Severe natural disasters carry great economic costs and threaten the health and well-being of many people. Severe natural disasters during the past decade include unprecedented flooding, catastrophic hurricanes, and devastating wildfires. The worst wildfire in California history struck Ventura and Santa Barbara counties in December 2017. The Thomas Fire in those counties burned 282,000 acres, took two lives, and incinerated or damaged over one thousand structures. Because of its location to major population centers, over 100,000 residents were evacuated, many more than once. In the aftermath of the fire, rain produced a massive mudslide cascading through the city of Montecito killing 23 people and destroying 115 homes. These catastrophic events within a geographically concentrated region offer a unique opportunity to better understand how individuals and families cope with and recover from profound stress. The focus of this project is to gain a richer understanding of how individuals and families manage post-disaster recovery and what predicts both positive and negative outcomes. By bringing together a multi-disciplinary team of computer scientists and disaster psychologists, new theories and computational methods will be evaluated to better understand human response to extreme events and to inform the development of future interventions.
Using Smart Phone technology and online surveys over a six-month period of time, 100 parent/child pairs and 100 non-parent survivors in Ventura and Santa Barbara counties will be followed. The surveys and the daily "check-ins" will provide critical data on how people cope with stress across time. By cultivating a very rich set of data on the same individuals over time, it will be possible to discern patterns of recovery in ways that past research has not done. Measuring outcomes on a daily basis will generate significant data and support the use of "big data" analysis methods (e.g., machine learning techniques) that can identify unique changes or shifts in functioning predicted by the guiding theoretical framework (self-regulation shift theory). This project extends what is currently understood related to post-disaster recovery by targeting key coping mechanisms of change and highlighting possible critical targets for supportive interventions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
