Author(s):
Kathryn Mercer
Lora Giangregorio
Eric Schneider
Parmit Chilana
Melissa Li
Kelly Grindrod
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/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.
Documentation:
https://doi.org/10.2196/mhealth.4225
References:
- Harvey JA, Chastin SF, Skelton DA. Prevalence of sedentary behavior in older adults: A systematic review. Int J Environ Res Public Health 2013 Dec;10(12):6645-6661 [FREE Full text] [CrossRef] [Medline]
- Christmas C, Andersen RA. Exercise and older patients: Guidelines for the clinician. J Am Geriatr Soc 2000 Mar;48(3):318-324. [Medline]
- Tanaka H, Dinenno FA, Monahan KD, Clevenger CM, DeSouza CA, Seals DR. Aging, habitual exercise, and dynamic arterial compliance. Circulation 2000 Sep 12;102(11):1270-1275 [FREE Full text] [Medline]
- US Department of Health and Human Services. Physical Activity Guidelines for Americans. 2008. URL: https://www.health.gov/paguidelines [accessed 2015-12-14] [WebCite Cache]
- Tucker JM, Welk G, Nusser SM, Beyler NK, Dzewaltowski D. Estimating minutes of physical activity from the previous day physical activity recall: Validation of a prediction equation. J Phys Act Health 2011 Jan;8(1):71-78. [Medline]
- Nelson ME, Rejeski WJ, Blair SN, Duncan PW, Judge JO, King AC, American College of Sports Medicine, et al. Physical activity and public health in older adults: Recommendation from the American College of Sports Medicine and the American Heart Association. Circulation 2007 Aug 28;116(9):1094-1105 [FREE Full text] [CrossRef] [Medline]
- Katzmarzyk PT. Physical activity, sedentary behavior, and health: Paradigm paralysis or paradigm shift? Diabetes 2010 Nov;59(11):2717-2725 [FREE Full text] [CrossRef] [Medline]
- Thorp AA, Owen N, Neuhaus M, Dunstan DW. Sedentary behaviors and subsequent health outcomes in adults a systematic review of longitudinal studies, 1996-2011. Am J Prev Med 2011 Aug;41(2):207-215. [CrossRef] [Medline]
- Kerr J, Marshall SJ, Patterson RE, Marinac CR, Natarajan L, Rosenberg D, et al. Objectively measured physical activity is related to cognitive function in older adults. J Am Geriatr Soc 2013 Nov;61(11):1927-1931 [FREE Full text] [CrossRef] [Medline]
- Dogra S, Stathokostas L. Sedentary behavior and physical activity are independent predictors of successful aging in middle-aged and older adults. J Aging Res 2012;2012:190654 [FREE Full text] [CrossRef] [Medline]
- Sedentary Behaviour Research Networ. Letter to the Editor: Standardized use of the terms “sedentary” and “sedentary behaviours”. Appl Physiol Nutr Metab 2012 Jun;37(3):540-542. [CrossRef] [Medline]
- Geraedts H, Zijlstra A, Bulstra S, Stevens M, Zijlstra W. Effects of remote feedback in home-based physical activity interventions for older adults: A systematic review. Patient Educ Couns 2013 Apr;91(1):14-24. [CrossRef] [Medline]
- Jefferis BJ, Sartini C, Lee I, Choi M, Amuzu A, Gutierrez C, et al. Adherence to physical activity guidelines in older adults, using objectively measured physical activity in a population-based study. BMC Public Health 2014;14(382):382 [FREE Full text] [CrossRef] [Medline]
- Macera C, Ham S, Yore M, Jones D, Ainsworth B, Kimsey C, et al. Prevalence of physical activity in the United States: Behavioral Risk Factor Surveillance System, 2001. Prev Chronic Dis 2005 Apr;2(2):A17 [FREE Full text] [Medline]
- Geraedts HA, Zijlstra W, Zhang W, Bulstra S, Stevens M. 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. BMC Public Health 2014;14:570 [FREE Full text] [CrossRef] [Medline]
