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This content will become publicly available on June 9, 2024

Title: Applying the extended parallel process model to understand households’ responses to tornado and earthquake risks in Oklahoma
Abstract

Oklahoma is a multihazard environment where both natural (e.g., tornadoes) and technological hazards (e.g., induced seismicity) are significant, making Oklahoma a unique setting to better understand how to manage and prepare for multiple hazards. While studies have attempted to understand drivers of hazard adjustments, few have focused on the overall number of adjustments undertaken instead of individual adjustments or adjustments in a multihazard environment. To address these gaps, we employ a survey sample of 866 households in Oklahoma to understand households’ danger control responses (protective hazard adjustments) for tornado and earthquake risks in Oklahoma. We apply the extended parallel processing model (EPPM) to categorize respondents according to their relative level of perceived threat and efficacy of protective actions in predicting the number of hazard adjustments they intend to or have adopted in response to tornadoes and induced earthquakes. In line with the EPPM, we found that households have the highest number of danger control responses when their perceived threat and efficacy are both high. Counter to the EPPM literature, we found low threat coupled with high efficacy moved some individuals toward the adoption of danger control responses in response to both tornadoes and earthquakes. When households have high efficacy, threat appraisals matter in tornado danger control responses but not in earthquake danger control responses. This EPPM categorization opens new research approaches for studies of natural and technological hazards. This study also provides information for local officials and emergency managers making mitigation and preparedness investments and policies.

 
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Award ID(s):
2038637
NSF-PAR ID:
10421428
Author(s) / Creator(s):
 ;  ;  
Publisher / Repository:
Wiley-Blackwell
Date Published:
Journal Name:
Risk Analysis
Volume:
44
Issue:
2
ISSN:
0272-4332
Format(s):
Medium: X Size: p. 408-424
Size(s):
["p. 408-424"]
Sponsoring Org:
National Science Foundation
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