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.

How Gender Segregation in Higher Education Contributes to Gender Segregation in the U.S. Labor Market.

What is the relationship between gender segregation in higher education and gender segregation in the labor market? Using Fossett's (2017) difference-of-means method for calculating segregation indices and data from the American Community Survey, we show that approximately 36% of occupational segregation among college-educated workers is associated with gender segregation across 173 fields of study, and roughly 64% reflects gender segregation within fields. A decomposition analysis shows that fields contribute to occupational segregation mainly through endowment effects (men's and women's uneven distribution across fields) than through the coefficient effects (gender differences in the likelihood of entering a male-dominated occupation from the same field). Endowment effects are highest in fields strongly linked to the labor market, suggesting that educational segregation among fields in which graduates tend to enter a limited set of occupations is particularly consequential for occupational segregation. Within-field occupational segregation is higher among heavily male-dominated fields than other fields, but it does not vary systematically by fields' STEM status or field-occupation linkage strength. Assuming the relationship between field segregation and occupational segregation is at least partly causal, these results imply that integrating higher education (e.g., by increasing women's representation in STEM majors) will reduce but not eliminate gender segregation in labor markets.

Using social and behavioural science to support COVID-19 pandemic response.

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.

Feeding the pipeline: Gender, occupational plans, and college major selection.

In this article, we analyze gender differences in college major selection for respondents to the Education Longitudinal Study (2002-2006), focusing on educational pathways through college that lead to science, engineering, or doctoral-track medicine occupations and to non-doctoral track clinical and health sciences occupations. We show that gender differences in college major selection remain substantial, even for a cohort in which rates of enrollment in postsecondary education are more than ten percent higher for young women than for young men. Consistent with other recent research, we demonstrate that neither gender differences in work-family goals nor in academic preparation explain a substantial portion of these differences. However, the occupational plans of high school seniors are strong predictors of initial college major selection, a finding that is revealed only when occupational plans are measured with sufficient detail, here by using the verbatim responses of students. We also find that the association between occupational plans and college major selection is not attributable to work-family orientation or academic preparation. Finally, we find gender differences in the associations between occupational plans and college major selection that are consistent with prior research on STEM attrition, as well as with the claim that attrition also affects the selection of majors that are gateways into doctoral-track medicine. We discuss the implications of the predictive power of occupational plans formed in adolescence for understanding sex segregation and for policies intended to create a gender-balanced STEM and doctoral-level medical workforce.