A Multi-level Dynamically Coupled Model for Evaluating Older Adults' Vulnerability and Resiliency to Disasters

University Of Texas At Arlington, Arlington TX

Investigators

Abstract

The overarching objective of this research is to attain a deeper understanding of vulnerability and resiliency of older adults to natural disasters. A new model will be constructed and validated to guide future disaster-related studies in the presence of aging populations and emerging technologies. Included in the research is the design and delivery of personalized assistance to older individuals before, during, and after disasters to increase their survivability and accelerate recovery. Fresh insights into how to effectively communicate tornado warnings to older adults and how to best mobilize protective action and mitigation behaviors will be provided. Activities are planned to promote diversity, public outreach, and dissemination of research outcomes. A prototype mobile app will be developed to educate the public on disaster preparedness and mitigation as well as collecting supplementary data for research purpose. This research will systematically explain fundamental differences between older and younger adults as well as disparities among older adults in factors, processes, and outcomes with respect to preparedness, action taking, and mitigation. It hypothesizes an underlying selection, optimization, and compensation process in which older adults minimize losses despite declining resources. A population-based stratified random sampling strategy will be used to oversample older adults in a longitudinal telephone survey of tornadic events respondents. Using latent class analysis, multilevel analysis, and structural equation modeling, this research will estimate the effect of multilevel factors on individual's decision-making and different factors leading to outcomes including patterns of access to warnings, decision-making patterns, physical and psychological impact, risk perceptions, and preparedness and mitigation before and after warnings. Variables and parameters will be mapped to visually present spatial distributions of vulnerability and resiliency of older populations in various communities. As the result, this research will add a more granular and textured depiction of older adults under extreme stress to the current knowledge and explore future opportunities and challenges presented by social media and other emerging communication technologies.