = .014). CONCLUSIONS: Our correlation results were similar to previous research examining validity of other Fitbit® models. However, Fitbit® Charge devices may overestimate step counts. Moreover, the algorithm used by Fitbit® may overestimate light and vigorous physical activity, while underestimating minutes in moderate physical activity. Further research is needed to determine reliability of Fitbit® Charge to assess activity and intensity that reflects current health recommendations. Therefore, researchers should use discretion if considering use of Fitbit® Charge for research purposes.

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Validation and Accuracy of FITBIT Charge: A Pilot Study in a University Worksite Walking Program (2016)

Journal of Fitness Research

Authors: Leininger, L.J., Cook, B.J. and Adams, K.J.

Abstract

PURPOSE: Wearable activity monitors (e.g., Fitbit®) have become increasingly popular for both researchers and lay people alike. Recent studies have reported several Fitbit® models correlate with research grade monitors; however none to date have examined the Fitbit® Charge model. Furthermore, none have reported on the accuracy of Fitbit® devices. The primary purpose of this study was to compare step counts assessed by Fitbit® Charge and a research grade accelerometer (i.e., Actigraph®). The secondary purpose of this study was to compare the Fitbit® Charge algorithms for physical activity intensity with an algorithm validated for research purposes. METHODS: Participants (n=8) wore Fitbit® Charge and Actigraph® monitors for 7 days. First, correlations were run to examine the concordance of step counts and physical activity intensity levels derived from Fitbit® Charge and Actigraph® algorithms. Next, accuracy was investigated by paired sample t-tests comparing each device’s assessment of step counts and minutes spent in light, moderate and vigorous intensity activity. RESULTS: Significant correlations were found for all study outcomes (p’s < .05). Significant differences were observed for step counts on all days and weekly total step count (p’s < .05). Analyses of each intensity level revealed significant differences on most days for light and moderate intensity (p’s <.05). For vigorous intensity, only day 6 (p = .007) and accumulated weekly total of minutes were different (p = .014). CONCLUSIONS: Our correlation results were similar to previous research examining validity of other Fitbit® models. However, Fitbit® Charge devices may overestimate step counts. Moreover, the algorithm used by Fitbit® may overestimate light and vigorous physical activity, while underestimating minutes in moderate physical activity. Further research is needed to determine reliability of Fitbit® Charge to assess activity and intensity that reflects current health recommendations. Therefore, researchers should use discretion if considering use of Fitbit® Charge for research purposes.

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Validation of the Fitbit Charge Heart Rate Device to Monitor Physical Activity in Children with Congenital Heart Disease (2016)

Canadian Journal of Cardiology

Authors: Gardner, R., Voss, C., Dean, P. and Harris, K.

Abstract

Background: Commercial wearable activity trackers, like the FitBit™, may be useful to monitor and promote activity in children. However, these trackers are designed for adults and it is unclear whether they are valid for use in children. The aim of this study was to determine whether the FitBit Charge HR™ accurately estimates daily step counts in a pediatric population. Methods: Eligible participants (10-18yrs) were recruited from the Children's Heart Centre at BC Children's Hospital and partnership clinics across the province of British Columbia. Participants were fitted with an accelerometer positioned over the right hip (Actigraph LLC; ‘criterion') and a wrist-worn FitBit Charge HR™ (‘measure'). Participants were asked to wear both devices simultaneously for 7 consecutive days. We retrieved daily sums of step counts from valid accelerometry days, which was defined as monitor wear time of =600 minutes/day (Actilife LLC). We paired these days with corresponding daily step counts from the FitBit™ for analyses. A subset of participants underwent exercise tolerance testing while wearing the FitBit™ to validate its heart rate tracking feature. We calculated intra-class correlation coefficients (ICC) and mean bias (criterion-measure) with 95% limits of agreement (95%LoA) to estimate agreement between devices. Results: Twenty-one participants (13.4±2.0yrs, 57% female) provided 97 person-days of data. Overall, there was a strong association between the two devices for daily step counts across person-days (ICC=0.852, ptextless0.001). However, FitBit™ devices systematically recorded more steps than accelerometers (9,914±5,255 vs. 7,637±3,953 steps/day) with a mean bias of -2,277 steps/day (95%LoA= -7,587-3,034). We were unable to assess the validity of the FitBit™ heart rate tracking feature during exercise tolerance testing because of electromagnetic interference from clinical equipment, which temporarily impacted the data recording ability of the FitBit™. Conclusion: FitBit Charge HR™ devices are a valid tool to assess patterns in daily step count in a pediatric population; however, caution is required when comparing FitBit Charge HR™ step counts to physical activity studies that are based on the more conservative criterion measure.

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Validity and Reliability of Fitbit Flex for Step Count, Moderate to Vigorous Physical Activity and Activity Energy Expenditure (2016)

PLOS ONE

Authors: Sushames, A., Edwards, A., Thompson, F., McDermott, R. and Gebel, K.

Abstract

Objectives: To examine the validity and reliability of the Fitbit Flex against direct observation for measuring steps in the laboratory and against the Actigraph for step counts in free-living conditions and for moderate-to-vigorous physical activity (MVPA) and activity energy expenditure (AEE) overall. Methods: Twenty-five adults (12 females, 13 males) wore a Fitbit Flex and an Actigraph GT3X+ during a laboratory based protocol (including walking, incline walking, running and stepping) and free-living conditions during a single day period to examine measurement of steps, AEE and MVPA. Twenty-four of the participants attended a second session using the same protocol. Results: Intraclass correlations (ICC) for test-retest reliability of the Fitbit Flex were strong for walking (ICC = 0.57), moderate for stair stepping (ICC = 0.34), and weak for incline walking (ICC = 0.22) and jogging (ICC = 0.26). The Fitbit significantly undercounted walking steps in the laboratory (absolute proportional difference: 21.2%, 95%CI 13.0–29.4%), but it was more accurate, despite slightly over counting, for both jogging (6.4%, 95%CI 3.7–9.0%) and stair stepping (15.5%, 95%CI 10.1–20.9%). The Fitbit had higher coefficients of variation (Cv) for step counts compared to direct observation and the Actigraph. In free-living conditions, the average MVPA minutes were lower in the Fitbit (35.4 minutes) compared to the Actigraph (54.6 minutes), but AEE was greater from the Fitbit (808.1 calories) versus the Actigraph (538.9 calories). The coefficients of variation were similar for AEE for the Actigraph (Cv = 36.0) and Fitbit (Cv = 35.0), but lower in the Actigraph (Cv = 25.5) for MVPA against the Fitbit (Cv = 32.7). Conclusion: The Fitbit Flex has moderate validity for measuring physical activity relative to direct observation and the Actigraph. Test-rest reliability of the Fitbit was dependant on activity type and had greater variation between sessions compared to the Actigraph. Physical activity surveillance studies using the Fitbit Flex should consider the potential effect of measurement reactivity and undercounting of steps.

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Validity of Wearable Fitness Trackers on Sleep Measure (2016)

Medicine & Science in Sports & Exercise

Authors: Keill, A.K., An, H.-S., Dinkel, D.M. and Lee, J.-M.

