INSTITUTE FOR POLICY RESEARCH

New IPR Research: April 2025

This month’s new research from our faculty experts explores how integrating biological and prevention sciences might improve mental health treatment and improving meta-analyses to strengthen evidence in education. It also investigates how voters evaluate candidates in primary elections and how top management journals have overwhelmingly focused on elite entrepreneurs. 

Methods for Policy Research

A Call for Collaboration with Communities to Improve Mental Health Treatment 

Personalized medicine—an approach that tailors treatments to an individual’s biology, environment, and lifestyle—has made significant strides in physical health, but its progress in mental health has been slower. Writing in Prevention Science on behalf of a task force appointed by the Board of the Society for Prevention Research, IPR psychologist Robin Nusslock and colleagues explore how integrating biological and prevention sciences might improve personalized mental health treatment. Prevention science aims to identify factors that put people’s health at risk—as well as factors that might protect them—and develop early interventions that promote health. Using biomarkers like brain scans and blood draws can open up new possibilities for personalized prevention strategies in mental health treatment, but there are notable hurdles. Connecting biomarkers to emotional and behavioral health outcomes is even more complicated than anticipated, and genetic and neuroimaging studies often yield small or inconsistent results. Research also lacks diversity—among both study participants and scientists—so findings may not apply across different populations. Ethical issues, including privacy concerns and the historical misuse of biological research, add further complications. To address these barriers, the authors advocate for Community-Based Participatory Research (CBPR), which involves diverse communities in shaping research priorities and methods. They also emphasize the need for stronger analytical techniques, a greater focus on equity in science, and interdisciplinary collaboration that embraces the dynamic connection between mind and body. By making research more inclusive and accessible, integrating biological and prevention sciences could lead to more effective personalized mental health interventions that benefit all communities.

Education and Human Development

Improving Meta-Analyses to Strengthen Evidence in Education

Meta-analyses—studies that systematically combine results from multiple studies—are critical tools for identifying effective interventions in education and beyond. But how rigorous are these analyses themselves? In Learning Disability Quarterly, IPR statistician Beth Tipton and colleagues evaluate 29 meta-analyses from 2000 to 2020 on mathematics interventions for students with disabilities or potential disabilities. They focus on four best practices: examining how different factors (such as student characteristics or teaching methods) influence results, adjusting for small sample sizes, properly accounting for studies that report multiple results for the same intervention, and checking for publication bias to ensure that it’s not only studies with positive results that are included. They found that more recent studies (2011-2020) increasingly used advanced techniques such as meta-regression, which identifies patterns across studies, and robust variance estimation, which prevents misleading conclusions when multiple results come from the same study. However, many still fail to correct for small sample bias or properly handle multiple results from the same source. Nearly 40% of the recent meta-analyses did not check for publication bias, raising concerns that interventions might appear more effective than they are. Tipton and her co-authors emphasize that strengthening the methods used in meta-analyses is essential for ensuring that educators and policymakers base decisions on the most reliable evidence. By improving the rigor of these studies, researchers can better identify which interventions truly help students with disabilities succeed in mathematics.

Policy Discourse and Decision Making

How Voters Evaluate Candidates in Primary Elections

General elections in the United States may not be highly competitive, so primary elections play a major role in determining the final election outcome. But how do voters decide which candidates to support in the primaries? In a working paper, IPR political scientist Laurel Harbridge-Yong and her colleagues investigate how voters determine a candidate’s electability, or how likely it is that a candidate will win a general election. Between May and August of 2022, the researchers conducted a survey experiment in Ohio, Pennsylvania, North Carolina, and Wisconsin before primary elections for senator, governor, or both. Voters were randomly shown candidates who would be on the primary ballot and provided either no information, or information about the candidates in one of three categories: the candidate’s level of ideological moderation, how much experience they had in elected office, and how much money they had raised. Next, voters were asked how likely they thought the party would be to win in the general election if each candidate won the primary, as well as how likely they were to vote for each candidate. The results show that voters use information about fundraising as a signal of electability. However, this pattern is driven by voters in Republican primaries. Democratic primary voters, by contrast, believe a candidate is more likely to be elected if they are more ideologically moderate. These patterns point to the importance of money in elections and raise new questions about whether Democratic voters value moderate candidates more than Republicans.

Most Research on Entrepreneurs Looks at Elites

Entrepreneurship research has long shaped how we understand innovation, economic growth, and social mobility—but who gets studied, and who gets left out? In Research in Organizational Behavior, entrepreneurship scholar and IPR associate Kylie Hwang and co-author Damon Phillips show that top management journals have overwhelmingly focused on elite entrepreneurs—those who are wealthy, highly educated, and well-connected—while largely neglecting those from marginalized backgrounds. They contend that this bias limits both the accuracy and applicability of entrepreneurship theories. Hwang and Phillips highlight how existing research disproportionately examines founders with access to stable, high-paying jobs, elite networks, and venture capital, overlooking entrepreneurs who start businesses out of necessity or due to barriers in traditional employment. They argue that this narrow lens has led scholars to develop theories that may not hold for the majority of entrepreneurs, particularly those from marginalized groups such as individuals with disabilities, low-income backgrounds, or past incarceration experience. By expanding research to include a broader range of entrepreneurial experiences—including small businesses, self-employment, and hybrid work models—Hwang and Phillips call for a shift in focus that can lead to more comprehensive theories and policies. Integrating the experiences of marginalized entrepreneurs, they argue, is not just a matter of representation—it is essential for understanding the true landscape of entrepreneurship and its potential to drive social and economic change.

Photo credit: Unsplash

Published: April 14, 2025.