Modeling compliance with COVID-19 prevention guidelines: the critical role of trust in science

The coronavirus pandemic is one of the biggest health crises of our time. In response to this global problem, various institutions around the world had soon issued evidence-based prevention guidelines. However, these guidelines, which were designed to slow the spread of COVID-19 and contribute to public well-being, are (deliberately) disregarded by some individuals. In the present study, we aimed to develop and test a multivariate model that could help us identify individual characteristics that make a person more/less likely to comply with COVID-19 prevention guidelines. A total of 525 attentive participants completed the online survey. The results of structural equation modeling (SEM) show that COVID-19 risk perception and trust in science both independently predict compliance with COVID-19 prevention guidelines, while the remaining variables in the model (political conservatism, religious orthodoxy, conspiracy ideation and intellectual curiosity) do so via the mediating role of trust in science. The described model exhibited an acceptable fit (chi(2)(1611) = 2485.84,p< .001, CFI = .91, RMSEA = .032, SRMR = .055). These findings thus provide empirical support for the proposed multivariate model and underline the importance of trust in science in explaining the different levels of compliance with COVID-19 prevention guidelines.

Automated summary

The study developed a multivariate model to identify individual characteristics that predict compliance with COVID-19 prevention guidelines, finding that COVID-19 risk perception and trust in science directly predict compliance, while other factors like political conservatism and conspiracy ideation influence compliance through the mediating role of trust in science. The model displayed acceptable fit and emphasizes the importance of trust in science in explaining compliance behavior.