RAPID: COVID-19 Information Exposure and Messaging Effects

抗击COVID-19大流行需要了解人们对该疾病的信息，以及官员如何提高公众知识并鼓励保护公共健康的行为。通过测量COVID-19的信念和态度，这项研究深入了解了公众对COVID-19的信念，以及政府和健康信息对大流行的有效性，以及这些数量如何随时间变化。除了测量受访者对COVID-19的了解，研究团队还评估了人们的在线媒体消费与他们的知识模式之间的关系。最后，该研究提供了有关公共卫生信息对受访者对COVID-19的了解和对公共卫生政策的支持的有效性的信息。研究团队正在收集美国人在多波全国代表性调查中的行为和调查数据。这项调查包括了居住在COVID-19病例高发地区并自愿同意提供其在线浏览活动数据的受访者的超额样本。每一波都衡量了对COVID-19不同类型信念的流行程度，以及对公共卫生当局建议的支持和遵守情况。为了评估对公共卫生官员信息的反应，第二波调查包括一个随机实验，评估卫生和医疗当局信息的影响。最后，该研究通过分析受访者使用人工编码和机器学习相结合的方法提供的行为数据，来描述人们在线消费的关于流行病的信息。该项目由DRMS和刺激竞争研究的既定计划（EPSCoR）联合资助该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的评估被认为值得支持。影响审查标准。

Fighting the COVID-19 pandemic requires understanding what information people have about the disease and how officials can improve public knowledge and encourage behaviors that will protect public health. By measuring COVID-19 beliefs and attitudes, this study provides insights into public beliefs about COVID-19 and the efficacy of government and health messaging about the pandemic, and how those quantities change over time. In addition to measuring respondents’ knowledge about COVID-19, the research team assesses how people’s online media consumption is related to their patterns of knowledge. Finally, the study provides information about the effectiveness of public health messages on respondents’ knowledge about COVID-19 and support for public health policies.The research team is collecting behavioral and survey data from Americans in a multi-wave nationally representative survey. This survey includes oversamples of respondents who live in areas with high numbers of COVID-19 cases and who have voluntarily agreed to provide data on their online browsing activity. Each wave measures both the prevalence of different types of beliefs about COVID-19 and reported support for and adherence to recommendations from public health authorities. To evaluate responses to information from public health officials, the second survey wave includes a randomized experiment evaluating the effects of messaging from health and medical authorities. Finally, the study characterizes the information people consume online about the pandemic by analyzing the behavioral data provided by respondents using a combination of human-coded and machine learning approaches.This project is jointly funded by DRMS and the Established Program to Stimulate Competitive Research (EPSCoR).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.