Information avoidance in the age of COVID-19: A meta-analysis

Abstract

Guided by three major theoretical frameworks, this meta-analysis synthesizes 17 empirical studies (15 articles with 18,297 participants, 13 of them are from non-representative samples) and quantifies the effect sizes of a list of antecedents (e.g., cognitive, affective, and social factors) on information avoidance during the COVID-19 context. Findings indicated that information-related factors including channel belief (r = -0.35, p < .01) and information overload (r = 0.23, p < .01) are more important in determining individual's avoidance behaviors toward COVID-19 information. Factors from the psychosocial aspects, however, had low correlations with information avoidance. While informational subjective norms released a negative correlation (r = -0.16, p < .1) which was approaching significant, positive and negative risk responses were not associated with information avoidance. Moderator analysis further revealed that the impacts of several antecedents varied for people with different demographic characteristics (i.e., age, gender, region of origin), and under certain sampling methods. Theoretically, this meta-analysis may help determine the most dominant factors from a larger landscape, thus providing valuable directions to refine frameworks and approaches in health information behaviors. Findings from moderator analysis have also practically inspired certain audience segmentation strategies to tackle occurrence of information avoidance during the COVID-19 pandemic.