Escalating environmental extremes – weather and climate events that are extreme in magnitude, frequency, and/or impact on communities – have been observed in recent years and are predicted to increase over this century. These extremes (e.g., wildfires, heat waves, storms, etc.) contribute to an estimated 150,000 deaths each year, and the World Health Organization conservatively projects they will result in 250,000 deaths annually between 2030 and 2050. Addressing these escalating environmental extremes will require personal and household adaptation to reduce human suffering (e.g., chronic respiratory ailments due to wildfire smoke exposure) and death (e.g., as a result of acute smoke exposure). The unprecedented scope of extremes makes it difficult for people to adapt, particularly for low-income persons of color (POC) who have access to fewer resources. Effective, low-cost, easily-accessible decision support tools such as those deployed through smartphone applications could play an important role in helping people understand the escalating nature of extremes and motivate them to adopt behaviors that result in improved personal outcomes contributing to greater societal resiliency. Yet, little is known about how exposure experienced as events unfold – unbiased by time or outcome knowledge – affects psychosocial factors, adaptation behaviors, and personal outcomes, and how decision support effects decision making in this context. The objectives of this Faculty Early Career Development (CAREER) integrated research and education plan are to (1) advance fundamental understanding of how decision support tools affect adaptation behavior given psychosocial antecedents in the face of real-time exposure to escalating extremes over time, particularly among low-income POC populations, (2) advance the conceptualization and testing of environmental extremes adaptation behavior models, and (3) transform how we train and educate the next generation of behavioral decision scientists to co-produce and deploy decision support tools with relevant stakeholders – especially among those low-income POC populations that may benefit the most–to more effectively motivate adaptation behaviors that yield desired adaptation outcomes.

The research objectives will be achieved by conducting a longitudinal randomized controlled trial to determine whether a “positive affect” or “social comparison” wildfire smoke intervention, delivered via a smartphone app-based decision support tool, can effectively enhance adaptation behaviors (face mask wearing, sheltering, home or workplace improvements) and desired adaptation outcomes (improved health, adoption of other adaptation measures such as fire protection) in the context of actual exposure (volatile organic compounds, NO2, particulate matter) among approximately 720 San Francisco Bay Area residents from low-income POC communities over time. My educational objective will be achieved by developing and testing a Research-Education-Practice curriculum that trains behavioral decision science scholars on co-producing and deploying effective decision support tools, and attracts and retains underrepresented minorities, low-income, and first-generation students and young investigators. The proposed plan will advance adaptation behavior models for environmental extremes, contribute to effective policy-making environmental extremes adaptation, and contribute to the training of the next generation of behavioral decision science scholars.

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.

National Science Foundation (NSF)
Division of Social and Economic Sciences (SES)
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Robert O'Connor
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Stanford University
United States
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