No abstract

The COVID-19 pandemic represents a unique context for studying the spread of conspiratorial beliefs within the general population and their role in mediating compliance with government guidance. Here, we apply multivariate and machine learning methods to analyse data from tens of thousands of members of the British public at 6-monthly timepoints during the COVID-19 pandemic. We report that distrust and conspiratorial beliefs significantly predict non-compliant behaviours and covary with sociodemographic variables, being most prevalent for disadvantaged and minority groups. Free text analyses reveal that perceptions of corruption, cronyism, disputing lockdown motivations and the potential of COVID-19 being a lab-leaked bioweapon were common topics motivating non-compliance, with the prevalence and distribution of such beliefs evolving as the pandemic progressed. We propose that survey data could be analysed this way to identify current topics of distrust and map them to demographic variables, enabling the most relevant arguments to be tailored for each individual.

Which population factors have predisposed people to disregard government safety guidelines during the COVID-19 pandemic and what justifications do they give for this non-compliance? To address these questions, we analyse fixed-choice and free-text responses to survey questions about compliance and government handling of the pandemic, collected from tens of thousands of members of the UK public at three 6-monthly timepoints. We report that sceptical opinions about the government and mainstream-media narrative, especially as pertaining to justification for guidelines, significantly predict non-compliance. However, free text topic modelling shows that such opinions are diverse, spanning from scepticism about government competence and self-interest to full-blown conspiracy theories, and covary in prevalence with sociodemographic variables. These results indicate that attempts to counter non-compliance through argument should account for this diversity in peoples’ underlying opinions, and inform conversations aimed at bridging the gap between the general public and bodies of authority accordingly.

Flexible behaviour requires cognitive-control mechanisms to efficiently resolve conflict between competing information and alternative actions. Whether a global neural resource mediates all forms of conflict or this is achieved within domainspecific systems remains debated. We use a novel fMRI paradigm to orthogonally manipulate rule, response and stimulus-based conflict within a full-factorial design. Whole-brain voxelwise analyses show that activation patterns associated with these conflict types are distinct but partially overlapping within Multiple Demand Cortex (MDC), the brain regions that are most commonly active during cognitive tasks. Region of interest analysis shows that most MDC sub-regions are activated for all conflict types, but to significantly varying levels. We propose that conflict resolution is an emergent property of distributed brain networks, the functional-anatomical components of which place on a continuous, not categorical, scale from domain-specialised to domain general. MDC brain regions place towards one end of that scale but display considerable functional heterogeneity.