Harris School of Public Policy Studies
Published December 13, 2023 | Version v1
Journal article Open

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

Creators

  • 1. Columbia University
  • 2. Max Planck Institute for Human Development
  • 3. University of Queensland
  • 4. University of Milan-Bicocca
  • 5. Mackenzie Presbyterian University
  • 6. Utrecht University
  • 7. University of Kent
  • 8. Massachusetts Institute of Technology
  • 9. University of Cambridge
  • 10. Harvard University
  • 11. Northwestern University
  • 12. Carleton University
  • 13. Ohio State University
  • 14. New York University
  • 15. University of British Columbia
  • 16. Stanford University
  • 17. Lehigh University
  • 18. University of Chicago

Description

Scientific evidence regularly guides policy decisions, with behavioural science increasingly part of this process. In April 2020, an influential paper3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts 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 finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. 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 effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects 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 scientific evidence in policy formulation and prioritization.

Notes

Due to the large number of authors, only the first 20 and the University of Chicago authors are included on the above author list. Please download the article for the complete list of authors.

Data availability

All data and study material are provided either in the Supplementary information or through the two online repositories (OSF and Tableau Public, both accessible via https://psyarxiv.com/58udn). No code was used for analyses in this work.

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Additional details

Identifiers

DOI
10.1038/s41586-023-06840-9
Other
oai:uchicago.tind.io:10087

Funding

National Science Foundation
2218595
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
88887.310255/2018
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
1133/2019
Conselho Nacional de Desenvolvimento Científico e Tecnológico
309905/2019-2
National Science Foundation
SES-2017651
National Science Foundation
SES-2022478
European Research Council
101018262
Canadian Institutes of Health Research
172681

UChicago Information

Division(s)
Harris School of Public Policy Studies
Department(s)
Harris School of Public Policy Studies Research Publications