Abstract

PURPOSE: To examine the validity of wearable fitness trackers for estimating total sleep time (TST) with respect to a sleep log as a reference measure. METHODS: Nineteen healthy individuals (mean ± SD; age = 29.5 ± 13.4 years; body mass index = 25.87 ± 5.03 kg textperiodcentered m2) participated in the study. Participants randomly assigned to one of two groups. Group 1 (n = 10) wore the BodyMedia SenseWear Mini Armband (SWA), Basis Peak (BP), and Fitbit Charge HR (FB). Group 2 (n = 9) wore the ActiGraph Sleep (AG), Jawbone UP3 (JU), and Garmin Vivosmart (GV). Trackers were worn on the non-dominant wrist for one night and a sleep log was completed. Two existing sleep algorithms for the AG (Sadeh and Cole-Kripke) and Fitbit sleep sensitive algorithm were also included for comparison. Pearson correlation was used to examine the linearity of mean TST minutes (TSTM) from each tracker compared to the log TSTM. Mean absolute percentage errors (MAPE) of TSTM from each tracker were calculated against the log TSTM. Lastly, mean differences in average TST between the trackers were examined by a general linear model for repeated measures. RESULTS: Pearson correlation coefficients were .32, .69, .24, and -.26 for the SWA, FB, and FBs with regard to log TSTM, respectively. Group 2 correlations between the log TSTM and Sadeh, Cole-Kripke, JU, and GV were .34, .65, .54, and .92, respectively. MAPE were 17.1%, 16.3%, 40.2%, and 32.9% for SWA, FB, FBs, and BP, respectively. MAPE of 17.0%, 11.5%, 14.9%, and 10% were observed for Sadeh, Cole-Kripke, JU, and GV, respectively. Bland-Altman Plots showed no systematic bias between all variables for TST compared with log TSTM. ANOVA and post-hoc analysis revealed a significant difference in the Fitbit sensitive TST (p = .001) in Group 1 (F (5, 51) = 8.06, p = .00) and no significant difference between Group 2 (F (4, 40) = 1.27, p = .296). CONCLUSION: The FB, Cole-Kripke, JU, and GV display the closest estimation of TST compared with log TST minutes. However, further research is needed to validate these monitors with polysomnography.

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Video and computer-based interactive exercises are safe and improve task-specific balance in geriatric and neurological rehabilitation: a randomised trial (2016)

Journal of Physiotherapy

Authors: van den Berg, M., Sherrington, C., Killington, M., Smith, S., Bongers, B., Hassett, L. and Crotty, M.

Abstract

Question: Does adding video/computer-based interactive exercises to inpatient geriatric and neurological rehabilitation improve mobility outcomes? Is it feasible and safe? Design: Randomised trial. Participants: Fifty-eight rehabilitation inpatients. Intervention: Physiotherapist-prescribed, tailored, video/computer-based interactive exercises for 1 hour on weekdays, mainly involving stepping and weight-shifting exercises. Outcome measures: The primary outcome was the Short Physical Performance Battery (0 to 3) at 2 weeks. Secondary outcomes were: Maximal Balance Range (mm); Step Test (step count); Rivermead Mobility Index (0 to 15); activity levels; Activity Measure for Post Acute Care Basic Mobility (18 to 72) and Daily Activity (15 to 60); Falls Efficacy Scale (10 to 40), ED5D utility score (0 to 1); Reintegration to Normal Living Index (0 to 100); System Usability Scale (0 to 100) and Physical Activity Enjoyment Scale (0 to 126). Safety was determined from adverse events during intervention. Results: At 2 weeks the between-group difference in the primary outcome (0.1, 95% CI –0.2 to 0.3) was not statistically significant. The intervention group performed significantly better than usual care for Maximal Balance Range (38mm difference after baseline adjustment, 95% CI 6 to 69). Other secondary outcomes were not statistically significant. Fifty-eight (55%) of the eligible patients agreed to participate, 25/29 (86%) completed the intervention and 10 (39%) attended textgreater 70% of sessions, with a mean of 5.6 sessions (SD 3.3) attended and overall average duration of 4.5hours (SD 3.1). Average scores were 62 (SD 21) for the System Usability Scale and 62 (SD 8) for the Physical Activity Enjoyment Scale. There were no adverse events. Conclusion: The addition of video/computer-based interactive exercises to usual rehabilitation is a safe and feasible way to increase exercise dose, but is not suitable for all. Adding the exercises to usual rehabilitation resulted in task-specific improvements in balance but not overall mobility. Registration: ACTRN12613000610730. [van den Berg M, Sherrington C, Killington M, Smith S, Bongers B, Hassett L, Crotty M (2016) Video and computer-based interactive exercises are safe and improve task-specific balance in geriatric and neurological rehabilitation: a randomised trial. Journal of Physiotherapy 62: 20–28]

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“Not just another walking program”: Everyday Activity Supports You (EASY) model---a randomized pilot study for a parallel randomized controlled trial (2015)

Pilot and Feasibility Studies

Authors: Ashe, M.C., Winters, M., Hoppmann, C.A., Dawes, M.G., Gardiner, P.A., Giangregorio, L.M., Madden, K.M., McAllister, M.M., Wong, G., Puyat, J.H., Singer, J., Sims-Gould, J. and McKay, H.A.

Abstract

Background: Maintaining physical activity is an important goal with positive health benefits, yet many people spend most of their day sitting. Our Everyday Activity Supports You (EASY) model aims to encourage movement through daily activities and utilitarian walking. The primary objective of this phase was to test study feasibility (recruitment and retention rates) for the EASY model. Methods: This 6-month study took place in Vancouver, Canada, from May to December 2013, with data analyses in February 2014. Participants were healthy, inactive, community-dwelling women aged 55--70 years. We recruited through advertisements in local community newspapers and randomized participants using a remote web service. The model included the following: group-based education and social support, individualized physical activity prescription (called Activity 4-1-1), and use of a Fitbit activity monitor. The control group received health-related information only. The main outcome measures were descriptions of study feasibility (recruitment and retention rates). We also collected information on activity patterns (ActiGraph GT3X+ accelerometers) and health-related outcomes such as body composition (height and weight using standard techniques), blood pressure (automatic blood pressure monitor), and psychosocial variables (questionnaires). Results: We advertised in local community newspapers to recruit participants. Over 3 weeks, 82 participants telephoned; following screening, 68% (56/82) met the inclusion criteria and 45% (25/56) were randomized by remote web-based allocation. This included 13 participants in the intervention group and 12 participants in the control group (education). At 6 months, 12/13 (92%) intervention and 8/12 (67%) control participants completed the final assessment. Controlling for baseline values, the intervention group had an average of 2,080 [95% confidence intervals (CIs) 704, 4,918] more steps/day at 6 months compared with the control group. There was an average between group difference in weight loss of -4.3 [95% CI -6.22, -2.40] kg and reduction in diastolic blood pressure of -8.54 [95% CI -16.89, -0.198] mmHg, in favor of EASY. Conclusions: The EASY pilot study was feasible to deliver; there was an increase in physical activity and reduction in weight and blood pressure for intervention participants at 6 months. (Continued

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A Mobile Health Driven Walking Program Improves Quality of Life but not Fitness or Fatness in Obese Sedentary Women (2015)

Circulation

Authors: Stewart, K.J., Katz, J., Dobrosielski, M. and Ouyang, P.

