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

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/m2. 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.

[1]  B. Turner,et al.  Grounded Theory and Organizational Research , 1986 .

[2]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[3]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[4]  Magid Igbaria,et al.  The effects of self-efficacy on computer usage , 1995 .

[5]  C. Pieper,et al.  The reliability, validity, and stability of a measure of physical activity in the elderly. , 1996, Archives of physical medicine and rehabilitation.

[6]  D. Ainscow,et al.  Transient osteoporosis of the hip associated with osteogenesis imperfecta , 1998 .

[7]  J. Annesi,et al.  Effects of Computer Feedback on Adherence to Exercise , 1998, Perceptual and motor skills.

[8]  T P Schmalzried,et al.  Quantitative Assessment of Walking Activity after Total Hip or Knee Replacement* , 1998, The Journal of bone and joint surgery. American volume.

[9]  C. Christmas,et al.  Exercise and Older Patients: Guidelines for the Clinician , 2000, Journal of the American Geriatrics Society.

[10]  Hirofumi Tanaka,et al.  Aging, Habitual Exercise, and Dynamic Arterial Compliance , 2000, Circulation.

[11]  S. Blair,et al.  A comparative evaluation of three accelerometry-based physical activity monitors. , 2000, Medicine and science in sports and exercise.

[12]  L. Haddon Domestication and Mobile Telephony , 2001 .

[13]  C. Tudor-Locke Taking Steps toward Increased Physical Activity: Using Pedometers To Measure and Motivate. , 2002 .

[14]  B. J. Fogg,et al.  Persuasive technology: using computers to change what we think and do , 2002, UBIQ.

[15]  Gerald V. Smith,et al.  Microprocessor-based ambulatory activity monitoring in stroke patients. , 2002, Medicine and science in sports and exercise.

[16]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[17]  Cheng-Chang Sam Pan,et al.  Students' Attitude in a Web-enhanced Hybrid Course: A Structural Equaadon Modeling Inquiry , 2003 .

[18]  E. Rogers,et al.  Diffusion of Innovations, 5th Edition , 2003 .

[19]  B. Ainsworth,et al.  International physical activity questionnaire: 12-country reliability and validity. , 2003, Medicine and science in sports and exercise.

[20]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[21]  Mical K. Shilts,et al.  Goal Setting as a Strategy for Dietary and Physical Activity Behavior Change: A Review of the Literature , 2004, American journal of health promotion : AJHP.

[22]  Barbara E Ainsworth,et al.  Prevalence of Physical Activity in the United States: Behavioral Risk Factor Surveillance System, 2001 , 2005, Preventing chronic disease.

[23]  Thomas E Novotny,et al.  US Department of Health and Human Services: a need for global health leadership in preparedness and health diplomacy. , 2006, American journal of public health.

[24]  Shannon J. Lane,et al.  Bmc Medical Informatics and Decision Making a Review of Randomized Controlled Trials Comparing the Effectiveness of Hand Held Computers with Paper Methods for Data Collection , 2006 .

[25]  V. Braun,et al.  Using thematic analysis in psychology , 2006 .

[26]  J. Brach,et al.  Using activity monitors to measure physical activity in free-living conditions. , 2006, Physical therapy.

[27]  A. King,et al.  Physical activity and public health in older adults: recommendation from the American College of Sports Medicine and the American Heart Association. , 2007, Medicine and science in sports and exercise.

[28]  K. Courneya,et al.  Randomized controlled trial of the effects of print materials and step pedometers on physical activity and quality of life in breast cancer survivors. , 2007, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[29]  David Weller,et al.  Are electronic diaries useful for symptoms research? A systematic review. , 2007, Journal of psychosomatic research.

[30]  A. Bauman,et al.  Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. , 2007, Circulation.

[31]  P. Sainsbury,et al.  Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. , 2007, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[32]  I. Olkin,et al.  Using pedometers to increase physical activity and improve health: a systematic review. , 2007, JAMA.

