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Race, Ethnicity, and Immigration Status in a Medical Licensing Educational Resource: a Systematic, Mixed-Methods
Jessica P Cerdeña1,2, Rohit Jaswaney3, Marie V Plaisime4
1Yale School of Medicine, New Haven, CT, USA. jessica.cerdena@yale.edu.
Background:
Medical 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.
Objective:
We conducted a systematic, mixed-methods content analysis to assess whether and how disease conditions might be racialized throughout this popular medical education resource.
Design:
We 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 Measures:
We 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.
Results:
References 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.
Conclusions:
Our 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.