Abstract

BackgroundMedical students preparing for the United States Medical Licensing Exam (USMLE) Step 2 Clinical Knowledge (CK) Exam frequently use the UWorld Step 2 CK Question Bank (QBank). Over 90% of medical students use UWorld QBanks to prepare for at least one USMLE. Although several questions in the QBank mention race, ethnicity, or immigration status, their contributions to the QBank remain underexamined.ObjectiveWe conducted a systematic, mixed-methods content analysis to assess whether and how disease conditions might be racialized throughout this popular medical education resource.DesignWe screened 3537 questions in the QBank between May 28 and August 11, 2020, for mentions of race, ethnicity, or immigration status. We performed multinomial logistic regression to assess the likelihood of each racial/ethnic category occurring in either the question stem, answer explanation, or both. We used an inductive technique for codebook development and determined code frequencies.Main MeasuresWe reviewed the frequency and distribution of race or ethnicity in question stems, answer choices, and answer explanations; assessed associations between disease conditions and racial and ethnic categories; and identified whether and how these associations correspond to race-, ethnicity-, or migration-based care.ResultsReferences to Black race occurred most frequently, followed by Asian, White, and Latinx groups. Mentions of race/ethnicity varied significantly by location in the question: Asian race had 6.40 times greater odds of occurring in the answer explanation only (95% CI 1.19–34.49; p < 0.031) and White race had 9.88 times greater odds of occurring only in the question stem (95% CI 2.56–38.08; p < 0.001). Qualitative analyses suggest frequent associations between disease conditions and racial, ethnic, and immigration categories, which often carry implicit or explicit biological and genetic explanations.ConclusionsOur analysis reveals patterns of race-based disease associations that have potential for systematic harm, including promoting incorrect race-based associations and upholding cultural conventions of White bodies as normative.

Highlights

  • Biomedical researchers frequently deploy the terms “race” and “ethnicity” to describe study populations

  • Though medical training varies across the USA, medical students rely on standardized study materials for the United States Medical Licensing Examinations (USMLEs).[7,8]

  • Despite extensive use of study resources such as the USMLE World (UWorld) Step 2 Clinical Knowledge (CK) Question Bank (QBank), the educational function of mentions of race, ethnicity, and immigration status remains poorly understood. This cross-sectional study examines whether and how racebased medicine operates throughout the UWorld Step 2 CK QBank by (1) reviewing the frequency and distribution of race, ethnicity, and immigration status in question stems, answer choices, and answer explanations; (2) assessing associations between disease conditions and racial, ethnic, and immigration categories; (3) evaluating biological explanations provided; and (4) identifying whether and how these associations correspond to race, ethnicity, or migration-based care

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Summary

Introduction

Biomedical researchers frequently deploy the terms “race” and “ethnicity” to describe study populations. Over 90% of medical students report using UWorld for at least one USMLE.[9] Studies indicate that “one-step” clinical associations produce high success rates in self-directed retrievalstudying.[10] Reliance on heuristics involving flawed racebased disease associations risks reinscribing harmful, biologized notions of race.[5] Despite extensive use of study resources such as the UWorld Step 2 Clinical Knowledge (CK) QBank, the educational function of mentions of race, ethnicity, and immigration status remains poorly understood This cross-sectional study examines whether and how racebased medicine operates throughout the UWorld Step 2 CK QBank by (1) reviewing the frequency and distribution of race, ethnicity, and immigration status in question stems, answer choices, and answer explanations; (2) assessing associations between disease conditions and racial, ethnic, and immigration categories; (3) evaluating biological explanations provided; and (4) identifying whether and how these associations correspond to race-, ethnicity-, or migration-based care. CONCLUSIONS: Our analysis reveals patterns of racebased disease associations that have potential for systematic harm, including promoting incorrect race-based associations and upholding cultural conventions of White bodies as normative

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