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Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis

Despite the ubiquity of smartphone ownership and the increasing integration of social engagement features in smoking cessation apps to engage users, the social and non-social engagement features that are present in current smoking cessation apps and the effectiveness of these features in engaging us...

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Detalles Bibliográficos
Autor principal: Yang, Qinghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8431714/
https://www.ncbi.nlm.nih.gov/pubmed/34501696
http://dx.doi.org/10.3390/ijerph18179106
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author Yang, Qinghua
author_facet Yang, Qinghua
author_sort Yang, Qinghua
collection PubMed
description Despite the ubiquity of smartphone ownership and the increasing integration of social engagement features in smoking cessation apps to engage users, the social and non-social engagement features that are present in current smoking cessation apps and the effectiveness of these features in engaging users remain understudied. To fill the gap in the literature, a content analysis of free and paid smoking cessation mobile apps was conducted to examine (a) the presence of social features (i.e., social support, social announcement, and social referencing) and non-social engagement features (e.g., personal environmental changes, goal setting, progress tracking, reinforcement tracking, self-monitoring, and personalized recommendations) and (b) their relationships with user engagement scores measured by the Mobile App Rating Scale. In this study, 28.2% of the smoking cessation apps enable social announcement and 8.1% offered the social support feature. Only two apps provided a social referencing feature (1.3%). No app included reinforcement tracking, with the percentage of other non-social engagement features ranging from 9.4% to 49.0%. Social support (β = 0.30, p < 0.001), social announcement (β = 0.21, p < 0.05), and social referencing (β = 0.18, p < 0.05) were significant predictors of user engagement. Regarding the non-social engagement features, personal environment changes (β = 0.38, p < 0.001), progress tracking (β = 0.18, p < 0.05), and personalized recommendations (β = 0.37, p < 0.001) significantly predicted user engagement. The findings not only contribute to the mobile communication literature by applying and extending the theory-based mobile health apps engagement typology, but also inform the future architecture design of smoking cessation mobile apps.
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spelling pubmed-84317142021-09-11 Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis Yang, Qinghua Int J Environ Res Public Health Article Despite the ubiquity of smartphone ownership and the increasing integration of social engagement features in smoking cessation apps to engage users, the social and non-social engagement features that are present in current smoking cessation apps and the effectiveness of these features in engaging users remain understudied. To fill the gap in the literature, a content analysis of free and paid smoking cessation mobile apps was conducted to examine (a) the presence of social features (i.e., social support, social announcement, and social referencing) and non-social engagement features (e.g., personal environmental changes, goal setting, progress tracking, reinforcement tracking, self-monitoring, and personalized recommendations) and (b) their relationships with user engagement scores measured by the Mobile App Rating Scale. In this study, 28.2% of the smoking cessation apps enable social announcement and 8.1% offered the social support feature. Only two apps provided a social referencing feature (1.3%). No app included reinforcement tracking, with the percentage of other non-social engagement features ranging from 9.4% to 49.0%. Social support (β = 0.30, p < 0.001), social announcement (β = 0.21, p < 0.05), and social referencing (β = 0.18, p < 0.05) were significant predictors of user engagement. Regarding the non-social engagement features, personal environment changes (β = 0.38, p < 0.001), progress tracking (β = 0.18, p < 0.05), and personalized recommendations (β = 0.37, p < 0.001) significantly predicted user engagement. The findings not only contribute to the mobile communication literature by applying and extending the theory-based mobile health apps engagement typology, but also inform the future architecture design of smoking cessation mobile apps. MDPI 2021-08-29 /pmc/articles/PMC8431714/ /pubmed/34501696 http://dx.doi.org/10.3390/ijerph18179106 Text en © 2021 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yang, Qinghua
Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis
title Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis
title_full Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis
title_fullStr Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis
title_full_unstemmed Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis
title_short Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis
title_sort theory-based social and non-social engagement features in smoking cessation mobile apps: a content analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8431714/
https://www.ncbi.nlm.nih.gov/pubmed/34501696
http://dx.doi.org/10.3390/ijerph18179106
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