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Unverified information avoidance behavior refers to the conscious effort made by individuals to avoid consuming information that has not been verified by credible sources. This behavior is essential in preventing the spread of misinformation that can hinder effective public health responses. While previous studies have examined information avoidance behavior in general, there is a lack of research specifically focusing on the avoidance of unverified information during health crises. This study aims to fill this gap by exploring factors that lead to social media users’ unverified information avoidance behavior during health crises, providing novel insights into the determinants of this protective behavior.

We based our research model on the health belief model and validated it using data collected from 424 individuals who use social media. The proposed model was tested by using the partial least squares structural equation modeling (PLS-SEM) approach.

Our results indicate that individuals’ government social media participation (following accounts and joining groups) affects their health beliefs (perceived severity and benefits of information avoidance), which in turn trigger their unverified information avoidance behavior.

Our study contributes to the current literature of social media crisis management and information avoidance behavior. The implications of these findings for policymakers, social media platforms and theory are further discussed.