Information avoidance during health crises: Predictors of avoiding information about the COVID-19 pandemic among german news consumers

Abstract

\n This study investigates the prevalence of source-specific information avoidance among German consumers and predictors of information-avoidance behavior in the context of the COVID-19 pandemic. Guided by the Risk Information Seeking and Processing Model (RISP), we propose that the perceived social norms, information insufficiency, risk perception, affective risk response, and attitudes toward seeking predict information avoidance. We supplement the RISP model by considering information overload as the vast volume and the incredulous quality of information in the COVID-19 pandemic challenge individuals’ information acquisition and processing. Using a stratified demographic sample of news consumers of a federal German state (N\xa0=\xa01,000), we empirically examined the proposed model, answered the research question, and tested our hypotheses using structural equation modeling. The results reveal information avoidance among one-third of the respondents. They avoided online sources, including online-mediated interpersonal sources, more often than interpersonal sources and traditional mass media. Information avoidance was linked to more negative attitudes toward seeking and negative affective risk responses, more pronounced descriptive and injunctive avoidance norms, and perceived information overload. Attitudes and information overload were the most influential predictors of avoidance. In contrast, risk perception and information insufficiency were not associated with information avoidance. This study provides insights into theory development, contributes to the information behavior literature, and identifies barriers to communication during health crises.\n