COVID-19 skepticism and the perception of risk

Abstract

A large group of people are receptive to COVID skeptic messages which can be linked to lower levels of perceived risk and uncompliant behavior. Using a survey instrument targeting young adults, which we repeated during the second and fourth waves of COVID-19, we explored how various psychological factors affect risk perception and to what degree can these be linked to COVID skepticism. Our results suggest that higher skepticism is very strongly associated with a lower risk perception. Skepticism also mediates the effects of well-known antecedents of risk perception, such as individualism, pro-social attitudes and trust in scientists. We found that contracting the virus is associated with increased risk perception and increased skepticism, which is contradictory, but understandable considering our sample composition. Among those who had a family member or a friend contracting the virus we observed higher levels of perceived risk and lower skepticism. The longitudinal nature of our research highlights that the influence of trust in scientists and government are dependent on the public discourse, which naturally develops over time. Differences in risk perception based on gender, which is well established in the literature and significant in our first sample, have diminished by the time of our second sample, suggesting this effect could be crowded out as people’s understanding grows and beliefs form about the virus. The findings emphasize the importance of assessing skepticism not only for researchers studying COVID related risk perception and its psychological predictors, but also for policy makers combating hazardous scenarios like the pandemic.

Keywords:

• Risk perception
• COVID-19
• skepticism
• trust
• worldviews

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

All data are publicly available on the Open Science Framework (OSF) website. The repository contains the detailed survey design, all raw data, and the scripts of the analysis (R code) for the presented paper. https://osf.io/rsvy6/