Eimear C Morrissey1, Teresa K Corbett2, Jane C Walsh2, Gerard J Molloy2. 1. School of Psychology, National University of Ireland, Galway, Ireland. Electronic address: e.morrissey6@nuigalway.ie. 2. School of Psychology, National University of Ireland, Galway, Ireland.
Abstract
INTRODUCTION: There are a vast number of smartphone applications (apps) aimed at promoting medication adherence on the market; however, the theory and evidence base in terms of applying established health behavior change techniques underpinning these apps remains unclear. This study aimed to code these apps using the Behavior Change Technique Taxonomy (v1) for the presence or absence of established behavior change techniques. METHODS: The sample of apps was identified through systematic searches in both the Google Play Store and Apple App Store in February 2015. All apps that fell into the search categories were downloaded for analysis. The downloaded apps were screened with exclusion criteria, and suitable apps were reviewed and coded for behavior change techniques in March 2015. Two researchers performed coding independently. RESULTS: In total, 166 medication adherence apps were identified and coded. The number of behavior change techniques contained in an app ranged from zero to seven (mean=2.77). A total of 12 of a possible 96 behavior change techniques were found to be present across apps. The most commonly included behavior change techniques were "action planning" and "prompt/cues," which were included in 96% of apps, followed by "self-monitoring" (37%) and "feedback on behavior" (36%). CONCLUSIONS: The current extent to which established behavior change techniques are used in medication adherence apps is limited. The development of medication adherence apps may not have benefited from advances in the theory and practice of health behavior change.
INTRODUCTION: There are a vast number of smartphone applications (apps) aimed at promoting medication adherence on the market; however, the theory and evidence base in terms of applying established health behavior change techniques underpinning these apps remains unclear. This study aimed to code these apps using the Behavior Change Technique Taxonomy (v1) for the presence or absence of established behavior change techniques. METHODS: The sample of apps was identified through systematic searches in both the Google Play Store and Apple App Store in February 2015. All apps that fell into the search categories were downloaded for analysis. The downloaded apps were screened with exclusion criteria, and suitable apps were reviewed and coded for behavior change techniques in March 2015. Two researchers performed coding independently. RESULTS: In total, 166 medication adherence apps were identified and coded. The number of behavior change techniques contained in an app ranged from zero to seven (mean=2.77). A total of 12 of a possible 96 behavior change techniques were found to be present across apps. The most commonly included behavior change techniques were "action planning" and "prompt/cues," which were included in 96% of apps, followed by "self-monitoring" (37%) and "feedback on behavior" (36%). CONCLUSIONS: The current extent to which established behavior change techniques are used in medication adherence apps is limited. The development of medication adherence apps may not have benefited from advances in the theory and practice of health behavior change.
Authors: Taylor H Hoj; Emarie L Covey; Allyn C Jones; Amanda C Haines; P Cougar Hall; Benjamin T Crookston; Joshua H West Journal: JMIR Mhealth Uhealth Date: 2017-08-03 Impact factor: 4.773
Authors: Clemens Ernsting; Stephan U Dombrowski; Monika Oedekoven; Julie L O Sullivan; Melanie Kanzler; Adelheid Kuhlmey; Paul Gellert Journal: J Med Internet Res Date: 2017-04-05 Impact factor: 5.428