Experience, experts, statistics, or just science? Predictors and consequences of reliance on different evidence types during the COVID-19 infodemic

Hang Lu, Haoran Chu, Yanni Ma

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

As an unprecedented global disease outbreak, the COVID-19 pandemic is also accompanied by an infodemic. To better cope with the pandemic, laypeople need to process information in ways that help guide informed judgments and decisions. Such information processing likely involves the reliance on various evidence types. Extending the Risk Information Seeking and Processing model via a two-wave survey (N = 1284), we examined the predictors and consequences of US-dwelling Chinese’s reliance on four evidence types (i.e. scientific, statistical, experiential, and expert) regarding COVID-19 information. Overall, Risk Information Seeking and Processing variables such as information insufficiency and perceived information gathering capacity predicted the use of all four evidence types. However, other Risk Information Seeking and Processing variables (e.g. informational subjective norms) did not emerge as important predictors. In addition, different evidence types had different associations with subsequent disease prevention behaviors and satisfaction with the US government’s action to address the pandemic. Finally, discrete emotions varied in their influences on the use of evidence types, behaviors, and satisfaction. The findings provide potentially valuable contributions to science and health communication theory and practice.

Original languageEnglish
Pages (from-to)515-534
Number of pages20
JournalPublic Understanding of Science
Volume30
Issue number5
DOIs
StatePublished - Jul 2021

Keywords

  • COVID-19
  • emotion
  • evidence
  • information processing

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