Activity Trackers Implement Different Behavior Change Techniques for Activity, Sleep, and Sedentary Behaviors

Mitch Duncan; Beatrice Murawski; Camille E Short; Amanda L Rebar; Stephanie Schoeppe; Stephanie Alley; Corneel Vandelanotte; Morwenna Kirwan

doi:10.2196/ijmr.6685

Activity Trackers Implement Different Behavior Change Techniques for Activity, Sleep, and Sedentary Behaviors

Interact J Med Res. 2017 Aug 14;6(2):e13. doi: 10.2196/ijmr.6685.

Authors

Mitch Duncan¹, Beatrice Murawski¹, Camille E Short², Amanda L Rebar³, Stephanie Schoeppe³, Stephanie Alley³, Corneel Vandelanotte³, Morwenna Kirwan⁴

Affiliations

¹ School of Medicine & Public Health, Priority Research Centre for Physical Activity and Nutrition, Faculty of Health and Medicine, The University of Newcastle, Callaghan, Australia.
² Freemasons Foundation Centre for Men's Health, School of Medicine, University of Adelaide, Adelaide, Australia.
³ Physical Activity Research Group, School of Medical, Health and Applied Sciences, Central Queensland University, Rockhampton, Australia.
⁴ School of Science and Health, Western Sydney University, Campbelltown, Australia.

Abstract

Background: Several studies have examined how the implementation of behavior change techniques (BCTs) varies between different activity trackers. However, activity trackers frequently allow tracking of activity, sleep, and sedentary behaviors; yet, it is unknown how the implementation of BCTs differs between these behaviors.

Objective: The aim of this study was to assess the number and type of BCTs that are implemented by wearable activity trackers (self-monitoring systems) in relation to activity, sleep, and sedentary behaviors and to determine whether the number and type of BCTs differ between behaviors.

Methods: Three self-monitoring systems (Fitbit [Charge HR], Garmin [Vivosmart], and Jawbone [UP3]) were each used for a 1-week period in August 2015. Each self-monitoring system was used by two of the authors (MJD and BM) concurrently. The Coventry, Aberdeen, and London-Refined (CALO-RE) taxonomy was used to assess the implementation of 40 BCTs in relation to activity, sleep, and sedentary behaviors. Discrepancies in ratings were resolved by discussion, and interrater agreement in the number of BCTs implemented was assessed using kappa statistics.

Results: Interrater agreement ranged from 0.64 to 1.00. From a possible range of 40 BCTs, the number of BCTs present for activity ranged from 19 (Garmin) to 33 (Jawbone), from 4 (Garmin) to 29 (Jawbone) for sleep, and 0 (Fitbit) to 10 (Garmin) for sedentary behavior. The average number of BCTs implemented was greatest for activity (n=26) and smaller for sleep (n=14) and sedentary behavior (n=6).

Conclusions: The number and type of BCTs implemented varied between each of the systems and between activity, sleep, and sedentary behaviors. This provides an indication of the potential of these systems to change these behaviors, but the long-term effectiveness of these systems to change activity, sleep, and sedentary behaviors remains unknown.

Keywords: adult, mobile applications; behavior change; exercise; fitness trackers; health behavior; public health; sleep.

©Mitch Duncan, Beatrice Murawski, Camille E Short, Amanda L Rebar, Stephanie Schoeppe, Stephanie Alley, Corneel Vandelanotte, Morwenna Kirwan. Originally published in the Interactive Journal of Medical Research (http://www.i-jmr.org/), 14.08.2017.