Yale School of Medicine, New Haven, CT, USA.
Department of Anthropology, Yale University, New Haven, CT, USA.
J Gen Intern Med. 2022 Apr;37(5):1045-1051. doi: 10.1007/s11606-021-06843-0. Epub 2021 May 13.
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.
We conducted a systematic, mixed-methods content analysis to assess whether and how disease conditions might be racialized throughout this popular medical education resource.
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.
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.
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.
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.
准备参加美国医师执照考试（USMLE）第 2 步临床知识（CK）考试的医学生经常使用 UWorld Step 2 CK 题库（QBank）。超过 90%的医学生使用 UWorld QBanks 来准备至少一次 USMLE。尽管 QBank 中的几个问题提到了种族、民族或移民身份，但它们对 QBank 的贡献仍未得到充分研究。
我们进行了一项系统的、混合方法的内容分析，以评估在这个流行的医学教育资源中，疾病状况是否以及如何被种族化。
我们在 2020 年 5 月 28 日至 8 月 11 日期间筛选了 QBank 中的 3537 个问题，以查找与种族、民族或移民身份相关的问题。我们进行了多项逻辑回归分析，以评估每个种族/民族类别出现在问题题干、答案解释或两者中的可能性。我们使用了一种归纳技术来开发代码簿，并确定了代码的频率。
我们审查了问题题干、答案选择和答案解释中种族或民族的出现频率和分布；评估了疾病状况与种族和民族类别的关联；并确定了这些关联是否以及如何对应于基于种族、民族或移民的护理。
黑人种族的提及最为频繁，其次是亚洲人、白人以及拉丁裔群体。种族/民族的提及在问题的不同位置有显著差异：亚洲种族出现在答案解释中的可能性是仅出现在问题题干中的亚洲种族的 6.40 倍（95%CI 1.19-34.49；p<0.031），而白人种族出现在问题题干中的可能性是仅出现在答案解释中的白人种族的 9.88 倍（95%CI 2.56-38.08；p<0.001）。定性分析表明，疾病状况与种族、民族和移民类别之间经常存在关联，这些关联往往带有隐含或明确的生物学和遗传学解释。
我们的分析揭示了基于种族的疾病关联模式，这些模式可能会造成系统性伤害，包括促进错误的基于种族的关联，并维护白人身体的文化规范。
