David E Conroy1, Chih-Hsiang Yang2, Jaclyn P Maher2. 1. Department of Kinesiology, Pennsylvania State University, University Park, Pennsylvania. Electronic address: conroy@psu.edu. 2. Department of Kinesiology, Pennsylvania State University, University Park, Pennsylvania.
Abstract
BACKGROUND: Mobile applications (apps) have potential for helping people increase their physical activity, but little is known about the behavior change techniques marketed in these apps. PURPOSE: The aim of this study was to characterize the behavior change techniques represented in online descriptions of top-ranked apps for physical activity. METHODS: Top-ranked apps (n=167) were identified on August 28, 2013, and coded using the Coventry, Aberdeen and London-Revised (CALO-RE) taxonomy of behavior change techniques during the following month. Analyses were conducted during 2013. RESULTS: Most descriptions of apps incorporated fewer than four behavior change techniques. The most common techniques involved providing instruction on how to perform exercises, modeling how to perform exercises, providing feedback on performance, goal-setting for physical activity, and planning social support/change. A latent class analysis revealed the existence of two types of apps, educational and motivational, based on their configurations of behavior change techniques. CONCLUSIONS: Behavior change techniques are not widely marketed in contemporary physical activity apps. Based on the available descriptions and functions of the observed techniques in contemporary health behavior theories, people may need multiple apps to initiate and maintain behavior change. This audit provides a starting point for scientists, developers, clinicians, and consumers to evaluate and enhance apps in this market.
BACKGROUND: Mobile applications (apps) have potential for helping people increase their physical activity, but little is known about the behavior change techniques marketed in these apps. PURPOSE: The aim of this study was to characterize the behavior change techniques represented in online descriptions of top-ranked apps for physical activity. METHODS: Top-ranked apps (n=167) were identified on August 28, 2013, and coded using the Coventry, Aberdeen and London-Revised (CALO-RE) taxonomy of behavior change techniques during the following month. Analyses were conducted during 2013. RESULTS: Most descriptions of apps incorporated fewer than four behavior change techniques. The most common techniques involved providing instruction on how to perform exercises, modeling how to perform exercises, providing feedback on performance, goal-setting for physical activity, and planning social support/change. A latent class analysis revealed the existence of two types of apps, educational and motivational, based on their configurations of behavior change techniques. CONCLUSIONS: Behavior change techniques are not widely marketed in contemporary physical activity apps. Based on the available descriptions and functions of the observed techniques in contemporary health behavior theories, people may need multiple apps to initiate and maintain behavior change. This audit provides a starting point for scientists, developers, clinicians, and consumers to evaluate and enhance apps in this market.
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