Dual-systems and fuzzy-trace theory predictions of COVID-19 risk taking in young adults.

Abstract

Risk-reduction behaviors are the first line of defense in viral epidemics. Choosing to not engage in risk-reduction behaviors produced millions of preventable deaths from COVID-19. Understanding why this happens and how to predict it is important for theory development and public policy. We took four approaches to this problem: experimentally varying theory-driven predictors (social rewards, transmission risk, and mandatory/ voluntary regulations) in choice scenarios, further probing choices in specific scenarios predicted to elicit risk taking, conducting hierarchical regressions with demographic and theory-driven predictors for both scenario types, and conducting corresponding regressions for self-reported protective behaviors. The sample consisted of 247 young adults to test highly publicized predictions about how the virus would spread and who would take risks. Results showed that risky choices for scenarios correlated with self-reported behavior and varied with transmission risk and whether regulations were mandatory. Experimentally varying social reward did not elicit greater risk taking as expected by dual-systems theory but risk taking in specific social scenarios was predicted by individual differences in sensation seeking as predicted by dual-systems theory. Sensation seeking predicted social distancing and impulsivity predicted mask wearing. Fuzzy-trace theory's predictors of categorical thinking about risk and endorsement of simple gist principles of social responsibility (to not hurt other people) consistently predicted choices and behaviors, accounting for significant variance beyond dual-systems predictors. Both controlled experiments and real-world self-reported behaviors converged on similar conclusions, identifying a major gap in influential theories (the omission of gist-based thinking) and challenging pessimistic predictions about motivations and mandates in public health.