Behavior change techniques in mobile applications for sedentary behavior

Objective Mobile applications (apps) are increasingly being utilized in health behavior change interventions. To determine the presence of underlying behavior change mechanisms, apps for physical activity have been coded for behavior change techniques (BCTs). However, apps for sedentary behavior hav...

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Main Authors: Emily E Dunn, Heather L Gainforth, Jennifer E Robertson-Wilson
Format: Article
Language:English
Published: SAGE Publishing 2018-07-01
Series:Digital Health
Online Access:https://doi.org/10.1177/2055207618785798
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spelling doaj-2b66eaa6dba94f0ea08375cf4f9f81db2020-11-25T03:22:47ZengSAGE PublishingDigital Health2055-20762018-07-01410.1177/2055207618785798Behavior change techniques in mobile applications for sedentary behaviorEmily E Dunn0Heather L Gainforth1Jennifer E Robertson-Wilson2Department of Kinesiology & Physical Education, Wilfrid Laurier University, CanadaSchool of Health & Exercise Sciences, University of British Columbia (Okanagan), CanadaDepartment of Kinesiology & Physical Education, Wilfrid Laurier University, CanadaObjective Mobile applications (apps) are increasingly being utilized in health behavior change interventions. To determine the presence of underlying behavior change mechanisms, apps for physical activity have been coded for behavior change techniques (BCTs). However, apps for sedentary behavior have yet to be assessed for BCTs. Thus, the purpose of the present study was to review apps designed to decrease sedentary time and determine the presence of BCTs. Methods Systematic searches of the iTunes App and Google Play stores were completed using keyword searches. Two reviewers independently coded free ( n  = 36) and paid ( n  = 14) app descriptions using a taxonomy of 93 BCTs (December 2016–January 2017). A subsample ( n  = 4) of free apps were trialed for one week by the reviewers and coded for the presence of BCTs (February 2017). Results In the free and paid app descriptions, only 10 of 93 BCTs were present with a mean of 2.42 BCTs (range 0–6) per app. The BCTs coded most frequently were “prompts/cues” ( n  = 43), “information about health consequences” ( n  = 31), and “self-monitoring of behavior” ( n  = 17). For the four free apps that were trialed, three additional BCTs were coded that were not coded in the descriptions: “graded tasks,” “focus on past successes,” and “behavior substitution.” Conclusions These sedentary behavior apps have fewer BCTs compared with physical activity apps and traditional (i.e., non-app) physical activity and healthy eating interventions. The present study sheds light on the behavior change potential of sedentary behavior apps and provides practical insight about coding for BCTs in apps.https://doi.org/10.1177/2055207618785798
collection DOAJ
language English
format Article
sources DOAJ
author Emily E Dunn
Heather L Gainforth
Jennifer E Robertson-Wilson
spellingShingle Emily E Dunn
Heather L Gainforth
Jennifer E Robertson-Wilson
Behavior change techniques in mobile applications for sedentary behavior
Digital Health
author_facet Emily E Dunn
Heather L Gainforth
Jennifer E Robertson-Wilson
author_sort Emily E Dunn
title Behavior change techniques in mobile applications for sedentary behavior
title_short Behavior change techniques in mobile applications for sedentary behavior
title_full Behavior change techniques in mobile applications for sedentary behavior
title_fullStr Behavior change techniques in mobile applications for sedentary behavior
title_full_unstemmed Behavior change techniques in mobile applications for sedentary behavior
title_sort behavior change techniques in mobile applications for sedentary behavior
publisher SAGE Publishing
series Digital Health
issn 2055-2076
publishDate 2018-07-01
description Objective Mobile applications (apps) are increasingly being utilized in health behavior change interventions. To determine the presence of underlying behavior change mechanisms, apps for physical activity have been coded for behavior change techniques (BCTs). However, apps for sedentary behavior have yet to be assessed for BCTs. Thus, the purpose of the present study was to review apps designed to decrease sedentary time and determine the presence of BCTs. Methods Systematic searches of the iTunes App and Google Play stores were completed using keyword searches. Two reviewers independently coded free ( n  = 36) and paid ( n  = 14) app descriptions using a taxonomy of 93 BCTs (December 2016–January 2017). A subsample ( n  = 4) of free apps were trialed for one week by the reviewers and coded for the presence of BCTs (February 2017). Results In the free and paid app descriptions, only 10 of 93 BCTs were present with a mean of 2.42 BCTs (range 0–6) per app. The BCTs coded most frequently were “prompts/cues” ( n  = 43), “information about health consequences” ( n  = 31), and “self-monitoring of behavior” ( n  = 17). For the four free apps that were trialed, three additional BCTs were coded that were not coded in the descriptions: “graded tasks,” “focus on past successes,” and “behavior substitution.” Conclusions These sedentary behavior apps have fewer BCTs compared with physical activity apps and traditional (i.e., non-app) physical activity and healthy eating interventions. The present study sheds light on the behavior change potential of sedentary behavior apps and provides practical insight about coding for BCTs in apps.
url https://doi.org/10.1177/2055207618785798
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