Tailoring Household Disaster Preparedness Interventions to Reduce Health Disparities: Nursing Implications from Machine Learning Importance Features from the 2018–2020 FEMA National Household Survey

Meghna Shukla, Taryn Amberson (), Tara Heagele, Charleen McNeill, Lavonne Adams, Kevin Ndayishimiye and Jessica Castner
Additional contact information
Meghna Shukla: College of Nursing, Wayne State University, 5557 Cass Ave, Detroit, MI 48202, USA
Taryn Amberson: Castner Incorporated, 1879 Whitehaven Road #150, Grand Island, NY 14072, USA
Tara Heagele: Hunter-Bellevue School of Nursing, Hunter College, The City University of New York, 425 East 25th Street, Office 427W, New York, NY 10010, USA
Charleen McNeill: College of Nursing, University of Tennessee Health Science Center’s, Suite 140C, 874 Union Ave., Memphis, TN 38163, USA
Lavonne Adams: Harris College of Nursing & Health Sciences, Texas Christian University, TCU Box 298620, Fort Worth, TX 76129, USA
Kevin Ndayishimiye: Castner Incorporated, 1879 Whitehaven Road #150, Grand Island, NY 14072, USA
Jessica Castner: Castner Incorporated, 1879 Whitehaven Road #150, Grand Island, NY 14072, USA

IJERPH, 2024, vol. 21, issue 5, 1-23

Abstract: Tailored disaster preparedness interventions may be more effective and equitable, yet little is known about specific factors associated with disaster household preparedness for older adults and/or those with African American/Black identities. This study aims to ascertain differences in the importance features of machine learning models of household disaster preparedness for four groups to inform culturally tailored intervention recommendations for nursing practice. A machine learning model was developed and tested by combining data from the 2018, 2019, and 2020 Federal Emergency Management Agency National Household Survey . The primary outcome variable was a composite readiness score. A total of 252 variables from 15,048 participants were included. Over 10% of the sample self-identified as African American/Black and 30.3% reported being 65 years of age or older. Importance features varied regarding financial and insurance preparedness, information seeking and transportation between groups. These results reiterate the need for targeted interventions to support financial resilience and equitable resource access. Notably, older adults with Black racial identities were the only group where TV, TV news, and the Weather Channel was a priority feature for household disaster preparedness. Additionally, reliance on public transportation was most important among older adults with Black racial identities, highlighting priority needs for equity in disaster preparedness and policy.

Keywords: disasters; disaster preparedness; machine learning; health disparities (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2024
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