A synthesis of evidence for policy from behavioural science during COVID-19

Abstract

Scientifc evidence regularly guides policy decisions1 , with behavioural science increasingly part of this process2 . In April 2020, an infuential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to eforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams fnding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy efectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed efects and there were no efects for highlighting individual benefts or protecting others. No available evidence existed to assess any distinct diferences in efects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientifc evidence in policy formulation and prioritization.