RAPID: Factors that affect understanding the risks of COVID-19

很大一部分美国人还没有清楚地认识到COVID-19病毒的威胁。许多人在采取有助于减轻大流行病风险的态度和行为方面行动迟缓。这种病毒已经引起了公众的注意，这怎么可能呢？研究人员假设，这些改变态度和行为的失败源于三个因素：没有意识到这种疾病的影响，没有意识到它的传播速度有多快，没有意识到它将对卫生保健系统造成的可怕后果。在本研究中，研究人员将研究这些失败的潜在因素以及改善与COVID-19相关信息传递的方法。预期将迅速广泛传播有关改善沟通和理解的结果和建议。为了研究如何提高对COVID-19风险的认识，研究人员组成了一个经验丰富的跨学科团队，提出了三个研究方向。他们将研究(a)关于疾病扩散的不同信息呈现方式如何影响人们对其发病率和死亡率的估计，以及预期的未来社会行为，(b)个人和国家之间的人口统计学和特征维度的个体差异如何影响他们对疾病传播的估计，以及(c)人们如何推理疾病对医疗系统可行性的影响。方法将包括测量预测疾病风险和后果的能力，以及作为若干变量函数的“曲线平坦化”的影响，这些变量包括信息呈现模式、计算能力、动机、健康状况以及其他人口统计学和特征变量。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 threat of the COVID-19 virus has not been clearly understood by a substantial portion of the U.S. population. Many people have been slow to adopt attitudes and behaviors that will serve to mitigate the risks of the pandemic. With all the publicity that the virus has engendered, how can this be so? The researchers hypothesize that these failures to change attitude and behavior stem from three factors: failures to realize the impact that this disease has, failures to realize how quickly it will be transmitted, and failures to appreciate the dire consequences it will have on the health care system. In this study, the researcher will examine factors underlying these failures and ways to improve delivery of information relevant to COVID-19. Results and suggestions for improving communication and comprehension are expected to be disseminated widely and expeditiously.In order to investigate ways of improving the understanding of the risks involving COVID-19, the researchers, a highly experienced and inter-disciplinary team, propose three lines of research. They will examine (a) how different ways of presenting information about the proliferation of the disease affects people’s estimates of its incidence and rates of death, as well as intended future social behavior, (b) how individual differences among individuals and countries along demographic and trait dimensions will influence their estimates of the spread of the disease, and (c) how people are reasoning about the impact of the disease on the viability of the healthcare system. Methods will include measuring the ability to predict risk and consequences of the disease as well as the impact of “flattening the curve” as functions of several variables, including mode of information presentation, numeracy, motivation, health status, and other demographic and trait variables.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.