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Skip the checking step: Investigating the pathways from online health information scanning to unverified health information sharing.

Authors :
Zheng, Han
Wang, Xiaohui
Luo, Chen
Zeng, Yueliang
Source :
Computers in Human Behavior. Sep2024, Vol. 158, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Health misinformation has become rampant in the digital age, because people often share unauthenticated health messages on online platforms. While previous studies have pinpointed different factors that influence the dissemination of such unverified health content, few have delved into the transition from exposure to online health information to its unverified sharing. Drawing upon the theory of motivated information management, this study proposes a research model that connects online health information scanning to unverified health information sharing. Using two-wave survey data in China, we found a positive association between online health information scanning and uncertainty discrepancy in Time 1. Such discrepancy subsequently led to perceived health threat and health anxiety in Time 2, which ultimately increased unverified health information sharing in Time 2. Overall, this study enriches the information management literature by theorizing the pathways from information scanning to unverified information sharing through cognitive and emotional responses. Moreover, the findings offer practical insights for social media operators and health professionals to propose informed strategies to curb the spread of unverified health information on the internet. • The study theorizes the pathways from information scanning to unverified information sharing. • A two-wave survey was conducted in China to test the model. • A positive association exists between information scanning and uncertainty discrepancy. • Uncertainty discrepancy increases perceived health threat and health anxiety. • Perceived health threat and health anxiety trigger unverified health information sharing. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07475632
Volume :
158
Database :
Academic Search Index
Journal :
Computers in Human Behavior
Publication Type :
Academic Journal
Accession number :
177750436
Full Text :
https://doi.org/10.1016/j.chb.2024.108279