Determinants of Fitness App Usage and Moderating Impacts of Education-, Motivation-, and Gamification-Related App Features on Physical Activity Intentions: Cross-sectional Survey Study

Abstract

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.

A meta-analysis of eWallet adoption using the UTAUT model

“…, 2016), health information technology (cf., Kijsanayotin et al. , 2009), electronic document management systems (cf., Ayaz and Yanartaş, 2020), mobile learning adoption (cf., Chao, 2019), physical activity apps (cf., Yang and Koenigstorfer, 2021) and a host of other related technological developments. As a result, the body of primary studies that have used the UTAUT and UTAUT2 is extensive and its usage to specifically explore the behavioral intentions to use eWallets is not an exception.…”

“…Mew and Millan, 2021;Ramli and Hamzah, 2021;Teng and Khong, 2021;Tun, 2020;U.S. Payments Forum, 2018;Yang et al, 2021). For the purpose of this study, we focus specifically on eWallet as an encompassing technological concept that facilitates mobile payments, using an eWallet system, and aim to understand the influence of specific antecedents on the intention to use eWallets, from the (existing or potential) customer's point of view.…”

“…They have been applied to a wide array of recently developed technologies. More specifically, these models have been applied to technologies including mobile banking (cf., Oliveira et al, 2014), computer security (cf., Khalilzadeh et al, 2017), e-government (cf., Rodrigues et al, 2016, health information technology (cf., Kijsanayotin et al, 2009), electronic document management systems (cf., Ayaz and Yanartas ¸, 2020), mobile learning adoption (cf., Chao, 2019), physical activity apps (cf., Yang and Koenigstorfer, 2021) and a host of other related technological developments. As a result, the body of primary studies that have used the UTAUT and UTAUT2 is extensive and its usage to specifically explore the behavioral intentions to use eWallets is not an exception.…”

Influencing Factors of College Students’ Use of Sports Apps in Mandatory Situations: Based on UTAUT and SDT

“…Second, the UTAUT was developed to integrate information and communication technology (ICT) research and theory into a comprehensive theoretical model [ 26 , 29 ], while sports apps are products of ICT. Furthermore, other studies [ 11 , 30 , 31 ] have demonstrated the value of the UTAUT and its expanded model in the research of sports apps. Third, the UTAUT integrated the core elements of eight models and theories when it was created.…”

A retrospective real-world observational pilot analysis of Waya: a self-monitoring fitness app in Germany

“…Self-monitoring, although a relatively recent development, has been increasingly integrated into behavioral weight loss apps [ 14 ]. The relative ease with which users can incorporate dietary and lifestyle guidance into their day-to-day lives appears to be an appealing aspect of such mobile apps, along with a perceived ‘gamification’ of an individual’s approach to their health [ 15 , 16 ]. Existing data suggest that users are drawn to the achievement-related features (such as goal setting or monitoring) used in fitness apps, which might be seen as difficult to measure or mimic in nonapp-based approaches to weight loss [ 16 ], alongside the potential social factors found to be associated with continued and consistent use of such apps [ 15 ], offering an additional form of motivation, which might not be present in traditional forms of physical activity.…”