Cited by 420Mobile Health and mHealth ApplicationsTechnology Use by Older AdultsPhysical Activity and Health

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Acceptance of Commercially Available Wearable Activity Trackers Among Adults Aged Over 50 and With Chronic Illness: A Mixed-Methods Evaluation

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Mercer, Kathryn, Giangregorio, Lora, Schneider, Eric, Chilana, Parmit, Li, Melissa, Grindrod, Kelly·2016·JMIR mHealth and uHealth

DOI 10.2196/mhealth.4225PMC PMC4749845

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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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Roy, R., Padhi, A., Nambiar, A. R., & Bhamburkar, V. K. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-4287-0.ch016
Additional file 1 of Effect of personal activity intelligence (PAI) monitoring in the maintenance phase of cardiac rehabilitation: a mixed methods evaluation
Hannan, A. L., Hing, W., Coombes, J. S., Gough, S., Climstein, M., Adsett, G., Jayasinghe, R., & Furness, J. W. (2021) · Figshare · doi:10.6084/m9.figshare.16780917
Additional file 10 of Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis
Casado-Robles, C., Viciana, J., Guijarro-Romero, S., & Mayorga-Vega, D. (2022) · Figshare · doi:10.6084/m9.figshare.19102005
Additional file 1 of Efficacy and acceptability of using wearable activity trackers in older adults living in retirement communities: a mixed method study
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Additional file 1 of Snacktivity™ to promote physical activity and reduce future risk of disease in the population: protocol for a feasibility randomised controlled trial and nested qualitative study
Daley, A., Griffin, R. A., Moakes, C. A., Sanders, J. P., Skrybant, M., Ives, N. J., Maylor, B., Greenfield, S. M., Gokal, K., Parretti, H. M., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26575772
Additional file 2 of Parkinson’s disease: current assessment methods and wearable devices for evaluation of movement disorder motor symptoms - a patient and healthcare professional perspective
AlMahadin, G., Lotfi, A., Zysk, E., Siena, F. L., Carthy, M. M., & Breedon, P. (2020) · Figshare · doi:10.6084/m9.figshare.13257485
Additional file 7 of Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis
Casado-Robles, C., Viciana, J., Guijarro-Romero, S., & Mayorga-Vega, D. (2022) · Figshare · doi:10.6084/m9.figshare.19102029
Additional file 8 of Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis
Casado-Robles, C., Viciana, J., Guijarro-Romero, S., & Mayorga-Vega, D. (2022) · Figshare · doi:10.6084/m9.figshare.19102032
Additional file 6 of Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis
Casado-Robles, C., Viciana, J., Guijarro-Romero, S., & Mayorga-Vega, D. (2022) · Figshare · doi:10.6084/m9.figshare.19102026
Additional file 1 of Exploring factors affecting the acceptance of fall detection technology among older adults and their families: a content analysis
Huang, H.-H., Chang, M.-H., Chen, P.-T., Lin, C.-L., Sung, P.-S., Chen, C.-H., & Fan, S.-Y. (2024) · Figshare · doi:10.6084/m9.figshare.26798769
Additional file 2 of Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis
Casado-Robles, C., Viciana, J., Guijarro-Romero, S., & Mayorga-Vega, D. (2022) · Figshare · doi:10.6084/m9.figshare.19102014
Additional file 11 of Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis
Casado-Robles, C., Viciana, J., Guijarro-Romero, S., & Mayorga-Vega, D. (2022) · Figshare · doi:10.6084/m9.figshare.19102008
Additional file 1 of Parkinson’s disease: current assessment methods and wearable devices for evaluation of movement disorder motor symptoms - a patient and healthcare professional perspective
AlMahadin, G., Lotfi, A., Zysk, E., Siena, F. L., Carthy, M. M., & Breedon, P. (2020) · Figshare · doi:10.6084/m9.figshare.13257482
Additional file 1 of It’s not about the capture, it’s about what we can learn”: a qualitative study of experts’ opinions and experiences regarding the use of wearable sensors to measure gait and physical activity
Keogh, A., Taraldsen, K., Caulfield, B., & Vereijken, B. (2021) · Figshare · doi:10.6084/m9.figshare.14576628
Additional file 1 of Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis
Casado-Robles, C., Viciana, J., Guijarro-Romero, S., & Mayorga-Vega, D. (2022) · Figshare · doi:10.6084/m9.figshare.19102011
Additional file 2 of It’s not about the capture, it’s about what we can learn”: a qualitative study of experts’ opinions and experiences regarding the use of wearable sensors to measure gait and physical activity
Keogh, A., Taraldsen, K., Caulfield, B., & Vereijken, B. (2021) · Figshare · doi:10.6084/m9.figshare.14576631
Additional file 3 of Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis
Casado-Robles, C., Viciana, J., Guijarro-Romero, S., & Mayorga-Vega, D. (2022) · Figshare · doi:10.6084/m9.figshare.19102017
Additional file 2 of Effect of personal activity intelligence (PAI) monitoring in the maintenance phase of cardiac rehabilitation: a mixed methods evaluation
Hannan, A. L., Hing, W., Coombes, J. S., Gough, S., Climstein, M., Adsett, G., Jayasinghe, R., & Furness, J. W. (2021) · Figshare · doi:10.6084/m9.figshare.16780920
Additional file 1 of The use of accelerometer-based wearable activity monitors in clinical settings: current practice, barriers, enablers, and future opportunities
Maher, C., Szeto, K., & Arnold, J. (2021) · Figshare · doi:10.6084/m9.figshare.16778375
Additional file 5 of Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis
Casado-Robles, C., Viciana, J., Guijarro-Romero, S., & Mayorga-Vega, D. (2022) · Figshare · doi:10.6084/m9.figshare.19102023

Authors: Mercer, K., Giangregorio, L., Schneider, E., Chilana, P., Li, M., & Grindrod, K.
Affiliations: University of Waterloo (CA)
Wingate University (US)
Corresponding author: Grindrod, Kelly
ORCID: Mercer, Kathryn
Giangregorio, Lora
Schneider, Eric
Chilana, Parmit
Li, Melissa
Grindrod, Kelly
Venue: JMIR mHealth and uHealth
Publisher: JMIR Publications Inc.
Published: 2016-01-27
Volume: 4
Issue: 1
Pages: e7
ISSN: 2291-5222 (ISSN-L)
DOI: 10.2196/mhealth.4225
PMC: PMC4749845
OpenAlex: W2254170564
Cited by: 419
References: 79
Citations by year: 2026: 18 · 2025: 38 · 2024: 28 · 2023: 36 · 2022: 50 · 2021: 71 · 2020: 47 · 2019: 40 · 2018: 42 · 2017: 39 · 2016: 10
FWCI: 81.22
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
Locations: JMIR mhealth and uhealth (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
UWSpace (University of Waterloo) (submittedVersion, cc-by)
Topics: Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Health Sciences › Medicine › Geriatrics and Gerontology › Technology Use by Older Adults
Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
Keywords: wearable activity trackers, older adults, chronic disease, technology acceptance, usability, pedometers, physical activity promotion, sedentary behavior, Fitbit, misfit, jaw bone, self-monitoring, goal setting, technology adoption, user experience, diabetes mellitus, arthritis, osteoporosis, vascular disease, physical inactivity prevention

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Acceptance of Commercially Available Wearable Activity Trackers Among Adults Aged Over 50 and With Chronic Illness: A Mixed-Methods Evaluation

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