Chair of Sport and Health Management, Technical University of Munich, Munich, Germany.
J Med Internet Res. 2021 Jul 13;23(7):e26063. doi: 10.2196/26063.
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.
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.
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.
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; R=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.
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.
智能手机健身应用程序被认为是促进身体活动和健康的有前途的工具。然而,尚不清楚哪些用户感知因素和应用程序功能鼓励用户下载旨在进行身体活动的应用程序。
本研究以第二版统一接受和使用技术理论为基础,旨在检验第二版统一接受和使用技术理论的七个决定因素与个体的应用程序使用意图及其身体活动的行为意图之间的关联,以及不同智能手机健身应用程序功能(即教育、动机和游戏化相关)和个体差异(即年龄、性别和经验)对这些意图的调节作用。
通过网络调查收集了 839 名报告至少使用过一种智能手机健身应用程序的美国居民的数据。进行了验证性因素分析,并使用路径建模来检验假设并探讨调节因素对结构关系的影响。
决定因素解释了健身应用程序使用意图的 76%的方差。习惯(β=.42;P<.001)、绩效预期(β=.36;P<.001)、便利条件(β=.15;P<.001)、价格价值(β=.13;P<.001)和努力期望(β=.09;P=.04)与健身应用程序使用意图呈正相关,而社会影响和享乐动机则没有显著预测作用。使用健身应用程序的意图与进行身体活动的意图呈正相关(β=.12;P<.001;R=0.02)。教育相关应用功能调节了绩效预期与习惯和应用使用意图之间的关系;动机相关特征调节了绩效预期、便利条件和习惯与使用意图之间的关系;游戏化相关特征调节了享乐动机与使用意图之间的关系。年龄调节了努力期望与使用意图之间的关系,性别调节了绩效预期与习惯和使用意图之间的关系。用户体验不是一个显著的调节因素。使用后续测试来描述显著交互效应的性质。
本研究确定了健身应用程序使用的驱动因素。智能手机应用程序功能应旨在通过支持用户实现目标和促进习惯形成,从而增加应用程序使用的可能性,进而促进身体活动。应考虑针对特定目标群体的教育、动机和游戏化相关应用功能偏好以及年龄和性别差异。对于欣赏动机相关功能的男性(与女性相比)用户,绩效预期对预期使用具有较高的预测能力。因此,针对这些用户群体的应用程序应侧重于与目标实现相关的功能(例如,目标设定和监控)。未来的研究可以检验这些调节效应的机制及其对身体活动的长期影响。