Reconsidering Trust and Information Engagement and Unpacking the Role of Emotion in Public Responses During the Early Stage of a Public Health Crisis in China: Web-Based Survey Study

  • Liu Z
  • Tu J
  • Lee T
  • et al.
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Abstract

BACKGROUND The COVID-19 pandemic continues to offer valuable insights into crisis management and risk communication, particularly through retrospective analyses that allow a more comprehensive understanding. Emotional responses played a crucial role in shaping how individuals processed information and built trust in different objects in the early stages of the COVID-19 pandemic. OBJECTIVE This study aimed to investigate how negative emotions influence online information engagement and trust in 4 distinct entities: government, scientists, health care providers, and other people (relatives, friends, family, and strangers). METHODS A nationwide survey was conducted in China from January 31 to February 9, 2020, involving 1568 adult participants. The data collection was particularly valuable due to the limited access to national samples in China during the early stages of the public health crisis. Participants were asked questions related to negative emotions, engagement with online information, and their trust in 4 different entities (government, scientists, other people, and health care providers) during the pandemic. Mediation analyses were performed to test the associations between the examined variables. A 95% bootstrap CI approach was used to estimate the mediation effects. RESULTS This study reveals that negative emotions not only had a direct effect on trust but also indirectly fostered trust in the government and scientists through increased information engagement. There was a positive association (B=0.219, SE 0.023; P

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Liu, Z., Tu, J., Lee, T.-T., & Wei, L. (2025). Reconsidering Trust and Information Engagement and Unpacking the Role of Emotion in Public Responses During the Early Stage of a Public Health Crisis in China: Web-Based Survey Study. Online Journal of Public Health Informatics, 17, e77790. https://doi.org/10.2196/77790

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