Partisan Media, Trust, and Media Literacy: Regression Analysis of Predictors of COVID-19 Knowledge

BackgroundThe COVID-19 pandemic was a devastating public health event that spurred an influx of misinformation. The increase in questionable health content was aided by the speed and scale of digital and social media and certain news agencies’ and politicians’ active dissemination of misinformation about the virus. The popularity of certain COVID-19 myths created confusion about effective health protocols and impacted trust in the health care and government sectors deployed to manage the pandemic. ObjectiveThis study explored how people’s information habits, their level of institutional trust, the news media outlets they consume and the technologies in which they access it, and their media literacy skills influenced their COVID-19 knowledge. MethodsWe administered a web-based survey using Amazon Mechanical Turk (MTurk) to assess US adults’ (n=1498) COVID-19 knowledge, media and news habits, media literacy skills, and trust in government and health-related institutions. The data were analyzed using a hierarchical linear regression to examine the association between trust, media literacy, news use, and COVID-19 knowledge. ResultsThe regression model of demographic variables, political affiliation, trust in institutions, media literacy, and the preference for watching Fox or CNN was statistically significant (R2=0.464; F24,1434=51.653; P