Is mobile health all peer pressure? The influence of mass media exposure on the motivation to use mobile health apps
| Autor: | Douglas M. McLeod, Jin Kyun Lee, Jonathan D'Angelo, Min-Woo Kwon, Kwansik Mun |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
medicine.medical_specialty
020205 medical informatics business.industry Communication Public health 05 social sciences Internet privacy 050801 communication & media studies 02 engineering and technology Interpersonal communication 0508 media and communications Arts and Humanities (miscellaneous) Information and Communications Technology mental disorders 0202 electrical engineering electronic engineering information engineering medicine Norm (social) Peer pressure Psychology business Mobile device mHealth Mass media |
| Zdroj: | Convergence: The International Journal of Research into New Media Technologies. 23:565-586 |
| ISSN: | 1748-7382 1354-8565 |
| DOI: | 10.1177/1354856516641065 |
| Popis: | In recent years, the spread of mobile communication devices such as smartphones has been markedly rapid. With this technological diffusion, mobile health (mHealth) has become an increasingly important issue. In particular, there is an increasing interest in smartphone apps improving public health. Although there is increased availability of mobile devices and health apps, little is known about motivational factors predicting health app adoption and use. The aim of this study was to identify motivational factors that predict the adoption and use of health apps (i.e. health app engagement). To identify the motivational factors, 391 college students were surveyed and survey questions considered the effects of media exposure to health information, interpersonal communication on health issues, and psychological factors (e.g. attitude, usefulness, peer norm, and self-efficacy) on health app engagement. Our results confirm the effect of attitude ( β = 0.36) and usefulness are ( β = 0.33) on mHealth App usage. Furthermore, we found that age ( β = 0.11) and reading news articles about health ( β = 0.13) predict mHealth App usage. Theoretical and practical implications and suggestions for future research are discussed. |
| Databáze: | OpenAIRE |
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