Understanding and Predicting the Adoption of Fitness Mobile Apps: Evidence from China

Increasing global interest in diet and fitness mobile applications (apps) has prompted the question: What are the factors affecting users' adoption and usage behaviors on a specific fitness app? By combining the unified theory of acceptance and use of technology (UTAUT) with the health belief model (HBM), and including risk perception of information technology with the farsighted planner and myopic doer from the theory of self-control, we explore the understanding of this academic question. We analyzed data from 8,840 users of Boohee, a diet and fitness app (ranked first in the weight-loss category on the App Store in China). Structural equation modeling revealed that self-efficacy as well as the perceived benefits, barriers, and threats of weight loss significantly influence a fitness app's performance expectancy, which, in turn, predicts users' intention to adopt it. Furthermore, actual usage behavior (i.e., diet, exercise, weight, and login records within 30 days after respondents completed the questionnaire) is positively affected by weight-loss intention and behavioral intention to use the app and negatively affected by users' risk perception. The main findings of this research could help healthcare practitioners and app developers find better ways to encourage people to adopt health apps for various reasons. App developers should attach more importance to users' actual continuous use behavior than to their intention to use an app. They should provide sufficient introductory information about their apps, thereby reducing users' risk perception and generating reasonable performance expectancy of the app, so as to improve users' actual continuous use behavior.

Automated summary

This research explores the factors influencing users' adoption and usage behaviors on a fitness app by combining various theories. The main findings suggest that users' self-efficacy, perceived benefits, barriers, threats of weight loss, and risk perception significantly impact their intention to adopt and actual usage behavior. App developers should focus on providing sufficient introductory information to reduce users' risk perception and improve actual continuous use behavior.