Abstract

Background: Many mHealth programs exist for increasing physical activity (PA) yet few have been tested for their effects on fitness, fatness, and health related quality of life (HRQOL). Methods: We conducted a 3-month randomized trial that examined 2 message formats that promoted the 10,000 steps/day walking program. Women (n=70), aged 48+/-12 years, BMI 35.0 +/-3.8, with self-report of no regular (PA), were given a FitBit and smartphone, which automatically sent daily step data to us daily. Daily messages with feedback about meeting step goals and motivation to add 500 more daily steps/week were sent to the subject's smartphone. We compared the Multimedia Messaging Service (MMS) consisting of audio, video and graphs versus the Short Message Service (SMS), or plain text messages. Message content was the same for both groups. Outcomes included the 6-minute walk test, weight, waist and hip circumferences, BMI, SF-36, and Profile of Mood States (POMS). We hypothesized that MMS subjects would be more engaged, walk more, and attain greater gains in study outcomes. Results: We delayed messaging for the first 2 weeks to establish a daily step baseline, which was 6665 +/-2270. There were no group differences in daily steps at baseline or at any time point in the study. Daily steps in Month 1 was 6926+/-2465; Month 2, 7327+/- 3310; and Month 3, 6642+/-2914. The increases from baseline to the full Month 1 (p=0.004) and Month 1 to 2 (p=0.025) were significant but not the decrease from Month 2 to 3. The FitBit was worn 91% of study days in both groups. There were no changes or group differences in any fitness or fatness measure. Both groups similarly improved SF-36 General Health (p=0.02) and Vitality (p=0.01); and POMS Fatigue (p=0.01), Vigor (p=0.001), Tension-Anxiety (p=0.03), and Total Mood Score, (p=0.02). Conclusions: Baseline steps were about 2-3 times more than expected for sedentary women. It seems that the novelty of using a tracking device accelerated the planned progression for walking, with a much higher than expected step count initially and then a slight drop over time. An average of 10,000 steps/day was not met. There were no changes in physical measures though indicators of HRQOL improved. Contrary to our hypothesis, the different messaging formats did not affect outcomes.

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A televideo exercise and nutrition program for children with acute lymphoblastic leukemia in maintenance therapy: design and methods (2015)

Open Access Journal of Clinical Trials

Authors: Gibson, C., August, K., Greene, J.L., Herrmann, S.D., Lee, J., Harvey, S.P., Lambourne, K. and Debra, S.

Abstract

Changes in nutrient intake and decreased exercise resulting from cancer therapies as well as their side effects may be contributing factors in the increased body weight and differences in physical fitness observed in survivors of childhood acute lymphoblastic leukemia (ALL). This article will describe the study protocol for an intervention program designed to improve the physical activity and nutrition behaviors of ALL survivors. Twenty-four children aged between 4 years and 12 years with ALL will be randomized to a 6-month technology-based exercise and nutrition program (TLC4ALLKids) or to enhanced usual care (eUC). The participants randomized to the TLC4ALLKids will participate in weekly, 1-hour coaching sessions on nutrition and physical activity and 1-hour physical activity classes delivered by group video conferencing. Participants will be provided with iPad tablets loaded with video conferencing software and the Healthy Lifestyle Tracking calendar to track daily nutrition and physical activity goals and weight. Both groups will be provided with Fitbit™ Zip to monitor physical activity. To assess feasibility, participant recruitment (achievement of proposed sample size), attendance (per weekly online sessions/assessment sessions), and adherence (number of families at 3 and 6 months) will be evaluated. Outcome measures to assess the intervention will include anthropometrics (weight, height, and waist circumference), physical activity (accelerometry), energy and macronutrient intake (food records), sleep habits (Children's Sleep Habits Questionnaire), and quality of life (Pediatric Quality of Life Inventory) will be obtained at baseline, 3 months, and 6 months. Semi-structured interviews will be used to gather information about ways to improve the program and overcome barriers to participation. If successful, the TLC4ALLKids intervention will provide a means to educate and improve the health behaviors of ALL survivors that can be delivered remotely and conveniently to participants.

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Comparison of a Commercial Accelerometer with Polysomnography and Actigraphy in Children and Adolescents (2015)

Sleep

Authors: Meltzer, L.J., Hiruma, L.S., Avis, K., Montgomery-Downs, H. and Valentin, J.

Abstract

Study Objectives: To evaluate the reliability and validity of the commercially available Fitbit Ultra (2012) accelerometer compared to polysomnography (PSG) and two different actigraphs in a pediatric sample. Design and Setting: All subjects wore the Fitbit Ultra while undergoing overnight clinical polysomnography in a sleep laboratory; a randomly selected subset of participants also wore either the Ambulatory Monitoring Inc. Motionlogger Sleep Watch (AMI) or Phillips-Respironics Mini-Mitter Spectrum (PRMM). Participants: 63 youth (32 females, 31 males), ages 3–17 years (mean 9.7 years, SD 4.6 years). Measurements: Both “Normal” and “Sensitive” sleep-recording Fitbit Ultra modes were examined. Outcome variables included total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE). Primary analyses examined the differences between Fitbit Ultra and PSG using repeated-measures ANCOVA, with epoch-by-epoch comparisons between Fitbit Ultra and PSG used to determine sensitivity, specificity, and accuracy. Intra-device reliability, differences between Fitbit Ultra and actigraphy, and differences by both developmental age group and sleep disordered breathing (SDB) status were also examined. Results: Compared to PSG, the Normal Fitbit Ultra mode demonstrated good sensitivity (0.86) and accuracy (0.84), but poor specificity (0.52); conversely, the Sensitive Fitbit Ultra mode demonstrated adequate specificity (0.79), but inadequate sensitivity (0.70) and accuracy (0.71). Compared to PSG, the Fitbit Ultra significantly overestimated TST (41 min) and SE (8%) in Normal mode, and underestimated TST (105 min) and SE (21%) in Sensitive mode. Similar differences were found between Fitbit Ultra (both modes) and both brands of actigraphs. Conclusions: Despite its low cost and ease of use for consumers, neither sleep-recording mode of the Fitbit Ultra accelerometer provided clinically comparable results to PSG. Further, pediatric sleep researchers and clinicians should be cautious about substituting these devices for validated actigraphs, with a significant risk of either overestimating or underestimating outcome data including total sleep time and sleep efficiency.

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Comparison of Three Inexpensive Commercially Available Activity Monitors to a Previously Validated Tri-Axial Accelerometer (2015)

Medicine & Science in Sports & Exercise

Authors: Reid, R.E., Comptour, A.M., Insogna, J.A., Bewski, N.A., Sciortino, C.D. and Andersen, R.E.

