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Influence Factors of Users’ Health Information Sharing Behavior on WeChat Platform
WU Xiaoli
Chinese Journal of Journalism & Communication ›› 2022, Vol. 44 ›› Issue (10) : 96-118.
PDF(1622 KB)
PDF(1622 KB)
Influence Factors of Users’ Health Information Sharing Behavior on WeChat Platform
WeChat has become the main social media platform for users to obtain information. Health information is one of the most important contents which can easily trigger users’ sharing behavior on the WeChat platform. Yet, knowledge about influence factors of health information sharing behavior in social media remains limited. Therefore, to discuss the impact factors of users’ health information sharing behavior, this paper established research hypotheses based on the theory of planned behavior, technology acceptance model, and social cognitive theory. The impact factors are divided into attitude, value, and environment, which include six variables: perceived usefulness, information quality, self-efficacy, perceived benefits, social support, and critical mass. To examine the research model, an online questionnaire was drawn up and administered to 375 WeChat users. The results of structural equation modeling analysis revealed that the research model fits the data well. The study found that all variables were positively correlated with WeChat users’ health information sharing intention. Among them, the value factor has the greatest effect. And the individual’s attitude towards information and the influence of environment on the individual are also important factors, but the degree of effect decreases. Meanwhile, users’ age and self-perceived health status also affect their health information sharing behavior. Overall, this study presents a new integrated conceptual model to explain influence factors that affect WeChat users’ sharing behavior regards to health information, and provides theoretical and practical implications regarding motivating public participation through information sharing on social media in health communication.
WeChat / information sharing behavior / impact factors / structural equation modeling / health communication
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