Patterns of compliance with COVID-19 preventive behaviours: a latent class analysis of 20,000 UK adults

Abstract

Background: Governments have implemented a range of measure to tackle COVID-19, primarily focusing on changing citizens behaviours in order to lower transmission of the virus. Few studies have looked at the patterns of compliance with different measures within individuals: whether people comply with all measures or selectively choose some but not others. Such research is important for designing interventions to increase compliance. Methods: We used cross-sectional data from 20,947 UK adults in the COVID-19 Social Study collected 17 November to 23 December 2020. Self-report compliance was assessed with six behaviours: mask wearing, hand washing, indoor household mixing, outdoor household mixing, social distancing, and compliance with other guidelines. Patterns of compliance behaviour were identified using latent class analysis, and multinomial logistic regression was used to assess demographic, socioeconomic and personality predictors of behaviour patterns. Results: We selected a four latent class solution. Most individuals reported similar levels of compliance across the six behaviour measures. High levels of compliance was the modal response. Lower self-reported compliance was related to young age, high risk-taking behaviour, low confidence in government, and low empathy, among other factors. Looking at individual behaviours, mask wearing had the highest level of compliance whilst compliance with social distancing was relatively low. Conclusion: Results suggest that individuals choose to comply with all guidelines, rather than some but not others. Strategies to increase compliance should focus on increasing general motivations to comply alongside specifically encouraging social distancing.