TY - JOUR
T1 - Determinants of fitness app usage and moderating impacts of education-, motivation-, and gamification-related app features on physical activity intentions
T2 - Cross-sectional survey study
AU - Yang, Yanxiang
AU - Koenigstorfer, Joerg
N1 - Publisher Copyright:
© Yanxiang Yang, Joerg Koenigstorfer. Originally published in the Journal of Medical Internet Research (https://www.jmir.org),13.07.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
PY - 2021/7
Y1 - 2021/7
N2 - Background: Smartphone fitness apps are considered promising tools for promoting physical activity and health. However, it is unclear which user-perceived factors and app features encourage users to download apps with the intention of being physically active. Objective: Building on the second version of the Unified Theory of Acceptance and Use of Technology, this study aims to examine the association of the seven determinants of the second version of the Unified Theory of Acceptance and Use of Technology with the app usage intentions of the individuals and their behavioral intentions of being physically active as well as the moderating effects of different smartphone fitness app features (ie, education, motivation, and gamification related) and individual differences (ie, age, gender, and experience) on these intentions. Methods: Data from 839 US residents who reported having used at least one smartphone fitness app were collected via a web-based survey. A confirmatory factor analysis was performed, and path modeling was used to test the hypotheses and explore the influence of moderators on structural relationships. Results: The determinants explain 76% of the variance in the behavioral intention to use fitness apps. Habit (β=.42; P<.001), performance expectancy (β=.36; P<.001), facilitating conditions (β=.15; P<.001), price value (β=.13; P<.001), and effort expectancy (β=.09; P=.04) were positively related to behavioral intention to use fitness apps, whereas social influence and hedonic motivation were nonsignificant predictors. Behavioral intentions to use fitness apps were positively related to intentions of being physically active (β=.12; P<.001; R2=0.02). Education-related app features moderated the association between performance expectancy and habit and app usage intentions; motivation-related features moderated the association of performance expectancy, facilitating conditions, and habit with usage intentions; and gamification-related features moderated the association between hedonic motivation and usage intentions. Age moderated the association between effort expectancy and usage intentions, and gender moderated the association between performance expectancy and habit and usage intentions. User experience was a nonsignificant moderator. Follow-up tests were used to describe the nature of significant interaction effects. Conclusions: This study identifies the drivers of the use of fitness apps. Smartphone app features should be designed to increase the likelihood of app usage, and hence physical activity, by supporting users in achieving their goals and facilitating habit formation. Target group–specific preferences for education-, motivation-, and gamification-related app features, as well as age and gender differences, should be considered. Performance expectancy had a high predictive power for intended usage for male (vs female) users who appreciated motivation-related features. Thus, apps targeting these user groups should focus on goal achievement–related features (eg, goal setting and monitoring). Future research could examine the mechanisms of these moderation effects and their long-term influence on physical activity.
AB - Background: Smartphone fitness apps are considered promising tools for promoting physical activity and health. However, it is unclear which user-perceived factors and app features encourage users to download apps with the intention of being physically active. Objective: Building on the second version of the Unified Theory of Acceptance and Use of Technology, this study aims to examine the association of the seven determinants of the second version of the Unified Theory of Acceptance and Use of Technology with the app usage intentions of the individuals and their behavioral intentions of being physically active as well as the moderating effects of different smartphone fitness app features (ie, education, motivation, and gamification related) and individual differences (ie, age, gender, and experience) on these intentions. Methods: Data from 839 US residents who reported having used at least one smartphone fitness app were collected via a web-based survey. A confirmatory factor analysis was performed, and path modeling was used to test the hypotheses and explore the influence of moderators on structural relationships. Results: The determinants explain 76% of the variance in the behavioral intention to use fitness apps. Habit (β=.42; P<.001), performance expectancy (β=.36; P<.001), facilitating conditions (β=.15; P<.001), price value (β=.13; P<.001), and effort expectancy (β=.09; P=.04) were positively related to behavioral intention to use fitness apps, whereas social influence and hedonic motivation were nonsignificant predictors. Behavioral intentions to use fitness apps were positively related to intentions of being physically active (β=.12; P<.001; R2=0.02). Education-related app features moderated the association between performance expectancy and habit and app usage intentions; motivation-related features moderated the association of performance expectancy, facilitating conditions, and habit with usage intentions; and gamification-related features moderated the association between hedonic motivation and usage intentions. Age moderated the association between effort expectancy and usage intentions, and gender moderated the association between performance expectancy and habit and usage intentions. User experience was a nonsignificant moderator. Follow-up tests were used to describe the nature of significant interaction effects. Conclusions: This study identifies the drivers of the use of fitness apps. Smartphone app features should be designed to increase the likelihood of app usage, and hence physical activity, by supporting users in achieving their goals and facilitating habit formation. Target group–specific preferences for education-, motivation-, and gamification-related app features, as well as age and gender differences, should be considered. Performance expectancy had a high predictive power for intended usage for male (vs female) users who appreciated motivation-related features. Thus, apps targeting these user groups should focus on goal achievement–related features (eg, goal setting and monitoring). Future research could examine the mechanisms of these moderation effects and their long-term influence on physical activity.
KW - Determinants of app usage
KW - Education-related app features
KW - Fitness applications
KW - Gamification-related app features
KW - MHealth
KW - Mobile phone
KW - Motivation-related app features
KW - Physical activity
KW - Smartphone
KW - Technology acceptance
KW - Unified Theory of Acceptance and Use of Technology 2
UR - http://www.scopus.com/inward/record.url?scp=85110712246&partnerID=8YFLogxK
U2 - 10.2196/26063
DO - 10.2196/26063
M3 - Review article
C2 - 34255656
AN - SCOPUS:85110712246
SN - 1438-8871
VL - 23
JO - Journal of Medical Internet Research
JF - Journal of Medical Internet Research
IS - 7
M1 - e26063
ER -