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Social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach
Research has shown that persuasive technologies aimed at behavior change will be more effective if behavioral determinants are targeted. However, research on the determinants of bodyweight exercise performance in the context of behavior modeling in fitness apps is scarce. To bridge this gap, we cond...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6240967/ https://www.ncbi.nlm.nih.gov/pubmed/30479828 http://dx.doi.org/10.1177/2055207618811555 |
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author | Oyibo, Kiemute Adaji, Ifeoma Vassileva, Julita |
author_facet | Oyibo, Kiemute Adaji, Ifeoma Vassileva, Julita |
author_sort | Oyibo, Kiemute |
collection | PubMed |
description | Research has shown that persuasive technologies aimed at behavior change will be more effective if behavioral determinants are targeted. However, research on the determinants of bodyweight exercise performance in the context of behavior modeling in fitness apps is scarce. To bridge this gap, we conducted an empirical study among 659 participants resident in North America using social cognitive theory as a framework to uncover the determinants of the performance of bodyweight exercise behavior. To contextualize our study, we modeled, in a hypothetical context, two popular bodyweight exercise behaviors – push ups and squats – featured in most fitness apps on the market using a virtual coach (aka behavior model). Our social cognitive model shows that users’ perceived self-efficacy (β(T) = 0.23, p < 0.001) and perceived social support (β(T) = 0.23, p < 0.001) are the strongest determinants of bodyweight exercise behavior, followed by outcome expectation (β(T) = 0.11, p < 0.05). However, users’ perceived self-regulation (β(T) = –0.07, p = n.s.) turns out to be a non-determinant of bodyweight exercise behavior. Comparatively, our model shows that perceived self-efficacy has a stronger direct effect on exercise behavior for men (β = 0.31, p < 0.001) than for women (β = 0.10, p = n.s.). In contrast, perceived social support has a stronger direct effect on exercise behavior for women (β = 0.15, p < 0.05) than for men (β = −0.01, p = n.s.). Based on these findings and qualitative analysis of participants’ comments, we provide a set of guidelines for the design of persuasive technologies for promoting regular exercise behavior. |
format | Online Article Text |
id | pubmed-6240967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-62409672018-11-26 Social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach Oyibo, Kiemute Adaji, Ifeoma Vassileva, Julita Digit Health Original Research Research has shown that persuasive technologies aimed at behavior change will be more effective if behavioral determinants are targeted. However, research on the determinants of bodyweight exercise performance in the context of behavior modeling in fitness apps is scarce. To bridge this gap, we conducted an empirical study among 659 participants resident in North America using social cognitive theory as a framework to uncover the determinants of the performance of bodyweight exercise behavior. To contextualize our study, we modeled, in a hypothetical context, two popular bodyweight exercise behaviors – push ups and squats – featured in most fitness apps on the market using a virtual coach (aka behavior model). Our social cognitive model shows that users’ perceived self-efficacy (β(T) = 0.23, p < 0.001) and perceived social support (β(T) = 0.23, p < 0.001) are the strongest determinants of bodyweight exercise behavior, followed by outcome expectation (β(T) = 0.11, p < 0.05). However, users’ perceived self-regulation (β(T) = –0.07, p = n.s.) turns out to be a non-determinant of bodyweight exercise behavior. Comparatively, our model shows that perceived self-efficacy has a stronger direct effect on exercise behavior for men (β = 0.31, p < 0.001) than for women (β = 0.10, p = n.s.). In contrast, perceived social support has a stronger direct effect on exercise behavior for women (β = 0.15, p < 0.05) than for men (β = −0.01, p = n.s.). Based on these findings and qualitative analysis of participants’ comments, we provide a set of guidelines for the design of persuasive technologies for promoting regular exercise behavior. SAGE Publications 2018-11-14 /pmc/articles/PMC6240967/ /pubmed/30479828 http://dx.doi.org/10.1177/2055207618811555 Text en © The Author(s) 2018 http://creativecommons.org/licenses/by/4.0/ Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Oyibo, Kiemute Adaji, Ifeoma Vassileva, Julita Social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach |
title | Social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach |
title_full | Social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach |
title_fullStr | Social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach |
title_full_unstemmed | Social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach |
title_short | Social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach |
title_sort | social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6240967/ https://www.ncbi.nlm.nih.gov/pubmed/30479828 http://dx.doi.org/10.1177/2055207618811555 |
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