Social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach. (November 2018)

• Record Type: Journal Article
• Authors: Oyibo, Kiemute; Adaji, Ifeoma; Vassileva, Julita
• Is Part Of: Digital health. Volume 4(2018)
• Publication Date: 2018-11
• Subjects: Social cognitive model -- bodyweight exercise -- behavior modeling -- fitness app -- persuasive technology -- gender difference; Medical care -- Data processing -- Periodicals; Medical informatics -- Periodicals; 362.10285
• DOI: 10.1177/2055207618811555
• Languages: English
• ISSNs: 2055-2076

Abstract

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 (βT = 0.23, p < 0.001) and perceived social support (βT = 0.23, p < 0.001) are the strongest determinants of bodyweight exercise behavior, followed by outcome expectation (βT = 0.11, p < 0.05). However, users' perceived self-regulation (βT = –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.