RAPID: Coping in Families Affected by California Wildfires and Flooding

严重的自然灾害带来巨大的经济代价，威胁到许多人的健康和福祉。过去十年的严重自然灾害包括史无前例的洪水、灾难性的飓风和毁灭性的野火。2017年12月，加州历史上最严重的野火袭击了文图拉县和圣巴巴拉县。这些县的托马斯大火烧毁了28.2万英亩土地，夺走了两人的生命，烧毁或损坏了1000多座建筑物。由于地处主要人口中心，超过10万名居民被疏散，远远不止一次。火灾发生后，暴雨引发大规模泥石流，席卷蒙特西托市，造成23人死亡，115座房屋被毁。这些发生在地理集中地区的灾难性事件为更好地了解个人和家庭如何应对和恢复巨大压力提供了一个独特的机会。该项目的重点是更深入地了解个人和家庭如何管理灾后恢复，以及什么预示着积极和消极的结果。通过将计算机科学家和灾难心理学家组成的多学科团队聚集在一起，将评估新的理论和计算方法，以更好地了解人类对极端事件的反应，并为未来干预的发展提供信息。利用智能手机技术和在线调查，在六个月的时间内，将跟踪文图拉县和圣巴巴拉县的100对父母/孩子和100名非父母幸存者。这些调查和每日的“签到”将提供人们如何应对压力的关键数据。随着时间的推移，通过培养一组关于同一个人的非常丰富的数据，将有可能以过去研究尚未完成的方式辨别复苏的模式。每天衡量结果将产生大量数据，并支持使用“大数据”分析方法(例如，机器学习技术)，这些方法可以确定指导理论框架(自我调节转变理论)预测的独特的功能变化或转变。该项目扩展了目前所理解的与灾后恢复相关的内容，以应对变化的关键机制为目标，并突出支持干预的可能关键目标。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.