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Examining Factors Influencing Protective Actions Among Persons with Disabilities During the December 10–11, 2021, Tornado Outbreak in the United States

Published online by Cambridge University Press:  01 September 2023

Jennifer M. First*
Affiliation:
College of Social Work, University of Tennessee, Knoxville, TN, USA
Sangwon Lee
Affiliation:
College of Social Work, University of Tennessee, Knoxville, TN, USA
*
Corresponding author: Jennifer M. First, Email: jfirst@utk.edu.
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Abstract

Objective:

This study examined various factors influencing protective actions among persons with disabilities exposed to the December 10–11, 2021, tornado outbreak in the US Midwest and Southeastern regions.

Methods:

Survey administration occurred 5 months following the tornado outbreak and included a total of 209 persons with disabilities who lived in one of the counties impacted by tornado warnings. Structural equation modeling was used to examine the direct and indirect effects of hypothesized predictors impacting protective behavioral actions.

Results:

Results found that persons with disabilities who had access to more tornado warning sources increased their protective actions, and tornado risk perception further mediated the relationship between warning information sources and protective actions. In addition, results found that persons with disabilities who encountered more situational barriers in their physical and social environment were found to have a decrease in protective action, and having more situational resources was found to contribute to the ability to take protective action.

Conclusions:

The current study’s results highlight the need for policies and practices that provide additional physical and social resources for persons with disabilities to seek protection during tornado threats.

Information

Type
Original Research
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of Society for Disaster Medicine and Public Health
Figure 0

Table 1. Descriptive statistics of participants

Figure 1

Table 2. Confirmatory factor analysis of latent variables for measurement model

Figure 2

Table 3. Structural model estimates

Figure 3

Figure 1. Diagram of structural model. N = 209, Model Fit statistics: χ2(119) = 1438.879, P < 0.01, CFI = 0.91, TLI = 0.90, RMSEA = 0.08, SRMR = 0.07; *P < 0.05, **P < 0.01, ***P < 0.001.