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.Fil: Ruggeri, Kai. New York Air National Guard; Estados Unidos. Columbia University Mailman School of Public Health; Estados Unidos. University of Cambridge; Estados UnidosFil: Stock, Friederike. Max Planck Institute for Human Development; Alemania. Humboldt-Universität zu Berlin; AlemaniaFil: Haslam, S. Alexander. University of Queensland; AustraliaFil: Capraro, Valerio. Università degli Studi di Milano; ItaliaFil: Boggio, Paulo. Universidade Presbiteriana Mackenzie; Brasil. National Institute of Science and Technology on Social and Affective Neuroscience; BrasilFil: Ellemers, Naomi. Utrecht University; Países Bajos. University of Utrecht; Países BajosFil: Cichocka, Aleksandra. University Of Kent; Reino UnidoFil: Douglas, Karen M.. University Of Kent; Reino UnidoFil: Rand, David G.. Massachusetts Institute of Technology; Estados UnidosFil: van der Linden, Sander. University of Cambridge; Estados UnidosFil: Cikara, Mina. Harvard University; Estados UnidosFil: Finkel, Eli J.. Northwestern University; Estados UnidosFil: Druckman, James N.. Northwestern University; Estados UnidosFil: Wohl, Michael J. A.. Carleton University; CanadáFil: Petty, Richard E.. Ohio State University; Estados UnidosFil: Tucker, Joshua A.. University of New York; Estados UnidosFil: Shariff, Azim. University of British Columbia; CanadáFil: Gelfand, Michele. University of Stanford; Estados UnidosFil: Packer, Dominic. Lehigh University; Estados UnidosFil: Jetten, Jolanda. University of Queensland; AustraliaFil: Van Lange, Paul A. M.. Universitat zu Köln; Alemania. Vrije Universiteit Amsterdam; Países BajosFil: Pennycook, Gordon. Cornell University; Estados UnidosFil: Peters, Ellen. University of Oregon; Estados UnidosFil: Navajas Ahumada, Joaquin Mariano. Universidad Torcuato Di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Papa, Francesca. Organisation for Economic Co-operation and Development; FranciaFil: Galizzi, Matteo M.. The London School of Economics and Political Science; Reino UnidoFil: Milkman, Katherine L.. University of Pennsylvania; Estados UnidosFil: Petrović, Marija. University of Belgrade; SerbiaFil: Van Bavel, Jay J.. University of New York; Estados UnidosFil: Willer, Robb. University of Stanford; Estados Unido