- Shilts MK, Horowitz M, Townsend MS. Goal setting as a strategy for dietary and physical activity behavior change: A review of the literature. Am J Health Promot 2004;19(2):81-93. [Medline]
- van Achterberg T, Huisman-de Waal GG, Ketelaar NA, Oostendorp RA, Jacobs JE, Wollersheim HC. How to promote healthy behaviours in patients? An overview of evidence for behaviour change techniques. Health Promot Int 2011 Jun;26(2):148-162 [FREE Full text] [CrossRef] [Medline]
- Fujii H, Nakade M, Haruyama Y, Fukuda H, Hashimoto M, Ikuyama T, et al. Evaluation of a computer-tailored lifestyle modification support tool for employees in Japan. Ind Health 2009 Jul;47(3):333-341 [FREE Full text] [Medline]
- de Vries H, Kremers SP, Smeets T, Brug J, Eijmael K. The effectiveness of tailored feedback and action plans in an intervention addressing multiple health behaviors. Am J Health Promot 2008;22(6):417-425. [CrossRef] [Medline]
- Annesi JJ. Effects of computer feedback on adherence to exercise. Percept Mot Skills 1998 Oct;87(2):723-730. [CrossRef] [Medline]
- Kim J. A qualitative analysis of user experiences with a self-tracker for activity, sleep, and diet. Interact J Med Res 2014;3(1):e8 [FREE Full text] [CrossRef] [Medline]
- Bravata DM, Smith-Spangler C, Sundaram V, Gienger AL, Lin N, Lewis R, et al. Using pedometers to increase physical activity and improve health: A systematic review. JAMA 2007 Nov 21;298(19):2296-2304. [CrossRef] [Medline]
- Funk M, Taylor EL. Pedometer-based walking interventions for free-living adults with type 2 diabetes: A systematic review. Curr Diabetes Rev 2013 Nov;9(6):462-471. [Medline]
- Miyazaki R, Kotani K, Tsuzaki K, Sakane N, Yonei Y, Ishii K. Effects of a year-long pedometer-based walking program on cardiovascular disease risk factors in active older people. Asia Pac J Public Health 2015 Mar;27(2):155-163. [CrossRef] [Medline]
- Kolt GS, Schofield GM, Kerse N, Garrett N, Ashton T, Patel A. Healthy Steps trial: Pedometer-based advice and physical activity for low-active older adults. Ann Fam Med 2012;10(3):206-212 [FREE Full text] [CrossRef] [Medline]
- Miyazaki R, Kotani K, Tsuzaki K, Sakane N, Yonei Y, Ishii K. Effects of a year-long pedometer-based walking program on cardiovascular disease risk factors in active older people. Asia Pac J Public Health 2015 Mar;27(2):155-163. [CrossRef] [Medline]
- Welk G, Blair S, Wood K, Jones S, Thompson RW. A comparative evaluation of three accelerometry-based physical activity monitors. Med Sci Sports Exerc 2000 Sep;32(9 Suppl):S489-S497. [Medline]
- Van Remoortel H, Giavedoni S, Raste Y, Burtin C, Louvaris Z, Gimeno-Santos E, PROactive consortium. Validity of activity monitors in health and chronic disease: A systematic review. Int J Behav Nutr Phys Act 2012;9:84 [FREE Full text] [CrossRef] [Medline]
- Van Remoortel H, Raste Y, Louvaris Z, Giavedoni S, Burtin C, Langer D, PROactive consortium. Validity of six activity monitors in chronic obstructive pulmonary disease: A comparison with indirect calorimetry. PLoS One 2012;7(6):e39198 [FREE Full text] [CrossRef] [Medline]
- Lee J, Kim Y, Welk GJ. Validity of consumer-based physical activity monitors. Med Sci Sports Exerc 2014 Sep;46(9):1840-1848. [CrossRef] [Medline]
- Lauritzen J, Muñoz A, Luis SJ, Civit A. The usefulness of activity trackers in elderly with reduced mobility: A case study. Stud Health Technol Inform 2013;192:759-762. [Medline]
- Schmalzried T, Szuszczewicz E, Northfield M, Akizuki KH, Frankel R, Belcher GH, et al. Quantitative assessment of walking activity after total hip or knee replacement. J Bone Joint Surg Am 1998 Jan;80(1):54-59. [Medline]