Abstract

Inexpensive personal activity monitors have recently gained popularity with the general public. Given the current wide-spread use of these devices, it is important to ensure that users are attaining accurate information compared to previously validated measures. PURPOSE: To compare the accuracy of the Fitbit Force™ and One™ activity monitors in measuring steps per day and time spent in different intensities of activity with the ActiGraph GT3X™tri-axial accelerometer. METHODS: Twenty-two women, 18-26y.o. with a BMI of 23.24 ± 3.26kg/m2 wore two Fitbit Ones TM (Bra and Waist respectively), a Fitbit Force TM (Wrist), and an ActiGraph GT3X™(Waist) for 7-consecutive days. ActiGraph™ data was processed using Actilife™ V5.1.1 and the Freedson equation activity cut points. Fitbit™ data was processed using their proprietary online software. A multivariate analysis of variance (MANOVA) was used to compare steps per day and time spent in light, moderate and vigorous intensity activities between the four devices. A post-hoc test of the least squared difference was used to determine where any differences occurred. RESULTS: The activity monitors differed in time spent in light F(3,19)= 3.16, ptextgreater.05) and vigorous (F(3,19)= 3.16, ptextgreater.05) intensity activities. Post-hoc comparisons revealed that the GT3X™ differed from all three Fitbit™ devices in the measurement of time spent in light (GT3X= 89.92±36 min, Force=419.97±129.22 min, Bra=379.93±122.2 min, Waist=392.75±114.78 min) and vigorous activities (GT3X=7.05±9.63 min, Force=36.91±27.7 min, Bra=31.29±18.53 min, Waist=30.45±18.3 min). There was no difference found in the number of steps per day or minutes of moderate intensity activity recorded between the four devices. CONCLUSIONS: Fitbit™ activity monitors compare well to other previously validated objective activity monitors in the measurement of steps per day and time spent in moderate intensity activities. However, Fitbit™ devices may not accurately quantify the time spent in light and vigorous intensity activities, and therefore may not be the ideal solution for individuals' personal activity monitoring needs.

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Effects of an Intervention using Movement Technology in a University Physical Activity Class (2015)

Medicine & Science in Sports & Exercise

Authors: Mahar, M.T., Nanney, L.W., Das, B.M., Raedeke, T.D., Vick, G.A. and Rowe, D.A.

Abstract

The college-age population is insufficiently active and physical activity declines during the college years. Interventions in university settings are potential avenues for increasing physical activity in this population. PURPOSE: To examine the effect of movement technology on college students' physical activity levels, self-determined motivation for physical activity, physical activity enjoyment, and stage of change. METHODS: Students (N = 75) wore pedometers for one week at baseline and at post-intervention to objectively assess physical activity. Volunteer participants in a university basic instruction course were randomly assigned to condition. The intervention group (n = 34) wore a Fitbit® Flex everyday throughout the 10-week intervention. The comparison group (n = 41) did not wear a Fitbit monitor. The Fitbit is a commercially available monitor that can be used to assess physical activity, provide feedback, self-monitor, and set goals. Intervention effectiveness was evaluated with a series of mixed model analyses of variance and effect size estimates via Cohen's delta (d). RESULTS: Across conditions, students showed decreases in objectively measured steps per day from baseline to post-intervention, possibly due to the time of the semester in which the pedometer assessment was conducted. However, students who wore a Fitbit had a lesser decrease in steps per day (decrease of 104 steps per day, d = -0.05) compared to students who did not wear a Fitbit (decrease of 461 steps per day, d = -0.18). The difference in changes in steps per day between conditions was small and not significant (p = .98; d = 0.16). From baseline to post-intervention, self-reported physical activity increased more in the students who wore a Fitbit than in students who did not (p = .07; d = 0.32). Changes in self-determined motivation for physical activity, physical activity enjoyment, and stage of change were similar for both groups (p textgreater .05, d textless 0.16). Intrinsic regulation was the only motivational variable that increased more among students who wore a Fitbit compared to students who did not wear a Fitbit (d = 0.33), although this difference was not significant (p = .11). CONCLUSIONS: Commercially available activity monitors, such as the Fitbit, can have a small positive impact on physical activity and intrinsic regulation for physical activity.

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Mobile Phone-Connected Wearable Motion Sensors to Assess Postoperative Mobilization (2015)

JMIR mHealth and uHealth

Authors: Appelboom, G., Taylor, B.E., Bruce, E., Bassile, C.C., Malakidis, C., Yang, A., Youngerman, B., D'Amico, R., Bruce, S., Bruyère, O., Reginster, J.-Y., Dumont, E.P. and Connolly Jr, E.S.

Abstract

Background: Early mobilization after surgery reduces the incidence of a wide range of complications. Wearable motion sensors measure movements over time and transmit this data wirelessly, which has the potential to monitor patient recovery and encourages patients to engage in their own rehabilitation. Objective: We sought to determine the ability of off-the-shelf activity sensors to remotely monitor patient postoperative mobility. Methods: Consecutive subjects were recruited under the Department of Neurosurgery at Columbia University. Patients were enrolled during physical therapy sessions. The total number of steps counted by the two blinded researchers was compared to the steps recorded on four activity sensors positioned at different body locations. Results: A total of 148 motion data points were generated. The start time, end time, and duration of each walking session were accurately recorded by the devices and were remotely available for the researchers to analyze. The sensor accuracy was significantly greater when placed over the ankles than over the hips (P<.001). Our multivariate analysis showed that step length was an independent predictor of sensor accuracy. On linear regression, there was a modest positive correlation between increasing step length and increased ankle sensor accuracy (r=.640, r2=.397) that reached statistical significance on the multivariate model (P=.03). Increased gait speed also correlated with increased ankle sensor accuracy, although less strongly (r=.444, r2=.197). We did not note an effect of unilateral weakness on the accuracy of left- versus right-sided sensors. Accuracy was also affected by several specific measures of a patient’s level of physical assistance, for which we generated a model to mathematically adjust for systematic underestimation as well as disease severity. Conclusions: We provide one of the first assessments of the accuracy and utility of widely available and wirelessly connected activity sensors in a postoperative patient population. Our results show that activity sensors are able to provide invaluable information about a patient’s mobility status and can transmit this data wirelessly, although there is a systematic underestimation bias in more debilitated patients.

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Systematic review of the validity and reliability of consumer-wearable activity trackers. (2015)

The International Journal of Behavioral Nutrition and Physical Activity

Authors: Evenson, K.R., Goto, M.M. and Furberg, R.D.

Abstract

BACKGROUND: Consumer-wearable activity trackers are electronic devices used for monitoring fitness- and other health-related metrics. The purpose of this systematic review was to summarize the evidence for validity and reliability of popular consumer-wearable activity trackers (Fitbit and Jawbone) and their ability to estimate steps, distance, physical activity, energy expenditure, and sleep. METHODS: Searches included only full-length English language studies published in PubMed, Embase, SPORTDiscus, and Google Scholar through July 31, 2015. Two people reviewed and abstracted each included study. RESULTS: In total, 22 studies were included in the review (20 on adults, 2 on youth). For laboratory-based studies using step counting or accelerometer steps, the correlation with tracker-assessed steps was high for both Fitbit and Jawbone (Pearson or intraclass correlation coefficients (CC) textgreater =0.80). Only one study assessed distance for the Fitbit, finding an over-estimate at slower speeds and under-estimate at faster speeds. Two field-based studies compared accelerometry-assessed physical activity to the trackers, with one study finding higher correlation (Spearman CC 0.86, Fitbit) while another study found a wide range in correlation (intraclass CC 0.36-0.70, Fitbit and Jawbone). Using several different comparison measures (indirect and direct calorimetry, accelerometry, self-report), energy expenditure was more often under-estimated by either tracker. Total sleep time and sleep efficiency were over-estimated and wake after sleep onset was under-estimated comparing metrics from polysomnography to either tracker using a normal mode setting. No studies of intradevice reliability were found. Interdevice reliability was reported on seven studies using the Fitbit, but none for the Jawbone. Walking- and running-based Fitbit trials indicated consistently high interdevice reliability for steps (Pearson and intraclass CC 0.76-1.00), distance (intraclass CC 0.90-0.99), and energy expenditure (Pearson and intraclass CC 0.71-0.97). When wearing two Fitbits while sleeping, consistency between the devices was high. CONCLUSION: This systematic review indicated higher validity of steps, few studies on distance and physical activity, and lower validity for energy expenditure and sleep. The evidence reviewed indicated high interdevice reliability for steps, distance, energy expenditure, and sleep for certain Fitbit models. As new activity trackers and features are introduced to the market, documentation of the measurement properties can guide their use in research settings.

