U.S. minority groups are disproportionately affected by many preventable health problems. They are also less likely to receive high-quality health interventions. Understanding these health inequities is fundamental to improving public health, as is understanding which existing preventive interventions are effective for which subgroups. Unfortunately, few studies have examined research questions about whether preventive interventions work differentially for minority subgroups, or about different mechanisms by which these interventions might work. Despite National Institutes of Health (NIH) policies requiring the inclusion of underrepresented minority groups in research studies, the sample sizes of diverse subgroups in these studies are often too low to conduct meaningful analyses to answer these key research questions.

In this presentation, we propose that there is a pressing need for “scientific equity,” or equality in the amount of scientific knowledge that is produced to understand both the potential causes and solutions to many health inequities. We begin by examining the issue of scientific equity, using prevention interventions as illustrative examples. We subsequently describe key strategies for promoting scientific equity including conducting more implementation research, utilizing adaptive intervention research designs, and promoting collaborative data synthesis work. The latter is a novel method that brings together individual-level data from multiple intervention studies for synthesis analysis, thereby increasing the number of participants from different minority subgroups available and enhancing statistical power. Promoting scientific equity through these strategies has the potential to bring about improvements in the efficacy and reach of preventive interventions, through more specific and better targeted interventions that can ultimately help address health inequities.

Dr. Brown is Professor of Epidemiology and Public Health at the University of Miami Miller School of Medicine, where he is also Director of the Social Systems Informatics Program in the Center for Computational Science. In addition, he is Director of the National Institute on Drug Abuse-funded Center for Prevention Implementation Methodology and Director of the National Institute of Mental Health-funded Prevention Science and Methodology Group. Dr. Brown has developed innovative randomized field trial designs for preventing drug abuse, depression, and suicide, and also has developed new methods for synthesizing findings across randomized trials with individual-level data, applying systems science and computational methods for implementation research.