[33]  David W. McDonald,et al.  Flowers or a robot army?: encouraging awareness & activity with personal, mobile displays , 2008, UbiComp.

[34]  David W. McDonald,et al.  Activity sensing in the wild: a field trial of ubifit garden , 2008, CHI.

[35]  M. Lim,et al.  SMS STI: A Review of the Uses of Mobile Phone Text Messaging in Sexual Health , 2008, International journal of STD & AIDS.

[36]  J. Brug,et al.  The Effectiveness of Tailored Feedback and Action Plans in an Intervention Addressing Multiple Health Behaviors , 2008, American journal of health promotion : AJHP.

[37]  Gunilla C. Nilsson,et al.  The Use of the Personal Digital Assistant (PDA) Among Personnel and Students in Health Care: A Review , 2008, Journal of medical Internet research.

[38]  Takashi Muto,et al.  Evaluation of a computer-tailored lifestyle modification support tool for employees in Japan. , 2009, Industrial health.

[39]  Ian Li,et al.  Beyond Counting Steps: Using Context to Improve Monitoring of Physical Activity , 2009 .

[40]  B. J. Fogg,et al.  A behavior model for persuasive design , 2009, Persuasive '09.

[41]  Ian Li Beyond Counting Steps: Using Context to Improve Monitoring of Physical Activity , 2009 .

[42]  B. Fjeldsoe,et al.  Behavior change interventions delivered by mobile telephone short-message service. , 2009, American journal of preventive medicine.

[43]  Peter T. Katzmarzyk,et al.  Physical Activity, Sedentary Behavior, and Health: Paradigm Paralysis or Paradigm Shift? , 2010, Diabetes.

[44]  Chia-Chin Chong,et al.  From Mobile Phones to Personal Wellness Dashboards , 2010, IEEE Pulse.

[45]  A. Haines,et al.  The effectiveness of M-health technologies for improving health and health services: a systematic review protocol , 2010, BMC Research Notes.

[46]  J. Blaya,et al.  E-health technologies show promise in developing countries. , 2010, Health affairs.

[47]  M. Terry Medical Apps for Smartphones. , 2010, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[48]  S. Michie,et al.  A refined taxonomy of behaviour change techniques to help people change their physical activity and healthy eating behaviours: The CALO-RE taxonomy , 2011, Psychology & health.

[49]  N. Owen,et al.  Sedentary behaviors and subsequent health outcomes in adults a systematic review of longitudinal studies, 1996-2011. , 2011, American journal of preventive medicine.

[50]  Wanda Pratt,et al.  How to evaluate technologies for health behavior change in HCI research , 2011, CHI.

[51]  V. Reed,et al.  The Effect of Computers for Weight Loss: A Systematic Review and Meta-analysis of Randomized Trials , 2011, Journal of General Internal Medicine.

[52]  R. Oostendorp,et al.  How to promote healthy behaviours in patients? An overview of evidence for behaviour change techniques , 2010, Health promotion international.

[53]  S. Nusser,et al.  Estimating minutes of physical activity from the previous day physical activity recall: validation of a prediction equation. , 2007, Journal of physical activity & health.

[54]  Shilpa Dogra,et al.  Sedentary Behavior and Physical Activity Are Independent Predictors of Successful Aging in Middle-Aged and Older Adults , 2012, Journal of aging research.

[55]  J. Schwartz,et al.  Interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people. , 2012, The Cochrane database of systematic reviews.

[56]  Thierry Troosters,et al.  Validity of Six Activity Monitors in Chronic Obstructive Pulmonary Disease: A Comparison with Indirect Calorimetry , 2012, PloS one.

[57]  Thierry Troosters,et al.  Validity of activity monitors in health and chronic disease: a systematic review , 2012, International Journal of Behavioral Nutrition and Physical Activity.

[58]  Morwenna Kirwan,et al.  Using Smartphone Technology to Monitor Physical Activity in the 10,000 Steps Program: A Matched Case–Control Trial , 2012, Journal of medical Internet research.