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Text Messaging to Reduce Inactivity Using Real-Time Step Count Monitoring in Sedentary Overweight Females (2015)

Circulation

Authors: Ouyang, P., Stewart, K.J., Bedra, M.E., York, S., Valdiviezo, C. and Finkelstein, J.

Abstract

Introduction: Prolonged periods of of inactivity are associated with higher CV morbidity independent of level of activity. Work and lifestyle choices today are associated with long periods of sitting, e.g. computer or screen watching. Wearable activity monitors such as pedometers have focused on increasing daily activity but not on reducing inactivity. Hypothesis: Sedentary women will decrease inactivity if given a real time reminder of inactivity . Method: We developed a program to monitor real-time activity levels generated by a wearable activity monitor (Fitbit). Fitbit communicated step counts to a smartphone which sent this information to a database every 15 minutes. When 10 or fewer steps had been recorded for a 60 min period of time, an inactivity reminder text message was sent to the participant to encourage them to move about. 30 obese women with self-reported > 3 hours of inactivity per day, were enrolled, provided with a Fitbit and smartphone, and monitored for 8 weeks. Women were randomized to two groups. Gp A received inactivity reminders (IR) for the first 4 weeks followed by 4 weeks without IR. Gp B received no IR during the first 4 weeks and IR was given during the second 4 weeks. We defined inactivity as = 20 steps in a 2 hr block. We compared the percent of 2-hr blocks between 8:00 and 24:00 hr where women were inactive during the 4 weeks with IR-on vs IR-off, for each of the 2 groups. The mean number of steps per day over each 4 week block was also compared. Results: Gps A and B were similar in age (51.8 + 12.2 y), BMI (37.1 + 6.9), self-reported hypertension (27% ), diabetes (23 %), and hyperlipidemia (23%). Fitbit data was available from 27 women. Gp A (n=15) self-reported 5.2 + 2.5 hr sitting/day at work during IR-off vs 3.9 + 2.7 with IR-on (p<0.004). Gp B (n=12), who had IR turned on in the second 4 week block, self-reported no change in hours sitting with or without IR. Activity monitoring data showed that Gp A were inactive for 32 + 23% of the 2-hr periods during the 4 weeks with IR-off vs 21 + 14% with IR-on (p < 0.004). However, Gp B had no difference in inactivity periods (28 + 12% with IR-off vs 28 + 14 % with IR-on). There were no differences in mean total daily steps walked during either 4 week block with IR-on or IR-off in either Gp. Conclusion: The use of real-time text messaging to inform women that they had been inactive for more than 60 mins was associated with a reduction in number of inactive periods independent of the number of steps taken a day. However, this effect was seen only when the reminder was implemented soon after enrollment. The behavior change did not persist after the reminders stopped. This study demonstrates that automated real time reminders can reduce periods of inactivity though the timing of the intervention affected the results. Further work will explore the behavioral factors that could improve the effectiveness and sustainability of the intervention.

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The Effect of Fitbit Technology on Physical Activity in Inactive Adults (50+ Years of Age) (2015)

Medicine & Science in Sports & Exercise

Authors: Vasold, K.L., Groendal, E.G. and Knous, J.L.

Abstract

The Fitbit tracker is a wearable technology designed to motivate individuals to become physically active by increasing awareness of physical activity (PA) levels. The Fitbit tracks activity, sleep, nutrition, uploads wirelessly, and is tiny and discreet. Published data is limited concerning the effectiveness of Fitbit technology on increasing PA levels in inactive adult populations. PURPOSE: To study changes in PA as a result of wearing the Fitbit for 8 weeks in individuals 50+ years of age. METHODS: Sixty university employees were stratified into two groups, intervention (n=29) and comparison (n=31), based on meeting PA recommendations of 150 minutes per week. Of these employees, 18 were ages 50 and over (7 intervention; 11 comparison). Intervention group participants (not meeting ACSM PA recommendations) were given a Fitbit to wear for 8 weeks, while comparison group participants were not and were encouraged to maintain their current PA habits. Demographic, anthropometric, and biometric data, body composition, flexibility, muscular strength/endurance, and cardiorespiratory fitness were assessed prior to and following the intervention. Self-reported PA was assessed via online survey. Independent sample T-tests were used to analyze differences between intervention and control groups. Paired sample T-tests were used to analyze differences pre- and post-Fitbit intervention. RESULTS: Mean age, weight, and BMI for the adult (50+) cohort of the sample was 58±5 years, 172±27 pounds, and 28.8±3.8 kg/m2, respectively. There were no significant differences between intervention and control groups at pre-test despite a large difference in self-reported PA (intervention: 70 minutes, comparison: 399 minutes). There was a positive change in self-reported PA in the intervention group from pre- to post-intervention that trended towards significance (p=0.08). Six out of seven of the intervention group participants were meeting PA recommendations post-intervention. CONCLUSIONS: Based on these results, wearing the Fitbit for 8 weeks increased PA in inactive adults (50+) to the point of meeting/exceeding PA recommendations. Further research is needed to determine the levels of improvement for this older adult population using this technology.

The Walking Interventions Through Texting (WalkIT) Trial: Rationale, Design, and Protocol for a Factorial Randomized Controlled Trial of Adaptive Interventions for Overweight and Obese, Inactive Adults (2015)

JMIR Research Protocols

Authors: Hurley, J.C., Hollingshead, K.E., Todd, M., Jarrett, C.L., Tucker, W.J., Angadi, S.S. and Adams, M.A.

Abstract

Background: Walking is a widely accepted and frequently targeted health promotion approach to increase physical activity (PA). Interventions to increase PA have produced only small improvements. Stronger and more potent behavioral intervention components are needed to increase time spent in PA, improve cardiometabolic risk markers, and optimize health. Objective: Our aim is to present the rationale and methods from the WalkIT Trial, a 4-month factorial randomized controlled trial (RCT) in inactive, overweight/obese adults. The main purpose of the study was to evaluate whether intensive adaptive components result in greater improvements to adults’ PA compared to the static intervention components. Methods: Participants enrolled in a 2x2 factorial RCT and were assigned to one of four semi-automated, text message–based walking interventions. Experimental components included adaptive versus static steps/day goals, and immediate versus delayed reinforcement. Principles of percentile shaping and behavioral economics were used to operationalize experimental components. A Fitbit Zip measured the main outcome: participants’ daily physical activity (steps and cadence) over the 4-month duration of the study. Secondary outcomes included self-reported PA, psychosocial outcomes, aerobic fitness, and cardiorespiratory risk factors assessed pre/post in a laboratory setting. Participants were recruited through email listservs and websites affiliated with the university campus, community businesses and local government, social groups, and social media advertising. Results: This study has completed data collection as of December 2014, but data cleaning and preliminary analyses are still in progress. We expect to complete analysis of the main outcomes in late 2015 to early 2016. Conclusions: The Walking Interventions through Texting (WalkIT) Trial will further the understanding of theory-based intervention components to increase the PA of men and women who are healthy, insufficiently active and are overweight or obese. WalkIT is one of the first studies focusing on the individual components of combined goal setting and reward structures in a factorial design to increase walking. The trial is expected to produce results useful to future research interventions and perhaps industry initiatives, primarily focused on mHealth, goal setting, and those looking to promote behavior change through performance-based incentives.

