Summary
Introduction:
This article examines e-cigarette users' risk information avoidance (RIa) and its predictors in the context of the e-cigarette health crisis in the United States. The study applies and extends previous RIa models and the Risk Information Seeking and Processing (RISP) model, incorporating new roles for scientific uncertainty and channel beliefs. The results provide insights into the mechanisms underlying e-cigarette users' RIa and offer suggestions for prevention and mitigation.
Key Points:
* The study examines e-cigarette users' RIa, which is a significant challenge to e-cigarette risk communication.
* The study identifies two pathways explaining e-cigarette users' motivation for RIa: one involving heightened risk perceptions associated with strong negative affective responses, and the other involving scientific uncertainty and relevant channel beliefs.
* Scientific uncertainty is positively associated with RIa, and it negatively affects channel beliefs, reducing the perceived quality of e-cigarette information.
* Negative affective responses, including fear, anger, sadness, and guilt, are positively associated with RIa intentions.
* The RISP model is applied and extended to examine the association between several variables, including risk perceptions, negative affective responses, channel beliefs, and RIa.
* The study proposes and tests a theoretical model predicting e-cigarette users' RIa in the context of e-cigarettes, negative affect encompassing fear, anger, sadness, and guilt, and scientific uncertainty.
* The findings suggest that scientific uncertainty and negative affective responses play essential roles in e-cigarette users' RIa.
Main Message:
The study highlights the importance of addressing scientific uncertainty and negative affective responses in e-cigarette risk communication. By improving channel beliefs, public health authorities and news media can reduce e-cigarette users' RIa and promote informed decision-making about e-cigarette use. The findings suggest that tailored communication strategies that address users' concerns and perceptions could be more effective in reducing e-cigarette-related health risks.
Citation
Kim E, Sarge Ma. Modeling Electronic-Cigarette Users’ Risk Information avoidance. Journal of health communication. 2022;27(8):603-613. doi:10.1080/10810730.2022.2140366