- Kochersberger G, McConnell E, Kuchibhatla M, Pieper C. The reliability, validity, and stability of a measure of physical activity in the elderly. Arch Phys Med Rehabil 1996 Aug;77(8):793-795. [Medline]
- Macko R, Haeuber E, Shaughnessy M, Coleman K, Boone D, Smith GK, et al. Microprocessor-based ambulatory activity monitoring in stroke patients. Med Sci Sports Exerc 2002 Mar;34(3):394-399. [Medline]
- Meyer J, Hein A. Live long and prosper: Potentials of low-cost consumer devices for the prevention of cardiovascular diseases. Med 2 0 2013;2(2):e7 [FREE Full text] [CrossRef] [Medline]
- Dasgupta K, Rosenberg E, Daskalopoulou SS. Step Monitoring to improve ARTERial health (SMARTER) through step count prescription in type 2 diabetes and hypertension: Trial design and methods. Cardiovasc Diabetol 2014;13:7 [FREE Full text] [CrossRef] [Medline]
- Vallance JK, Courneya K, Plotnikoff R, Yasui Y, Mackey J. Randomized controlled trial of the effects of print materials and step pedometers on physical activity and quality of life in breast cancer survivors. J Clin Oncol 2007 Jun 10;25(17):2352-2359 [FREE Full text] [CrossRef] [Medline]
- Vooijs M, Alpay L, Snoeck-Stroband J, Beerthuizen T, Siemonsma P, Abbink J, et al. Validity and usability of low-cost accelerometers for internet-based self-monitoring of physical activity in patients with chronic obstructive pulmonary disease. Interact J Med Res 2014;3(4):e14 [FREE Full text] [CrossRef] [Medline]
- Fogg B. A Behavior Model for Persuasive Design. New York: ACM; 2009. URL: http://bjfogg.com/fbm_files/page4_1.pdf [accessed 2015-12-14] [WebCite Cache]
- Terry K. Gamification Boosts Employee Health Behavior, Blue Shield Argues. 2014. URL: http://www.informationweek.com/healthcare/patient-tools/gamification-boosts-employee-health-behavior-blue-shield-argues/d/d-id/1103948? [accessed 2015-12-14] [WebCite Cache]
- Sircar I, Sage D, Goodier C, Fussey P, Dainty A. Constructing resilient futures: Integrating UK multi-stakeholder transport and energy resilience for 2050. Futures 2013 May;49:49-63. [CrossRef]
- Kirwan M, Duncan MJ, Vandelanotte C, Mummery WK. Using smartphone technology to monitor physical activity in the 10,000 Steps program: A matched case-control trial. J Med Internet Res 2012;14(2):e55 [FREE Full text] [CrossRef] [Medline]
- Consolvo S, Klasnja P, McDonald D, Avrahami D, Froehlich J, LeGrand L, et al. Flowers or a robot army? Encouraging awareness & activity with personal, mobile displays. In: UbiComp’08. New York: ACM Press; 2008 Presented at: 10th International Conference on Ubiquitous Computing; Sept 21-24, 2008; Seoul, South Korea p. 54-63 URL: https://dub.washington.edu/djangosite/media/papers/UbiComp188-consolvo.pdf
- van der Weegen S, Verwey R, Spreeuwenberg M, Tange H, van der Weijden T, de Witte L. 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. JMIR Mhealth Uhealth 2013 Jul;1(2):e8 [FREE Full text] [CrossRef] [Medline]
- Meyer J, Hein A. Live long and prosper: Potentials of low-cost consumer devices for the prevention of cardiovascular diseases. Med 2 0 2013 Aug;2(2) [FREE Full text] [CrossRef] [Medline]
- Lyons E, Lewis Z, Mayrsohn B, Rowland J. Behavior change techniques implemented in electronic lifestyle activity monitors: A systematic content analysis. J Med Internet Res 2014;16(8) [FREE Full text] [CrossRef] [Medline]