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Use of the Fitbit to Measure Adherence to a Physical Activity Intervention Among Overweight or Obese, Postmenopausal Women: Self-Monitoring Trajectory During 16 Weeks. (2015)

JMIR mHealth and uHealth

Authors: Cadmus-Bertram, L., Marcus, B.H., Patterson, R.E., Parker, B.A. and Morey, B.L.

Abstract

BACKGROUND: Direct-to-consumer trackers and devices have potential to enhance theory-based physical activity interventions by offering a simple and pleasant way to help participants self-monitor their behavior. A secondary benefit of these devices is the opportunity for investigators to objectively track adherence to physical activity goals across weeks or even months, rather than relying on self-report or a small number of accelerometry wear periods. The use of consumer trackers for continuous monitoring of adherence has considerable potential to enhance physical activity research, but few studies have been published in this rapidly developing area. OBJECTIVE: The objective of the study was to assess the trajectory of physical activity adherence across a 16-week self-monitoring intervention, as measured by the Fitbit tracker. METHODS: Participants were 25 overweight or obese, postmenopausal women enrolled in the intervention arm of a randomized controlled physical activity intervention trial. Each participant received a 16-week technology-based intervention that used the Fitbit physical activity tracker and website. The overall study goal was 150 minutes/week of moderate to vigorous intensity physical activity (MVPA) and 10,000 steps/day; however, goals were set individually for each participant and updated at Week 4 based on progress. Adherence data were collected by the Fitbit and aggregated by Fitabase. Participants also wore an ActiGraph GT3X+ accelerometer for 7 days prior to the intervention and again during Week 16. RESULTS: The median participant logged 10 hours or more/day of Fitbit wear on 95% of the 112 intervention days, with no significant decline in wear over the study period. Participants averaged 7540 (SD 2373) steps/day and 82 minutes/week (SD 43) of accumulated "fairly active" and "very active" minutes during the intervention. At Week 4, 80% (20/25) of women chose to maintain/increase their individual MVPA goal and 72% (18/25) of participants chose to maintain/increase their step goal. Physical activity levels were relatively stable after peaking at 3 weeks, with only small declines of 8% for steps (P=.06) and 14% for MVPA (P=.05) by 16 weeks. CONCLUSIONS: These data indicate that a sophisticated, direct-to-consumer activity tracker encouraged high levels of self-monitoring that were sustained over 16 weeks. Further study is needed to determine how to motivate additional gains in physical activity and evaluate the long-term utility of the Fitbit tracker as part of a strategy for chronic disease prevention.

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Wearable Sensor/Device (Fitbit One) and SMS Text-Messaging Prompts to Increase Physical Activity in Overweight and Obese Adults: A Randomized Controlled Trial. (2015)

Telemedicine and e-Health

Authors: Wang, J.B., Cadmus-Bertram, L.A., Natarajan, L., White, M.M., Madanat, H., Nichols, J.F., Ayala, G.X. and Pierce, J.P.

Abstract

BACKGROUND: Studies have shown self-monitoring can modify health behaviors, including physical activity (PA). This study tested the utility of a wearable sensor/device (Fitbit(®) One™; Fitbit Inc., San Francisco, CA) and short message service (SMS) text-messaging prompts to increase PA in overweight and obese adults. MATERIALS AND METHODS: Sixty-seven adults wore a Fitbit One tracker for 6 weeks; half were randomized to also receive three daily SMS-based PA prompts. The Fitbit One consisted of a wearable tracker for instant feedback on performance and a Web site/mobile application (app) for detailed summaries. Outcome measures were objectively measured steps and minutes of PA by intensity using two accelerometers: Actigraph™ (Pensacola, FL) GT3X+ (primary measure) at baseline and Week 6 and Fitbit One (secondary measure) at baseline and Weeks 1, 2, 3, 4, 5, and 6. RESULTS: Mixed-model repeated-measures analysis of primary measures indicated a significant within-group increase of +4.3 (standard error [SE]=2.0) min/week of moderate- to vigorous-intensity PA (MVPA) at 6-week follow-up (p=0.04) in the comparison group (Fitbit only), but no study group differences across PA levels. Secondary measures indicated the SMS text-messaging effect lasted for only 1 week: the intervention group increased by +1,266 steps (SE=491; p=0.01), +17.8 min/week MVPA (SE=8.5; p=0.04), and +38.3 min/week total PA (SE=15.9; p=0.02) compared with no changes in the comparison group, and these between-group differences were significant for steps (p=0.01), fairly/very active minutes (ptextless0.01), and total active minutes (p=0.02). CONCLUSIONS: These data suggest that the Fitbit One achieved a small increase in MVPA at follow-up and that the SMS-based PA prompts were insufficient in increasing PA beyond 1 week. Future studies can test this intervention in those requiring less help and/or test strategies to increase participants' engagement levels.

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Accuracy of 2 activity monitors in detecting steps in people with stroke and traumatic brain injury. (2014)

Physical Therapy

Authors: Fulk, G.D., Combs, S.A., Danks, K.A., Nirider, C.D., Raja, B. and Reisman, D.S.

Abstract

BACKGROUND: Advances in sensor technologies and signal processing techniques provide a method to accurately measure walking activity in the home and community. Activity monitors geared toward consumer or patient use may be an alternative to more expensive monitors designed for research to measure stepping activity. OBJECTIVE: The objective of this study was to examine the accuracy of 2 consumer/patient activity monitors, the Fitbit Ultra and the Nike+ Fuelband, in identifying stepping activity in people with stroke and traumatic brain injury (TBI). Secondarily, the study sought to compare the accuracy of these 2 activity monitors with that of the StepWatch Activity Monitor (SAM) and a pedometer, the Yamax Digi-Walker SW-701 pedometer (YDWP). DESIGN: A cross-sectional design was used for this study. METHOD: People with chronic stroke and TBI wore the 4 activity monitors while they performed the Two-Minute Walk Test (2MWT), during which they were videotaped. Activity monitor estimated steps taken were compared with actual steps taken counted from videotape. Accuracy and agreement between activity monitor estimated steps and actual steps were examined using intraclass correlation coefficients (ICC [2,1]) and the Bland-Altman method. RESULTS: The SAM demonstrated the greatest accuracy (ICC [2,1]=.97, mean difference between actual steps and SAM estimated steps=4.7 steps) followed by the Fitbit Ultra (ICC [2,1]=.73, mean difference between actual steps and Fitbit Ultra estimated steps=-9.7 steps), the YDWP (ICC [2,1]=.42, mean difference between actual steps and YDWP estimated steps=-28.8 steps), and the Nike+ Fuelband (ICC [2,1]=.20, mean difference between actual steps and Nike+ Fuelband estimated steps=-66.2 steps). LIMITATIONS: Walking activity was measured over a short distance in a closed environment, and participants were high functioning ambulators, with a mean gait speed of 0.93 m/s. CONCLUSIONS: The Fitbit Ultra may be a low-cost alternative to measure the stepping activity in level, predictable environments of people with stroke and TBI who can walk at speeds =0.58 m/s.

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Activity monitor intervention to promote physical activity of physicians-in-training: randomized controlled trial. (2014)

PloS ONE

Authors: Thorndike, A.N., Mills, S., Sonnenberg, L., Palakshappa, D., Gao, T., Pau, C.T. and Regan, S.

