RAPID: Investigating the Causal Propositions of the Affect Heuristic During an Ongoing Pandemic

由冠状病毒引起的前所未有的大流行感染了世界各地的许多人，引发了焦虑和恐慌，扰乱了生活的各个方面。除了病例和死亡人数不断增加外，其社会、经济和政治影响也是巨大的。由于缺乏疫苗或有效的治疗方法，预防这种疾病传播的第一线取决于人的行为，遵循有关保持社会距离、卫生和其他建议措施的准则。这种疾病的未来发展轨迹及其影响存在很大的不确定性。在这种灾难性威胁的背景下，这项研究预测了公众对风险的看法，包括希望和恐惧，使用了一种新的理论模型，这种模型基于所谓的“影响启发式”。研究人员以两种方式建立并测试了这个模型，以加深对受日常新闻报道影响的积极情绪和消极情绪如何相互作用以指导行为的理解。了解人们对新闻信息反应的变化不仅能提高对风险感知的理解，还能创造有效的风险沟通信息。这项研究提供了对决定疾病进程的行为的见解，并有助于减轻其有害的社会和经济影响。研究一致发现，对利益的判断与与各种危害相关的风险之间存在反比关系。这种关系的发生是因为对风险重要性的情感认识以相反的方式产生了对风险和利益的认识。这个过程被称为情感启发式。情感和感知到的风险和收益之间关系的因果关系仍然知之甚少。这个项目做了三件事：（1a）构建一个系统动力学模拟模型，该模型明确包含允许情感发挥这种调节作用的信息反馈回路；（1b）模拟随着冠状病毒大流行的展开，情感和感知风险和收益的轨迹；(2)构建一个基于混合主体的模型，该模型包含系统模型的发现，但允许主体之间的异质性（例如，不同程度的医疗脆弱性）；(3)开展全国纵向小组调查，在6个月期间调查公众对大流行的反应。这些数据与来自独立面板的数据一起用于估计和验证这两个模型。这个项目具有广泛的影响，因为了解我们如何管理我们对风险和利益的感知对我们做出的决策和行为至关重要。该项目有助于解释这种纠缠，并预测公众对当前流行病以及潜在的其他危机的反应。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The unprecedented pandemic wrought by the coronavirus has infected many people around the world, triggering anxiety and panic and disrupting all facets of life. In addition to the growing numbers of cases and deaths, the social, economic, and political impacts are vast. Lacking a vaccine or effective therapeutic cure, the front line of defense against the spread of this disease depends on human behavior, following guidelines about social distancing, sanitation, and other recommended measures. There is great uncertainty about the future trajectory of the disease and its impacts. Against the backdrop of this catastrophic threat this research forecasts public perceptions of risks, including hopes and fears, using a new theoretical model based on what is known as “the affect heuristic.” The researchers build and test this model in two ways that increase understanding of how positive and negative emotions, influenced by daily news reports, interact to guide behavior. Understanding the changing reactions to news information not only advances understanding of risk perception, but enables the creation of effective risk communication messages. The research provides insight into the behaviors that will determine the course of the disease and can help to mitigate its harmful social and economic impacts.Studies have consistently found an inverse relationship between judgments of benefits and risks associated with a wide array of hazards. This relationship occurs because perceptions of risk and benefit are derived in opposite ways from an affective sense of the importance of the risk. This process became known as the affect heuristic. The causal dynamics that underlie the relationship between affect and perceived risks and benefits remain poorly understood. This project does three things: (1a) constructs a system dynamics simulation model that explicitly incorporates the informational feedback loops that allow affect to play this moderating role and (1b) simulates the trajectories of affect and perceived risk and benefits as the coronavirus pandemic unfolds, (2) constructs a hybrid agent-based model that incorporates findings from the systems model but allows for heterogeneity (e.g., different levels of medical vulnerability) among agents, and (3) conducts a longitudinal national panel to survey the public’s response to the pandemic over a 6 month period. These data together with data from an independent panel are be used to estimate and validate both models. This project has broad impacts because understanding how we manage our perceptions of risk and benefits is critical to the decisions we make and our behaviors. The project helps to explain this entanglement and predict public reaction to the current pandemic and, potentially, to other crises.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.