OP02 Balancing core beliefs and values about pandemics mitigation policies in the general population: a discrete choice experiment

Background During the Covid-19 pandemic, policy-makers had to make challenging decisions about mitigation policies, trying to find the balance between several domains such as physical health (contamination, hospitalisations, and fatalities), health system resilience, economic activity and welfare, individual liberties, and mental wellbeing. Restrictive measures were also at risk of not being followed by the population. Indeed, studies indicated that restrictive policies were better accepted and had less detrimental effects when they were understood correctly and underpinned by shared core beliefs and values in the general population. In this context, we carried out a Discrete Choice Experiment (DCE) with a representative sample of the general population in four countries (Belgium, France, the Netherlands, and the UK) with a view to determining the population’s core beliefs and values that best support mitigation policies. Methods DCE is method rooted in random utility theory and widely used to model individuals’ choice behaviour. The model allows disentangling the core beliefs and values underpinning preferences. In this online survey, a sample of 800 respondents (200 per country), representative of the general population in terms of gender, age group, geographic location, and socioeconomic status, was involved. Respondents were presented with a set of random alternative attributes and attribute levels to choose from. Alternatives represented two fictitious country, A and B, and attributes were the reported consequences of the pandemic mitigation policies on four criteria: admissions to hospitals, active population losing their job, movement restrictions towards public places, and psychological distress. The survey also included indicators on sociodemographic status and core policy beliefs. Results Preliminary analyses revealed that respondents tended to choose the country with the lowest disutility, i.e. lowest sum of negative consequences. However, when the highest disutility was chosen, job loss was the domain that counterbalanced other negative effects (total effect of job loss: χ2=173.8, p