Abstract

BACKGROUND: Physicians are expected to serve as role models for healthy lifestyles, but long work hours reduce time for healthy behaviors. A hospital-based physical activity intervention could improve physician health and increase counseling about exercise. METHODS: We conducted a two-phase intervention among 104 medical residents at a large hospital in Boston, Massachusetts. Phase 1 was a 6-week randomized controlled trial comparing daily steps of residents assigned to an activity monitor displaying feedback about steps and energy consumed (intervention) or to a blinded monitor (control). Phase 2 immediately followed and was a 6-week non-randomized team steps competition in which all participants wore monitors with feedback. Phase 1 outcomes were: 1) median steps/day and 2) proportion of days activity monitor worn. The Phase 2 outcome was mean steps/day on days monitor worn (=500 steps/day). Physiologic measurements were collected at baseline and study end. Median steps/day were compared using Wilcoxon rank-sum tests. Mean steps were compared using repeated measures regression analyses. RESULTS: In Phase 1, intervention and control groups had similar activity (6369 vs. 6063 steps/day, p = 0.16) and compliance with wearing the monitor (77% vs. 77% of days, p = 0.73). In Phase 2 (team competition), residents recorded more steps/day than during Phase 1 (CONTROL: 7,971 vs. 7,567, p = 0.002; INTERVENTION: 7,832 vs. 7,739, p = 0.13). Mean compliance with wearing the activity monitor decreased for both groups during Phase 2 compared to Phase 1 (60% vs. 77%, p < 0.001). Mean systolic blood pressure decreased (p = 0.004) and HDL cholesterol increased (p < 0.001) among all participants at end of study compared to baseline. CONCLUSIONS: Although the activity monitor intervention did not have a major impact on activity or health, the high participation rates of busy residents and modest changes in steps, blood pressure, and HDL suggest that more intensive hospital-based wellness programs have potential for promoting healthier lifestyles among physicians.

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An inexpensive device for monitoring patients' weights via automated hovering (2014)

International Journal of Cardiology

Authors: Shaffer, J.A., Diaz, K., Alcántara, C., Edmondson, D., Krupka, D.J., Chaplin, W.F. and Davidson, K.W.

Abstract

Daily weight monitoring is integral to the management of heart failure (HF). Indeed, weight gain is a marker of HF decompensation, and daily weight monitoring has been associated with favorable prognosis. Until now, assessment of weight has required patients to attend an in-person visit, which provides only an infrequent snapshot of their weight. Remote hovering practices have gained considerable traction during the past several years, but their use outside of research settings has been limited. We tested the accuracy of remote weight monitoring using the Fitbit® Aria™ weight scale, a commercially available, inexpensive device that communicates data wirelessly, can transmit data remotely to healthcare providers, and yields data that can be banked into medical data repositories. We recruited 33 healthy employees from an academic medical center. Participants were at least 18 years of age, could read or write in English, and were routinely on campus at least 4 days per week. Participants were excluded if they failed to complete their daily weight assessments. Each day participants weighed themselves using both the Fitbit® Aria™ and seca 769 scales, the latter of which served as a gold standard comparator. Participants recorded the date and time of their scale reading and the weights reported by both scales to the nearest 0.1 lb. Participants provided informed consent, and the study protocol was approved by the local institutional review board. 32 participants provided at least 10 weight readings (minimum, 12; maximum, 41; mean, 26; standard deviation [SD], 7.2). Participants' weights ranged from 89.8 lbs to 224.6 lbs, with a mean weight of 150.9 lbs (31.2 lbs) on the Aria™ scale and a mean weight of 150.2 lbs (31.0 lbs) on the seca 769. The Aria™ demonstrated excellent agreement with the seca 769. Multilevel linear regression analysis revealed that the Aria™ systematically provided a weight reading that was 0.6 lbs greater than the seca 769, although the two scales did not differ in their assessment of weight over time. The flood of inexpensive monitoring devices to the consumer market has introduced new possibilities for remote HF management, but little is known about their accuracy. We demonstrated the accuracy of the Fitbit® Aria™ scale compared to the seca 769, a conventional scale designed for use in clinical practice. Daily information about patients' weights can alert clinicians to HF patients who are at high risk for hospitalization. Hovering remotely over patients may also engage patients in their own self-management.

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Behavior Change Techniques Implemented in Electronic Lifestyle Activity Monitors: A Systematic Content Analysis (2014)

Journal of Medical Internet Research

Authors: Lyons, E.J., Lewis, Z.H., Mayrsohn, B.G. and Rowland, J.L.

Abstract

Background: Electronic activity monitors (such as those manufactured by Fitbit, Jawbone, and Nike) improve on standard pedometers by providing automated feedback and interactive behavior change tools via mobile device or personal computer. These monitors are commercially popular and show promise for use in public health interventions. However, little is known about the content of their feedback applications and how individual monitors may differ from one another. Objective: The purpose of this study was to describe the behavior change techniques implemented in commercially available electronic activity monitors. Methods: Electronic activity monitors (N=13) were systematically identified and tested by 3 trained coders for at least 1 week each. All monitors measured lifestyle physical activity and provided feedback via an app (computer or mobile). Coding was based on a hierarchical list of 93 behavior change techniques. Further coding of potentially effective techniques and adherence to theory-based recommendations were based on findings from meta-analyses and meta-regressions in the research literature. Results: All monitors provided tools for self-monitoring, feedback, and environmental change by definition. The next most prevalent techniques (13 out of 13 monitors) were goal-setting and emphasizing discrepancy between current and goal behavior. Review of behavioral goals, social support, social comparison, prompts/cues, rewards, and a focus on past success were found in more than half of the systems. The monitors included a range of 5-10 of 14 total techniques identified from the research literature as potentially effective. Most of the monitors included goal-setting, self-monitoring, and feedback content that closely matched recommendations from social cognitive theory. Conclusions: Electronic activity monitors contain a wide range of behavior change techniques typically used in clinical behavioral interventions. Thus, the monitors may represent a medium by which these interventions could be translated for widespread use. This technology has broad applications for use in clinical, public health, and rehabilitation settings.

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Feasibility of Using Fitbit Flex to Motivate People with Rheumatoid Arthritis to BE Physically Active (2014)

Annals of the Rheumatic Diseases

Authors: Feehan, L., Clayton, C., Carruthers, E. and Li, L.