[59]  G. Schofield,et al.  Healthy Steps Trial: Pedometer-Based Advice and Physical Activity for Low-Active Older Adults , 2012, The Annals of Family Medicine.

[60]  Lucas J Carr,et al.  Letter to the editor: standardized use of the terms "sedentary" and "sedentary behaviours". , 2012, Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme.

[61]  Trudy van der Weijden,et al.  The Development of a Mobile Monitoring and Feedback Tool to Stimulate Physical Activity of People With a Chronic Disease in Primary Care: A User-Centered Design , 2013, JMIR mHealth and uHealth.

[62]  Andreas Hein,et al.  Live Long and Prosper: Potentials of Low-Cost Consumer Devices for the Prevention of Cardiovascular Diseases , 2013, Medicine 2.0.

[63]  Adolfo Muñoz,et al.  The Usefulness of Activity Trackers in Elderly with Reduced Mobility: A Case Study , 2013, MedInfo.

[64]  Jacqueline Kerr,et al.  Objectively Measured Physical Activity Is Related to Cognitive Function in Older Adults , 2013, Journal of the American Geriatrics Society.

[65]  E. L. Taylor,et al.  Pedometer-based walking interventions for free-living adults with type 2 diabetes: a systematic review. , 2013, Current diabetes reviews.

[66]  Dawn A. Skelton,et al.  Prevalence of Sedentary Behavior in Older Adults: A Systematic Review , 2013, International journal of environmental research and public health.

[67]  W. Zijlstra,et al.  Effects of remote feedback in home-based physical activity interventions for older adults , 2013 .

[68]  A. Dainty,et al.  Constructing Resilient Futures: Integrating UK multi-stakeholder transport and energy resilience for 2050 , 2013 .

[69]  Gregory J Welk,et al.  Validity of consumer-based physical activity monitors. , 2014, Medicine and science in sports and exercise.

[70]  Jeongeun Kim,et al.  A Qualitative Analysis of User Experiences With a Self-Tracker for Activity, Sleep, and Diet , 2014, Interactive journal of medical research.

[71]  Allison Gates,et al.  Evaluating User Perceptions of Mobile Medication Management Applications With Older Adults: A Usability Study , 2014, JMIR mHealth and uHealth.

[72]  P. Whincup,et al.  Adherence to physical activity guidelines in older adults, using objectively measured physical activity in a population-based study , 2014, BMC Public Health.

[73]  Wiebren Zijlstra,et al.  Adherence to and effectiveness of an individually tailored home-based exercise program for frail older adults, driven by mobility monitoring: design of a prospective cohort study , 2014, BMC Public Health.

[74]  Elizabeth J Lyons,et al.  Behavior Change Techniques Implemented in Electronic Lifestyle Activity Monitors: A Systematic Content Analysis , 2014, Journal of medical Internet research.

[75]  P. Siemonsma,et al.  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.

[76]  J. Brug,et al.  Apps to promote physical activity among adults: a review and content analysis , 2014, International Journal of Behavioral Nutrition and Physical Activity.

[77]  S. Daskalopoulou,et al.  Step Monitoring to improve ARTERial health (SMARTER) through step count prescription in type 2 diabetes and hypertension: trial design and methods , 2014, Cardiovascular Diabetology.

[78]  P Aveyard,et al.  Effect of behavioural techniques and delivery mode on effectiveness of weight management: systematic review, meta-analysis and meta-regression , 2014, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[79]  R. Dellavalle,et al.  Mobile medical and health apps: state of the art, concerns, regulatory control and certification , 2014, Online journal of public health informatics.

[80]  K. Kotani,et al.  Effects of a Year-Long Pedometer-Based Walking Program on Cardiovascular Disease Risk Factors in Active Older People , 2015, Asia-Pacific journal of public health.

[81]  James E. Katz,et al.  Machines That Become Us: The Social Context of Personal Communication Technology , 2017 .