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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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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. |
format | Online Article Text |
id | pubmed-8431714 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT yangqinghua theorybasedsocialandnonsocialengagementfeaturesinsmokingcessationmobileappsacontentanalysis |