Article ID Journal Published Year Pages File Type
516708 International Journal of Medical Informatics 2016 9 Pages PDF
Abstract

•This study tests model of explaining the post-adoption behaviors of using health apps.•Confirmation of primary expectation of health apps plays the key roles.•Satisfaction with health apps use positively affects continuance intention of those apps.•Perceived usefulness of health apps positively affects continuance intention.•Perceived ease of using health apps significantly influences continuance intention.

BackgroundRecently, there has been a rapid increase in the development and use of health apps on smartphones. In spite of research on such technologies, there exist considerable gaps between health app use and our understandings of such technology. Therefore, this study explored the process of leading people to keep using health apps, mainly based on the post-acceptance model (PAM).PurposeDespite significant previous research on health apps, few studies have focused on the post-adoption behaviors of using these technologies. To address and fill the gaps in health app research, this study has developed and tested a model to explain the micro-mechanism that determines the continuance intention to use health apps, theoretically relying on the post-acceptance model (PAM) and the technology acceptance model (TAM).MethodsA sample consisting of 343 Korean adults who were currently using health apps on smartphones participated in an online survey. A path analysis was conducted to test the proposed model composed of the main factors from PAM and TAM.ResultsThe results from the path analysis indicated that the following perceptual and emotional factors—perceived usefulness, perceived ease of use, confirmation, and satisfaction—were significantly associated with the continuance intention to use health apps on smartphones.Discussion/ConclusionMain findings from this present study contribute to developing and empirically testing a model of explaining the basic process of motivating health app users to keep using those apps. This model will be helpful for researchers to further examine health-related technologies, particularly mHealth-oriented ones.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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