{Reference Type}: Journal Article
{Title}: A synthesis of evidence for policy from behavioural science during COVID-19.
{Author}: Ruggeri K;Stock F;Haslam SA;Capraro V;Boggio P;Ellemers N;Cichocka A;Douglas KM;Rand DG;van der Linden S;Cikara M;Finkel EJ;Druckman JN;Wohl MJA;Petty RE;Tucker JA;Shariff A;Gelfand M;Packer D;Jetten J;Van Lange PAM;Pennycook G;Peters E;Baicker K;Crum A;Weeden KA;Napper L;Tabri N;Zaki J;Skitka L;Kitayama S;Mobbs D;Sunstein CR;Ashcroft-Jones S;Todsen AL;Hajian A;Verra S;Buehler V;Friedemann M;Hecht M;Mobarak RS;Karakasheva R;Tünte MR;Yeung SK;Rosenbaum RS;Lep Ž;Yamada Y;Hudson STJ;Macchia L;Soboleva I;Dimant E;Geiger SJ;Jarke H;Wingen T;Berkessel JB;Mareva S;McGill L;Papa F;Većkalov B;Afif Z;Buabang EK;Landman M;Tavera F;Andrews JL;Bursalıoğlu A;Zupan Z;Wagner L;Navajas J;Vranka M;Kasdan D;Chen P;Hudson KR;Novak LM;Teas P;Rachev NR;Galizzi MM;Milkman KL;Petrović M;Van Bavel JJ;Willer R;
{Journal}: Nature
{Volume}: 625
{Issue}: 7993
{Year}: 2024 Jan 13
{Factor}: 69.504
{DOI}: 10.1038/s41586-023-06840-9
{Abstract}: Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. 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.