In a rapidly changing public health crisis such as COVID-19, researchers need innovative approaches that can effectively link qualitative approaches and computational methods. In this article, computational and qualitative methods are used to analyze survey data collected in March 2020 (n = 2,270) to explore the content of persuasive messages and their relationship with self-reported health behavior—that is, social distancing. Results suggest that persuasive messages, based on participants’ perspectives, vary by gender and race and are associated with self-reported health behavior. This article illustrates how qualitative analysis and structural topic modeling can be used in synergy in a public health study to understand the public’s perception and behavior related to science issues. Implications for health communication and future research are discussed.

在 COVID-19 等快速变化的公共卫生危机中，研究人员需要能够有效地将定性方法和计算方法联系起来的创新方法。在本文中，计算和定性方法用于分析 2020 年 3 月收集的调查数据（n= 2,270）探索有说服力的信息的内容及其与自我报告的健康行为（即社交距离）的关系。结果表明，基于参与者观点的有说服力的信息因性别和种族而异，并且与自我报告的健康行为有关。本文说明了如何在公共卫生研究中协同使用定性分析和结构主题建模，以了解公众对科学问题的看法和行为。讨论了对健康传播和未来研究的影响。