Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning.

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions.

National identity predicts public health support during a global pandemic.

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g.

Bring out your experts: The relationship between perceived expert causal understanding and pandemic behaviors.

In the complex modern world, people's understanding of how things work is often outsourced to other people. We explore how people's perceptions of expert causal understanding of the coronavirus disease (COVID-19) pandemic predicted their pandemic-related behaviors. As part of a larger longitudinal study, we collected data at four time points that measured participants' perceptions of experts' causal understanding of COVID-19, along with those participants' self-reported pandemic-related health behaviors.

Of Pandemics and Zombies: The Influence of Prior Concepts on COVID-19 Pandemic-Related Behaviors.

We use a concepts and categories research perspective to explore how prior conceptual knowledge influences thinking about a novel disease, namely COVID-19. We collected measures of how similar people thought COVID-19 was to several existing concepts that may have served as other possible comparison points for the pandemic. We also collected participants' self-reported engagement in pandemic-related behaviors.