4.7 Article

Behavior Change Techniques Implemented in Electronic Lifestyle Activity Monitors: A Systematic Content Analysis

Journal

JOURNAL OF MEDICAL INTERNET RESEARCH
Volume 16, Issue 8, Pages -

Publisher

JMIR PUBLICATIONS, INC
DOI: 10.2196/jmir.3469

Keywords

electronic activity monitor; mobile; mhealth; physical activity; behavior change technique

Funding

  1. Office of Research on Women's Health, the Office of the Director, the National Institute of Allergy and Infectious Diseases [K12HD052023]
  2. Eunice Kennedy Shriver National Institute of Child Health and Human Development at the National Institutes of Health
  3. American Heart Association [13BGIA17110021]
  4. National Institute on Disability and Rehabilitation Research [H133G080120]
  5. Institute for Translational Sciences
  6. National Center for Advancing Translational Sciences, National Institutes of Health [UL1TR000071]
  7. Sealy Center on Aging and Claude D Pepper Older Americans Independence Center at the University of Texas Medical Branch [P30AG024832]
  8. US Agency for Healthcare Research and Quality [R24HS22134]

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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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