JOURNAL ARTICLE

The effects of mortality salience on perceived risk and trust in the managing bodies of nuclear power: The moderating effect of nuclear power support.

  • Published In: Asian Journal of Social Psychology, 2024, v. 27, n. 4. P. 767 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Tsujikawa, Norifumi 3 of 3

Abstract

Public concern regarding nuclear power has arisen due to accidents involving radiation leakages, natural disasters, terrorism, war and other incidents. That is, people's concerns regarding the use of nuclear power have grown as situations that threaten their survival have increased. This study uses terror management theory to examine how mortality salience affects people's risk perception and trust in the managing bodies of nuclear power. The results of Study 1 and Study 2 revealed that when the level of support for nuclear power is low, the effect of mortality salience increases trust in the managing bodies. Study 2's findings reveal mortality salience leads to decreased risk perception of nuclear power. In the case of risks that are managed by others and that are difficult to understand, such as nuclear power, people tend to place higher value on the managing bodies because they cannot handle the risk themselves. These results highlight the changes in people's perceptions of nuclear power managing bodies when they are conscious of death and provide important information on the nature of communication between citizens and experts regarding nuclear power. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Asian Journal of Social Psychology. 2024/12, Vol. 27, Issue 4, p767
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2024
  • ISSN:1367-2223
  • DOI:10.1111/ajsp.12636
  • Accession Number:181922004
  • Copyright Statement:Copyright of Asian Journal of Social Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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