The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Keep Using My Health Apps: Discover Users' Perception of Health and Fitness Apps with the UTAUT2 Model
Abstract
Background: Health and fitness applications (apps) are one of the major app categories in the current mobile app market. Few studies have examined this area from the users' perspective. This study adopted the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) Model to examine the predictors of the users' intention to adopt health and fitness apps. Materials and Methods: A survey ( n =317) was conducted with college-aged smartphone users at a Midwestern university in the United States. Results: Performance expectancy, hedonic motivations, price value, and habit were significant predictors of users' intention of continued usage of health and fitness apps. However, effort expectancy, social influence, and facilitating conditions were not found to predict users' intention of continued usage of health and fitness apps. Conclusions: This study extends the UTATU2 Model to the mobile apps domain and provides health professions, app designers, and marketers with the insights of user experience in terms of continuously using health and fitness apps.
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Cited by
Tamilmani, K., Rana, N. P., Wamba, S. F., & Dwivedi, R. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102269 · Cited by 660
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Metadata
- Authors
- Yuan, S., Ma, W., Kanthawala, S., & Peng, W.
- Venue
- Telemedicine and e-Health
- Publisher
- SAGE Publications
- Published
- 2015-09
- Volume
- 21
- Issue
- 9
- Pages
- 735-741
- ISSN
- 1530-5627 (ISSN-L)
- 1556-3669
- OpenAlex
- W1910906908
- Cited by
- 403
- References
- 31
- FWCI
- 25.09
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yuan, S., Ma, W., Kanthawala, S., & Peng, W. (2015). Keep Using My Health Apps: Discover Users' Perception of Health and Fitness Apps with the UTAUT2 Model. Telemedicine and e-Health. https://doi.org/10.1089/tmj.2014.0148
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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