Search

Importance: Racially minoritized and socioeconomically disadvantaged populations are currently underrepresented in clinical trials. Data-driven, quantitative analyses and strategies are required to help address this inequity., Objective: To systematically analyze the geographical distribution of self-identified racial and socioeconomic demographics within commuting distance to cancer clinical trial centers and other hospitals in the US., Design, Setting, and Participants: This longitudinal quantitative study used data from the US Census 2020 Decennial and American community survey (which collects data from all US residents), OpenStreetMap, National Cancer Institute-designated Cancer Centers list, Nature Index of Cancer Research Health Institutions, National Trial registry, and National Homeland Infrastructure Foundation-Level Data. Statistical analyses were performed on data collected between 2006 and 2020., Main Outcomes and Measures: Population distributions of socioeconomic deprivation indices and self-identified race within 30-, 60-, and 120-minute 1-way driving commute times from US cancer trial sites. Map overlay of high deprivation index and high diversity areas with existing hospitals, existing major cancer trial centers, and commuting distance to the closest cancer trial center., Results: The 78 major US cancer trial centers that are involved in 94% of all US cancer trials and included in this study were found to be located in areas with socioeconomically more affluent populations with higher proportions of self-identified White individuals (+10.1% unpaired mean difference; 95% CI, +6.8% to +13.7%) compared with the national average. The top 10th percentile of all US hospitals has catchment populations with a range of absolute sum difference from 2.4% to 35% from one-third each of Asian/multiracial/other (Asian alone, American Indian or Alaska Native alone, Native Hawaiian or Other Pacific Islander alone, some other race alone, population of 2 or more races), Black or African American, and White populations. Currently available data are sufficient to identify diverse census tracks within preset commuting times (30, 60, or 120 minutes) from all hospitals in the US (N = 7623). Maps are presented for each US city above 500 000 inhabitants, which display all prospective hospitals and major cancer trial sites within commutable distance to racially diverse and socioeconomically disadvantaged populations., Conclusion and Relevance: This study identified biases in the sociodemographics of populations living within commuting distance to US-based cancer trial sites and enables the determination of more equitably commutable prospective satellite hospital sites that could be mobilized for enhanced racial and socioeconomic representation in clinical trials. The maps generated in this work may inform the design of future clinical trials or investigations in enrollment and retention strategies for clinical trials; however, other recruitment barriers still need to be addressed to ensure racial and socioeconomic demographics within the geographical vicinity of a clinical site can translate to equitable trial participant representation.

We tested the hypothesis that underrepresented students in active-learning classrooms experience narrower achievement gaps than underrepresented students in traditional lecturing classrooms, averaged across all science, technology, engineering, and mathematics (STEM) fields and courses. We conducted a comprehensive search for both published and unpublished studies that compared the performance of underrepresented students to their overrepresented classmates in active-learning and traditional-lecturing treatments. This search resulted in data on student examination scores from 15 studies (9,238 total students) and data on student failure rates from 26 studies (44,606 total students). Bayesian regression analyses showed that on average, active learning reduced achievement gaps in examination scores by 33% and narrowed gaps in passing rates by 45%. The reported proportion of time that students spend on in-class activities was important, as only classes that implemented high-intensity active learning narrowed achievement gaps. Sensitivity analyses showed that the conclusions are robust to sampling bias and other issues. To explain the extensive variation in efficacy observed among studies, we propose the heads-and-hearts hypothesis, which holds that meaningful reductions in achievement gaps only occur when course designs combine deliberate practice with inclusive teaching. Our results support calls to replace traditional lecturing with evidence-based, active-learning course designs across the STEM disciplines and suggest that innovations in instructional strategies can increase equity in higher education., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)