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

Details

• Personal Author:
  Adams L ; Amberson T ; Castner J ; Heagele T ; McNeill C ; Ndayishimiye K ; Shukla M
• Description:
  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. [Description provided by NIOSH]
• Subjects:
  Disaster Planning Emergencies Healthcare Disparities Health Personnel Occupational Health Safety
• Keywords:
  Author Keywords: Disasters Disaster Planning Disaster Preparedness Emergency Preparedness Health Disparities Health Equity Intervention Machine Learning Nursing
• ISSN:
  1660-4601
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  District of Columbia ; New York ; OSHA Region 10 ; OSHA Region 2 ; OSHA Region 3 ; OSHA Region 4 ; OSHA Region 5 ; OSHA Region 6 ; Tennessee ; Texas ; Washington ; Wisconsin
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  21
• Issue:
  5
• NIOSHTIC Number:
  nn:20069774
• Citation:
  Int J Environ Res Public Health 2024 May; 21(5):521
• Contact Point Address:
  Taryn Amberson, Castner Incorporated, 1879 Whitehaven Road #150, Grand Island, NY 14072, USA
• Email:
  amberson.taryn@gmail.com
• Federal Fiscal Year:
  2024
• Performing Organization:
  University of Washington
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  International Journal of Environmental Research and Public Health
• End Date:
  20250630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:1f8da94bb00f6d75fe8475a1f360d70937a90b417146c92e6b8aab3a4c9f192e29dc071a8418b8f17019e1e1c742f125956db781ac43002844db50909a4dabb8
• Download URL:
  https://stacks.cdc.gov/view/cdc/208130/cdc_208130_DS1.pdf
• File Type:
  [PDF - 400.16 KB ]