Special Communication
A trade-off dual-factor model to investigate discontinuous intention of health app users: From the perspective of information disclosure

https://doi.org/10.1016/j.jbi.2019.103302Get rights and content
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Highlights

  • Numerous mobile apps have been developed for making our lives more convenient and improving our quality of life.

  • Health apps are designed for recording users’ health-related behaviors and to give advice about improving their physical conditions.

  • This study conducts an empirical investigation and develops a trade-off dual-factor model to dissect the reason why users discontinue use of health apps.

  • The result reveals that our research model explains 31% of the variance.

Abstract

Numerous mobile apps have been developed for making our lives more convenient and improving our quality of life. Health apps are among them. These types of apps are designed to help users for recording their health-related behaviors and to give advice about improving users’ physical conditions. However, users frequently do not continue to use these health apps. As a result, the companies of health apps have paid the development cost but cannot get back the benefit from the apps they launch. To find out the reason, this study conducts an empirical investigation and develops a trade-off dual-factor model to dissect the reason why users discontinue use of health apps. The research model is based on the perspectives of information disclosure and expectation-confirmation theory. Users may worry about the disclosure of individual health privacy; however, on the other hand, they enjoy the functions of health apps, proffering various kinds of health-related assistance. The decision of whether or not to continue using this kind of app turns into a trade-off issue. To delve into the determinants, we conduct an online survey and collect 242 qualified responses as our research samples. Structural equation modeling is employed to analyze the samples in this study. The result reveals that our research model explains 31% of the variance. The findings and implications can serve as references for researchers and practitioners.

Graphical abstract

Value on path: Standardized coefficients (β); *p < 0.05, **p < 0.01, ***p < 0.001.

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Keywords

Discontinuance usage
Information disclosure
Expectation-confirmation theory
Health apps

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