JMIR Publications

ABSTRACT

Background:

Smartphone fitness apps have been considered promising tools for promoting physical activity and health. Yet, the user-perceived factors and app features that influence users’ adoption of these apps and subsequent associations with intentions to be physically active remain uncertain.

Objective:

Building upon the second version of the Unified Theory of Acceptance and Use of Technology (UTAUT2), this study aims to examine the influence of the seven UTAUT2 determinants as well as the moderating effects of different smartphone fitness app features (i.e., education-, motivation-, and gamification-related) on individuals’ usage intentions and their behavioral intentions to be physically active.

Methods:

Data from 839 U.S. residents who reported having used at least one smartphone fitness app were collected via an online survey. A confirmatory factor analysis was performed and path modeling was used to test the hypotheses and explore the influence of app features on the structural relationships.

Results:

The seven determinants explain 73% of the variance in behavioral intentions to use fitness apps. Performance expectancy (β = .42, P < .001), effort expectancy (β = .10, P = .001), facilitating conditions (β = .09, P = .002), hedonic motivation (β = .06, P = .03), price value (β = .11, P < .001), and habit (β = .35, P < .001) are positively related to behavioral intentions to use fitness apps. There is no significant relation between social influence and behavioral intentions to use fitness apps. The behavioral intentions to use fitness apps relate positively to intentions to be physically active (β = .12, P < .001; R2 = .02). Education-related app features moderate the effect of performance expectancy; motivation-related features moderate the effects of performance expectancy, facilitating conditions, and habit; and gamification-related features moderate the effect of hedonic motivation on usage intentions. Follow-up tests are employed to describe the nature of the interaction effects.

Conclusions:

The study identifies important drivers of the usage 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 should be taken into account. For example, since performance expectancy has a high predictive power of intended usage for consumers who appreciate motivation-related features, apps targeting these users should focus on goal achievement-related features (e.g., goal setting and monitoring). Future research might look into the mechanisms of these moderation effects, and their long-term influence on physical activity levels.