Collection and especially analysis of open-ended survey responses are relatively rare in the discipline and when conductedare almost exclusively done through human coding. We present an alternative, semiautomated approach, the structural topic model (STM) survey questions. Collection and especially analysis of open-ended data are relatively rare in the discipline and when conducted are almost exclusively done through human coding. We present an alternative, semiautomated approach, the structural topic model (STM) , that draws

Objective To study the U.S. public’s health behaviors, attitudes, and policy opinions about COVID-19 in the earliest weeks of the national health crisis (March 20–23, 2020). Method We designed and fielded an original representative survey of 3,000 American adults between March 20–23, 2020 to collect data on a battery of 38 health-related behaviors, government policy preferences on COVID-19 response and worries about the pandemic. We test for partisan differences COVID-19 related policy attitudes and behaviors, measured in three different ways: party affiliation, intended 2020 Presidential vote, and self-placed ideological positioning. Our multivariate approach adjusts for a wide range of individual demographic and geographic characteristics that might confound the relationship between partisanship and health behaviors, attitudes, and preferences. Results We find that partisanship—measured as party identification, support for President Trump, or left-right ideological positioning—explains differences in Americans across a wide range of health behaviors and policy preferences. We find no consistent evidence that controlling for individual news consumption, the local policy environment, and local pandemic-related deaths erases the observed partisan differences in health behaviors, beliefs, and attitudes. In further analyses, we use a LASSO regression approach to select predictors, and find that a partisanship indicator is the most commonly selected predictor across the 38 dependent variables that we study. Conclusion Our analysis of individual self-reported behavior, attitudes, and policy preferences in response to COVID-19 reveals that partisanship played a central role in shaping individual responses in the earliest months of the COVID-19 pandemic. These results indicate that partisan differences in responding to a national public health emergency were entrenched from the earliest days of the pandemic.

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To study the U.S. public's health behaviors, attitudes, and policy opinions about COVID-19 in the earliest weeks of the national health crisis (March 20-23, 2020). MethodWe designed and fielded an original representative survey of 3,000 American adults between March 20-23, 2020 to collect data on a battery of 38 health-related behaviors, government policy preferences on COVID-19 response and worries about the pandemic. We test for partisan differences COVID-19 related policy attitudes and behaviors, measured in three different ways: party affiliation, intended 2020 Presidential vote, and self-placed ideological positioning. Our multivariate approach adjusts for a wide range of individual demographic and geographic characteristics that might confound the relationship between partisanship and health behaviors, attitudes, and preferences. ResultsWe find that partisanship-measured as party identification, support for President Trump, or left-right ideological positioning-explains differences in Americans across a wide range of health behaviors and policy preferences. We find no consistent evidence that controlling for individual news consumption, the local policy environment, and local pandemic-related deaths erases the observed partisan differences in health behaviors, beliefs, and attitudes. In further analyses, we use a LASSO regression approach to select predictors, and find that a partisanship indicator is the most commonly selected predictor across the 38 dependent variables that we study. ConclusionOur analysis of individual self-reported behavior, attitudes, and policy preferences in response to COVID-19 reveals that partisanship played a central role in shaping individual

In this article, we use the issue of immigration to explore the role of anxiety in responses to political appeals. According to previous literature, anxiety motivates citizens to learn and pay more attention to news coverage. Literature in psychology demonstrates that anxiety is associated with a tendency to pay closer attention to threatening information. We predict that anxious citizens will seek more information but that they will seek out and be attracted to threatening information. In an experiment, we induce anxiety about immigration and then subjects have the opportunity to search for additional information in a website designed to mimic online news sources. The website has both immigration and nonimmigration stories, and the immigration stories are split between threatening coverage and nonthreatening coverage. We find that anxious subjects exhibit biased information processing; they read, remember, and agree with threatening information.