Abstract
BackgroundCollege students’ health behavior is a topic that deserves attention. Individual factors and eHealth literacy may affect an individual’s health behaviors. The integrative model of eHealth use (IMeHU) provides a parsimonious account of the connections among the digital divide, health care disparities, and the unequal distribution and use of communication technologies. However, few studies have explored the associations among individual factors, eHealth literacy, and health behaviors, and IMeHU has not been empirically investigated.ObjectiveThis study examines the associations among individual factors, eHealth literacy, and health behaviors using IMeHU.MethodsThe Health Behavior Scale is a 12-item instrument developed to measure college students’ eating, exercise, and sleep behaviors. The eHealth Literacy Scale is a 12-item instrument designed to measure college students’ functional, interactive, and critical eHealth literacy. A nationally representative sample of 525 valid college students in Taiwan was surveyed. A questionnaire was administered to collect background information about participants’ health status, degree of health concern, major, and the frequency with which they engaged in health-related discussions. This study used Amos 6.0 to conduct a confirmatory factor analysis to identify the best measurement models for the eHealth Literacy Scale and the Health Behavior Scale. We then conducted a multiple regression analysis to examine the associations among individual factors, eHealth literacy, and health behaviors. Additionally, causal steps approach was used to explore indirect (mediating) effects and Sobel tests were used to test the significance of the mediating effects.ResultsThe study found that perceptions of better health status (t520=2.14-6.12, P<.001-.03) and greater concern for health (t520=2.58-6.95, P<.001-.003) influenced college students’ development of 3 dimensions of eHealth literacy and adoption of healthy eating, exercise, and sleep behaviors. Moreover, eHealth literacy played an intermediary role in the association between individual factors and health behaviors (Sobel test=2.09-2.72, P<.001-.03). Specifically, higher levels of critical eHealth literacy promoted students’ health status and their practice of multiple positive health behaviors, including eating, exercise, and sleep behaviors.ConclusionsBecause this study showed that eHealth literacy mediates the association between individual factors and health behaviors, schools should aim to enhance students’ eHealth literacy and promote their health behaviors to help them achieve high levels of critical eHealth literacy. Although some of the study’s hypotheses were not supported in this study, the factors that influence health behaviors are complex and interdependent. Therefore, a follow-up study should be conducted to further explore how these factors influence one another.
Highlights
IntroductionBackgroundThe health behavior of college students is a topic that is worth exploring
BackgroundThe health behavior of college students is a topic that is worth exploring
Because this study showed that eHealth literacy mediates the association between individual factors and health behaviors, schools should aim to enhance students’ eHealth literacy and promote their health behaviors to help them achieve high levels of critical eHealth literacy
Summary
BackgroundThe health behavior of college students is a topic that is worth exploring. Data from a 2010 survey showed a 2-hour difference between the number of hours students spent sleeping on school days (6.4 hours) and weekends (8.5 hours) These results indicate that Taiwanese college students’ exercise, eating, and sleep behaviors must be improved [2]. Given that sleep is a basic physiological need and an essential element in maintaining physical and mental health, we will examine the health behaviors of college students by measuring their eating, exercise, and sleep behaviors. Individual factors and eHealth literacy may affect an individual’s health behaviors. Few studies have explored the associations among individual factors, eHealth literacy, and health behaviors, and IMeHU has not been empirically investigated. We used multiple regression analysis to examine the associations among individual factors, eHealth literacy, and health behaviors. A causal steps approach was used to explore the indirect (mediating) effects [36] and Sobel tests [37] were used to test the significance of the mediating effects
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