To know or not to know? Exploring COVID-19 information seeking with the risk information seeking and processing model
Year: 2022
Type: article
Study design: Observational Study
Abstract: To cope with the COVID-19 pandemic and reduce uncertainty, the public needs accurate and timely information. Inspired by the risk information seeking and processing (RISP) model, this article discovers the significant predictors of individuals’ COVID-19 information-seeking intention and behaviour. Overall, 394 adult participants from 47 states completed this study’s online survey. The hierarchical regression analysis reveals that risk experience and informational subjective norms are the most substantial predictors of individuals’ online information-seeking behaviour about COVID-19. Information insufficiency did not predict information seeking, and participants tend to overestimate their knowledge about COVID-19. RISP variables tend to share power in explaining the variances of information-seeking behaviour. Moreover, both channel beliefs and perceived information gathering capacity moderate information insufficiency’s prediction of information-seeking intention. These findings will assist researchers in discovering the fundamental motivation of information seeking. This article can guide pragmatic interventions to reduce the public’s uncertainty and mitigate the risk.
Source: Journal of Information Science
Authors: Xianlin Jin, Derek Lane
Institutions: University of Toledo, University of Kentucky
Language: English
Subfield: Communication
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4296624951