- Consolvo S, McDonald D, Toscos T, Chen MY, Froehlich J, Harrison B, et al. Activity Sensing in the Wild: A Field Trial of UbiFit Garden. New York: ACM Press; 2008. URL: https://www.cs.umd.edu/~jonf/publications/Consolvo_ActivitySensingInTheWild-AFieldTrialOfUbiFitGarden_CHI2008.pdf [accessed 2015-12-14] [WebCite Cache]
- Klasnja P, Consolvo S, Pratt W. How to Evaluate Technologies for Health Behavior Change in HCI Research. New York: ACM Press; 2011. CHI 2011 URL: http://faculty.washington.edu/wpratt/Publications/Evaluting%20tech%20for%20behavior%20change-cr-FINAL.pdf [accessed 2015-12-14] [WebCite Cache]
- Li I. Beyond counting steps: Using context to improving monitoring of physical activity. : UbiComp 2009; 2009 Presented at: 11th International Conference on Ubiquitous Computing (Proc. UbiComp’09); 2009; Orlando, FL URL: https://ianli.com/publications/2009-ianli-ubicomp-beyond-counting-steps.pdf
- Tudor-Locke C. Taking Steps Toward Increased Physical Activity: Using Pedometers to Measure and Motivate. Rockville, MD: President’s Council on Physical Fitness and Sports; 2002 Jun. URL: https://www.presidentschallenge.org/informed/digest/docs/200206digest.pdf [accessed 2015-12-14] [WebCite Cache]
- Michie S, Ashford S, Sniehotta FF, Dombrowski SU, Bishop A, French DP. A refined taxonomy of behaviour change techniques to help people change their physical activity and healthy eating behaviours: The CALO-RE taxonomy. Psychol Health 2011 Nov;26(11):1479-1498. [CrossRef] [Medline]
- Fogg B. Persuasive Technology: Using Computers to Change What We Think and Do. San Francisco, CA: Morgan Kaufmann; 2003.
- Klasnja P, Consolvo S, Pratt W. How to Evaluate Technologies for Health Behavior Change in HCI Research. In: CHI. 2011 Presented at: CHI 2011; May 7–12, 2011; Vancouver, Canada URL: http://faculty.washington.edu/wpratt/Publications/Evaluting%20tech%20for%20behavior%20change-cr-FINAL.pdf
- Reed VA, Schifferdecker KE, Rezaee ME, O’Connor S, Larson RJ. The effect of computers for weight loss: A systematic review and meta-analysis of randomized trials. J Gen Intern Med 2012 Jan;27(1):99-108 [FREE Full text] [CrossRef] [Medline]
- Wieland L, Falzon L, Sciamanna C, Trudeau K, Brodney S, Schwartz J, et al. Interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people. Cochrane Database Syst Rev 2012;8 [FREE Full text] [CrossRef] [Medline]
- Hartmann-Boyce J, Johns DJ, Jebb SA, Aveyard P, Behavioural Weight Management Review Group. Effect of behavioural techniques and delivery mode on effectiveness of weight management: Systematic review, meta-analysis and meta-regression. Obes Rev 2014 Jul;15(7):598-609 [FREE Full text] [CrossRef] [Medline]
- Grindrod KA, Li M, Gates A. Evaluating user perceptions of mobile medication management applications with older adults: A usability study. JMIR Mhealth Uhealth 2014;2(1):e11 [FREE Full text] [CrossRef] [Medline]
- Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): A 32-item checklist for interviews and focus groups. Int J Qual Health Care 2007 Dec;19(6):349-357 [FREE Full text] [CrossRef] [Medline]
- Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: A comparison of two theoretical models. Manage Sci 1989;35(8):982-1003.
- Canadian Society for Exercise Physiology. PAR-Q & You (Revised 2002). 2014 Jun 20. URL: http://www.csep.ca/cmfiles/publications/parq/par-q.pdf [accessed 2015-12-14] [WebCite Cache]
- Craig C, Marshall A, Sjöström M, Bauman A, Booth M, Ainsworth B, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003 Aug;35(8):1381-1395. [CrossRef] [Medline]
- Rogers EM. Diffusion of Innovations. 5th edition. New York: The Free Press; 2003.
- Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 1989 Sep;13(3):319-340. [CrossRef]
- Haddon L. Domestication and mobile telephony. In: Katz J, editor. Machines that Become Us: The Social Context of Personal Communication Technology. New Brunswick, NJ: Transaction Publishers; 2003:43-56.
- Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: Toward a unified view. MIS Q 2003;27(3):425-478 [FREE Full text]
- Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol 2006 Jan;3(2):77-101. [CrossRef]
- Guest G, MacQueen KM, Namey EE. Introduction to thematic analysis. In: Applied Thematic Analysis. London, UK: Sage; Nov 9, 2011:3-18.
- Martin PY. Grounded theory and organizational research. J Appl Behav Sci 1986 Apr 01;22(2):141-157. [CrossRef]
- Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: A comparison of two theoretical models. Manage Sci 1989 Aug;35(8):982-1003. [CrossRef]
- Mason M. Forum: Qualitative Social Research. 2010. Sample size and saturation in PhD Studies using qualitative interviews URL: http://www.qualitative-research.net/index.php/fqs/article/view/1428/3027 [accessed 2016-01-17] [WebCite Cache]
- Igbaria M, Iivari J. The effects of self-efficacy on computer usage. Omega 1995 Dec;23(6):587-605. [CrossRef]
- Pan C. Students’ attitude in a web-enhanced hybrid course: A structural equation modeling inquiry. J Educ Media Lib Sci 2003;41(2):181-194 [FREE Full text]
- Blaya J, Fraser HS, Holt B. E-health technologies show promise in developing countries. Health Aff 2010 Feb;29(2):244-251 [FREE Full text] [CrossRef] [Medline]
- Lindquist A, Johansson P, Petersson G, Saveman BI, Nilsson GC. The use of the personal digital assistant (PDA) among personnel and students in health care: A review. J Med Internet Res 2008;10(4):e31 [FREE Full text] [CrossRef] [Medline]
- Middelweerd E, Mollee JS, van der Wal CN, Brug J, Te Velde Saskia J. Apps to promote physical activity among adults: A review and content analysis. Int J Behav Nutr Phys Act 2014;11:97 [FREE Full text] [CrossRef] [Medline]
- Kailas A, Chong CC, Watanabe F. From mobile phones to personal wellness dashboards. IEEE Pulse 2010;1(1):57-63. [CrossRef] [Medline]
- Burton C, Weller D, Sharpe M. Are electronic diaries useful for symptoms research? A systematic review. J Psychosom Res 2007 May;62(5):553-561. [CrossRef] [Medline]
- Fjeldsoe BS, Marshall AL, Miller YD. Behavior change interventions delivered by mobile telephone short-message service. Am J Prev Med 2009 Feb;36(2):165-173. [CrossRef] [Medline]
- Lim MS, Hocking JS, Hellard ME, Aitken CK. SMS STI: A review of the uses of mobile phone text messaging in sexual health. Int J STD AIDS 2008 May;19(5):287-290. [CrossRef] [Medline]
- Lane S, Heddle N, Arnold E, Walker I. A review of randomized controlled trials comparing the effectiveness of hand held computers with paper methods for data collection. BMC Med Inform Decis Mak 2006;6:23 [FREE Full text] [CrossRef] [Medline]
- Free C, Phillips G, Felix L, Galli L, Patel V, Edwards P. The effectiveness of M-health technologies for improving health and health services: A systematic review protocol. BMC Res Notes 2010;3:250 [FREE Full text] [CrossRef] [Medline]
- Free C, Phillips G, Felix L, Galli L, Patel V, Edwards P. The effectiveness of M-health technologies for improving health and health services: A systematic review protocol. BMC Res Notes 2010;3:250 [FREE Full text] [CrossRef] [Medline]
- Terry M. Medical apps for smartphones. Telemed J E Health 2010;16(1):17-22. [CrossRef] [Medline]
- Boulos MN, Brewer AC, Karimkhani C, Buller DB, Dellavalle RP. Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online J Public Health Inform 2014;5(3):229 [FREE Full text] [CrossRef] [Medline]
- Berlin JE, Storti KL, Brach JS. Using activity monitors to measure physical activity in free-living conditions. Phys Ther 2006 Aug;86(8):1137-1145 [FREE Full text] [Medline]