Abstract
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.
Published Version
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