Abstract
The pervasive of COVID-19 information has driven some to escape daily conversations or media coverage. A rich set of theoretical discussions and empirical studies help explain why individuals avoid health risk information, but few studies have explored social network antecedents to information avoidance. This study investigates how personal discussion networks about COVID-19 shape individuals’ information avoidance behaviors. Using a nationally representative sample (N = 1,304), we examined the effects of network size, heterogeneity, ego-alter dissimilarity, and social norms. Our results suggest that the four network variables had varying effects on different forms of information avoidance. Notably, social norms significantly predicted individuals’ information avoidance. The theoretical and methodological implications of our findings are discussed.
Original language | English (US) |
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Pages (from-to) | 216-227 |
Number of pages | 12 |
Journal | Health communication |
Volume | 38 |
Issue number | 2 |
DOIs | |
State | Published - 2023 |
Bibliographical note
Funding Information:This work was supported by the University of North Carolina at Chapel Hill [UNC University Research Council (URC) 2018]; University of North Carolina at Chapel Hill [UNC University Research Council (URC) 2018].
Publisher Copyright:
© 2021 Taylor & Francis Group, LLC.
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't