Abstract

Background: Physical activity (PA) can reduce pain and fatigue and improve quality of life in people with rheumatoid arthritis (RA), but adherence to an active lifestyle is poor. Wearable digital devices, such as Fitbit Flex™, are commercially available for people to track their PA and obtain on-demand feedback, with a goal to motivate users to be physically active. Most devices are designed for the general public. It is unclear whether it is feasible for people with RA, who have unique challenges with physical activity, to use these devices. Objectives: To examine the feasibility for people with RA to use Fitbit Flex for tracking their PA and motivating them to be active. Methods: Participants were recruited from rheumatologists' offices and online in Vancouver, Canada. Individuals were eligible if they were age 19 or older, had physician-diagnosed RA, were available for an orientation session, and had daily access to computer and internet service. Individuals with comorbid conditions that prevented them from being physically active were excluded. Eligible participants were given a Fitbit Flex to wear on the non-dominant wrist for 4 weeks. Instructions were provided to set up the device and their online personal profile, where they could view at real time their step count, caloric output, number of active minutes and sleep quality of the previous night. Participants also wore a SenseWear Mini™ accelerometer, a validated tool for measuring physical activity in RA patients, during the first and last 7 days of the study. Step count, energy expenditure, active time and sedentary time were compared between the two monitors using paired t-test. Participants were also asked to rate on a 5-point scale their experience with Fitbit at the end of 4 weeks. Results: 10 people with RA were recruited in September 2013. The majority were women (n=8) with a median age of 57 years (IQR=17; 67). All participants adhered to the 4-week protocol. The mean rating of the overall experience with the device and the online profile was 4.7 and 4.1, respectively. Compared to Sensewear, Fitbit recorded significantly higher step counts and total sedentary time, and lower total energy expenditure and light activity time. No significant difference was found in the moderate/vigorous physical activity (MVPA) time between the two devices. Conclusions: Participants enjoyed using Fitbit Flex to monitor their physical activity. However, it appeared to overestimate the number of steps and sedentary time, and underestimate light activity time and total energy expenditure. Our findings suggest that Fitbit may be more suitable for motivating patients with RA to increase MVPA than to decrease sedentary behaviours.

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Validity and usability of low-cost accelerometers for internet-based self-monitoring of physical activity in patients with chronic obstructive pulmonary disease. (2014)

Interactive Journal of Medical Research

Authors: Vooijs, M., Alpay, L.L., Snoeck-Stroband, J.B., Beerthuizen, T., Siemonsma, P.C., Abbink, J.J., Sont, J.K. and Rövekamp, T.A.

Abstract

BACKGROUND: The importance of regular physical activity for patients with chronic obstructive pulmonary disease (COPD) is well-established. However, many patients do not meet the recommended daily amount. Accelerometers might provide patients with the information needed to increase physical activity in daily life. OBJECTIVE: Our objective was to assess the validity and usability of low-cost Internet-connected accelerometers. Furthermore we explored patients' preferences with regards to the presentation of and feedback on monitored physical activity. METHODS: To assess concurrent validity we conducted a field validation study with patients who wore two low-cost accelerometers, Fitbit and Physical Activity Monitor (PAM), at the same time along with a sophisticated multisensor accelerometer (SenseWear Armband) for 48 hours. Data on energy expenditure assessed from registrations from the two low-cost accelerometers were compared to the well validated SenseWear Armband which served as a reference criterion. Usability was examined in a cross-over study with patients who, in succession, wore the Fitbit and the PAM for 7 consecutive days and filled out a 16 item questionnaire with regards to the use of the corresponding device RESULTS: The agreement between energy expenditure (METs) from the SenseWear Armband with METs estimated by the Fitbit and PAM was good (r=.77) and moderate (r=.41), respectively. The regression model that was developed for the Fitbit explained 92% whereas the PAM-model could explain 89% of total variance in METs measured by the SenseWear. With regards to the usability, both the Fitbit and PAM were well rated on all items. There were no significant differences between the two devices. CONCLUSIONS: The low-cost Fitbit and PAM are valid and usable devices to measure physical activity in patients with COPD. These devices may be useful in long-term interventions aiming at increasing physical activity levels in these patients.

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Live Long and Prosper: Potentials of Low-Cost Consumer Devices for the Prevention of Cardiovascular Diseases (2013)

Medicine 2.0

Authors: Meyer, J. and Hein, A.

Abstract

Background: Cardiovascular diseases (CVD) are one of the major causes of death worldwide. Personal behavior such as physical activity considerably influences the risk of incurring a CVD. In the last years numerous products such as pedometers have become available on the mass market that allow monitoring relevant behaviors and vital parameters. These devices are sufficiently precise, affordable, and easy to use. While today they are mostly lifestyle oriented they also have considerable potential for health and prevention. Objective: Our goal is to investigate how recent low-cost devices can be used in real-life settings for the prevention of CVD, and whether using these devices has an advantage over subjective self-assessment. We also examine whether it is feasible to use multiple of such devices in parallel. Methods: We observe whether and how persons are willing and able to use multiple devices in their daily lives. We compare the devices&8217; measurements with subjective self-assessment. We make use of existing low-cost consumer devices to monitor a user's behavior. By mapping the devices' features with pre-defined prevention goals we ensure that the system collects meaningful data that can be used to monitor the individual's behavior. We conducted a user study with 10 healthy adults to measure usability and to identify problems with sensor use in real life. The participants used the devices' original portals to monitor their behavior. The subjects (age range 35-75) used an off-the-shelf pedometer and a sports watch for 4 weeks. Results: The participants responded in principle positively to the use of the devices. Analyzing the sensor data, we found that the users had some difficulties in operating the devices. We also found that the participants' self-assessment of their health behavior was too optimistic compared to the monitored data. They rated the usability of the overall system with 71 of up to 100 points in the &34;System Usability Scale&34;. Conclusions: Our study indicates that today's devices are suitable for a long term monitoring of health for the prevention of CVD. Using the devices provides more precise data than a subjective self-assessment. However usability and acceptance of the systems are still major topics.

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Accuracy of the Fitbit pedometer for self-paced and prescribed physical activity (2012)

Medicine & Science in Sports & Exercise

Authors: Ramirez, E., Peterson, C., Wu, W. and Norman, G.J.

Abstract

PURPOSE: The purpose of this study was to examine the validity of the Fitbit pedometer (FB; Fitbit Inc.) for measuring steps taken during self-paced and prescribed physical activity. METHODS: A total of 17 adults (8 males, 9 females; age = 41.19, BMI = 28.82 kg/m2) participated in this study. Participants completed four to eight bouts of physical activities in a laboratory condition and in a simulated free-living condition. During the laboratory (treadmill) condition participants completed walking bouts at a slow pace (1.5 mph), a normal pace (3.0 mph), a brisk pace (4.0 mph) and one jogging bout (5.5 mph). Each bout lasted three minutes. Participants then completed 400m self-paced walking bouts at slow, normal, and brisk paces as well as one 400m jog on an outdoor track.. Male participants wore one FB and one Omron HJ-720IT (OM) on the right hip attached to an elastic belt and one FB in the right front pocket. Female participants wore the devices in the same configuration but also wore an additional FB attached to the front/center of the sports bra. Absolute and percent differences were calculated for FB vs. directly observed (DO) steps. Linear mixed models were determined effects of body location, speed, condition (laboratory vs. free-living) on FB accuracy. RESULTS:The magnitude of the difference between DO and the FB devices (M(SD); range) across all activities was small for both the FB-waist (2.0%(4.7%); -6 - 23%) and FB-bra (0.8%(4.3%); -11 - 15%) and moderate for the FB-pocket (8.8%(16.8%); 4 - 74%). Model parameter estimates from the full factorial mixed-model indicated the FB under estimated by 24 (SE = 2.83) steps across all conditions compared to direct observation. Significant parameter estimates for body location, speed and the body location × speed interaction (all p textless .001) indicated that the FB in the pocket underestimated steps more than on the waist, both devices underestimated steps more as speed increased, and the magnitude of the underestimation increased more for the pocket compared to the waist as speed increased. CONCLUSIONS:The FB appears to be a valid device for assessing step counts in adults when worn on the waist. Caution should be taken when assessing activities at higher ambulatory speeds. Further research is needed to better understand the validity of the FB in free-living conditions.

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