Risk perception, efficacies and disaster preparedness: A comparison between people with and without disability.
Published In: Journal of Contingencies & Crisis Management, 2024, v. 32, n. 3. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Li, Yingxiang; Chen, Yung‐Fang; Wang, Ziyi; Han, Ziqiang 3 of 3
Abstract
Persons with disabilities (PwDs) face a disproportionately high risk due to their physical or mental limitations and socioeconomic barriers during emergencies. To better understand and empower PwDs for disaster preparedness, this study used an updated national representative survey (2021 Federal Emergency Management Agency National Household Survey) from the United States to examine the differences between PwDs and their counterparts concerning disaster preparedness with the guidance of the protection motivation theory. The results of the Tobit regression models indicated that being disabled was negatively correlated with the level of preparedness. Furthermore, disability status significantly and negatively modified the relationship between risk perception and disaster preparedness. Likewise, self‐efficacy was less strongly correlated with preparedness activities if people self‐reported themselves as having a disability. Moreover, for people with disabilities, their beliefs about the effectiveness of preventive behaviours (response efficacy) predicted decreased adoption of preparedness measures. Promoting disaster risk reduction education, strengthening self‐efficacy and developing more inclusive and targeted intervention strategies for PwDs can be used to improve their preparedness degree and capacity for disaster prevention. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Contingencies & Crisis Management. 2024/09, Vol. 32, Issue 3, p1
- Document Type:Article
- Subject Area:Psychology
- Publication Date:2024
- ISSN:0966-0879
- DOI:10.1111/1468-5973.12597
- Accession Number:179945081
- Copyright Statement:Copyright of Journal of Contingencies & Crisis Management 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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