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

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

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

Scientific evidence regularly guides policy decisions 1, with behavioural science increasingly part of this process 2. In April 2020, an influential paper 3 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

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

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.Scientific evidence regularly guides policy decisions, with behavioural science increasingly part of this process. In April 2020, an influential paper 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.The National Science Foundation; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brazilian Federal Agency for the Support and Evaluation of Graduate Education); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brazilian Federal Agency for the Support and Evaluation of Graduate Education); the Ministry of Science, Technology and Innovation | Conselho Nacional de Desenvolvimento Científico e Tecnológico (National Council for Scientific and Technological Development); National Science Foundation grants; the European Research Council; the Canadian Institutes of Health Research.http://www.nature.com/naturehj2024Gordon Institute of Business Science (GIBS)Non

Health Promotion at Work: A Comparison of Policy and Practice Across Europe

Background: Promoting healthy lifestyles at work should complement workplace safety programs. This study systematically investigates current states of occupational health and safety (OHS) policy as well as practice in the European Union (EU). Methods: OHS policies of EU member states were categorized as either prevention or health promotion provisions using a manifest content analysis. Policy rankings were then created for each prevention and promotion. Rankings compared eight indicators from the European Survey of Enterprises on New and Emerging Risks-2 data on prevention and promotion practices for each member state using Chi-square and probit regression analyses. Results: Overall, 73.1% of EU establishments take preventive measures against direct physical harm, and about 35.4% take measures to prevent psychosocial risks. Merely 29.5% have measures to promote health. Weak and inconsistent links between OHS policy and practice indicators were identified. Conclusion: National OHS policies evidently concentrate on prevention while compliance with health and safety practices is relatively low. Psychosocial risks are often addressed in national policy but not implemented by institutions. Current risk assessment methods are outdated and often lack psychosocial indicators. Health promotion at work is rare in policy and practice, and its interpretation remains preventive. Member states need to adopt policies that actively improve health and well-being at the workplace. Keywords: Health promotion, Occupational health, Occupational health policy, Occupational health and safety, Workplace health promotio

What's important to you?: Socioeconomic inequalities in the perceived importance of health compared to other life domains

BACKGROUND: Pressing issues, like financial concerns, may outweigh the importance people attach to health. This study tested whether health, compared to other life domains, was considered more important by people in high versus low socioeconomic positions, with future focus and financial strain as potential explanatory factors. METHODS: A cross-sectional survey was conducted in 2019 among N=1,330 Dutch adults. Participants rated the importance of two health-related domains (not being ill, living a long life) and seven other life domains (e.g., work, family) on a five-point scale. A latent class analysis grouped participants in classes with similar patterns of importance ratings. Differences in class membership according to socioeconomic position (indicated by income and education) were examined using structural equation modelling, with future focus and financial strain as mediators. RESULTS: Three classes were identified, which were defined as: neutralists, who found all domains neutral or unimportant (3.5% of the sample); hedonists, who found most domains important except living a long life, work, and religion (36.2%); and maximalists, who found nearly all domains important, including both health domains (60.3%). Of the neutralists, 38% considered not being ill important, and 30% considered living a long life important. For hedonists, this was 92% and 39%, respectively, and for maximalists this was 99% and 87%, respectively. Compared to belonging to the maximalists class, a low income predicted belonging to the neutralists, and a higher educational level and unemployment predicted belonging to the hedonists. No mediation pathways via future focus or financial strain were found. CONCLUSIONS: Lower income groups were less likely to consider not being ill important. Those without paid employment and those with a higher educational level were less likely to consider living a long life important. Neither future focus nor financial strain explained these inequalities. Future research should investigate socioeconomic differences in conceptualisations of health, and if inequalities in the perceived importance of health are associated with inequalities in health. To support individuals dealing with challenging circumstances in daily life, health-promoting interventions could align to the life domains perceived important to reach their target group and to prevent widening socioeconomic health inequalities

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

Acknowledgements: We thank Z. Ji, M. Nair Dedhia, A. Lazara, G. Wilson, J. Usseglio, A. Asfa Durrani and M. Kobotis, as well as Corpus Christi College and the Centre for Business Research, University of Cambridge; and S. Kousta. K.R. reports financial support from the National Science Foundation (2218595). P.B. reports funding from (1) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brazilian Federal Agency for the Support and Evaluation of Graduate Education) — 88887.310255/2018; (2) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brazilian Federal Agency for the Support and Evaluation of Graduate Education) — 1133/2019; and (3) the Ministry of Science, Technology and Innovation | Conselho Nacional de Desenvolvimento Científico e Tecnológico (National Council for Scientific and Technological Development) — 309905/2019-2. E.P. reports financial support from National Science Foundation grants (SES-2017651 and SES-2022478). K.M.D. reports financial support from the European Research Council (101018262). R.S.R. reports financial support from the Canadian Institutes of Health Research (172681). Elements of Fig. 1 come from Apple Keys software.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

The globalizability of temporal discounting.

Economic inequality is associated with preferences for smaller, immediate gains over larger, delayed ones. Such temporal discounting may feed into rising global inequality, yet it is unclear whether it is a function of choice preferences or norms, or rather the absence of sufficient resources for immediate needs. It is also not clear whether these reflect true differences in choice patterns between income groups. We tested temporal discounting and five intertemporal choice anomalies using local currencies and value standards in 61 countries (N = 13,629). Across a diverse sample, we found consistent, robust rates of choice anomalies. Lower-income groups were not significantly different, but economic inequality and broader financial circumstances were clearly correlated with population choice patterns