What predicts people’s belief in COVID-19 misinformation? A retrospective study using a nationwide online survey among adults residing in the United States

Abstract

Abstract Background Tackling infodemics with flooding misinformation is key to managing the COVID-19 pandemic. Yet only a few studies have attempted to understand the characteristics of the people who believe in misinformation. Methods Data was used from an online survey that was administered in April 2020 to 6518 English-speaking adult participants in the United States. We created binary variables to represent four misinformation categories related to COVID-19: general COVID-19-related, vaccine/anti-vaccine, COVID-19 as an act of bioterrorism, and mode of transmission. Using binary logistic regression and the LASSO regularization, we then identified the important predictors of belief in each type of misinformation. Nested vector bootstrapping approach was used to estimate the standard error of the LASSO coefficients. Results About 30% of our sample reported believing in at least one type of COVID-19-related misinformation. Belief in one type of misinformation was not strongly associated with belief in other types. We also identified 58 demographic and socioeconomic factors that predicted people’s susceptibility to at least one type of COVID-19 misinformation. Different groups, characterized by distinct sets of predictors, were susceptible to different types of misinformation. There were 25 predictors for general COVID-19 misinformation, 42 for COVID-19 vaccine, 36 for COVID-19 as an act of bioterrorism, and 27 for mode of COVID-transmission. Conclusion Our findings confirm the existence of groups with unique characteristics that believe in different types of COVID-19 misinformation. Findings are readily applicable by policymakers to inform careful targeting of misinformation mitigation strategies.