A Cross-Cultural Comparison of an Extended Planned Risk Information Seeking Model on Mental Health among College Students: Cross-Sectional Study

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Abstract

Background: Approximately 42.5 million adults have been affected by mental illness in the United States in 2013, and 173 million people have been affected by a diagnosable psychiatric disorder in China. An increasing number of people tend to seek health information on the Web, and it is important to understand the factors associated with individuals’ mental health information seeking. Identifying factors associated with mental health information seeking may influence the disease progression of potential patients. The planned risk information seeking model (PRISM) was developed in 2010 by integrating multiple information seeking models including the theory of planned behavior. Few studies have replicated PRISM outside the United States and no previous study has examined mental health as a personal risk in different cultures. Objective: This study aimed to test the planned risk information seeking model (PRISM) in China and the United States with a chronic disease, mental illness, and two additional factors, ie, media use and cultural identity, among college students. Methods: Data were collected in both countries using the same online survey through a survey management program (Qualtrics). In China, college instructors distributed the survey link among university students, and it was also posted on a leading social media site called Sina Weibo. In the United States, the data were collected in a college-wide survey pool in a large Northwestern university. Results: The final sample size was 235 for the Chinese sample and 241 for the US sample. Media use was significantly associated with mental health information–seeking intentions in the Chinese sample (P

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Niu, Z., Willoughby, J. F., Mei, J., Li, S., & Hu, P. (2020). A Cross-Cultural Comparison of an Extended Planned Risk Information Seeking Model on Mental Health among College Students: Cross-Sectional Study. Journal of Medical Internet Research, 22(5). https://doi.org/10.2196/15817

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