Department of Anatomy and Cell Biology, Rush University, Chicago, Illinois, USA.
Rush Medical College, Rush University, Chicago, Illinois, USA.
Anat Sci Educ. 2024 Jul-Aug;17(5):1055-1070. doi: 10.1002/ase.2432. Epub 2024 May 2.
Previous research suggests that underrepresentation in medical curricula perpetuates inequities in healthcare. This study aimed to quantify the prevalence of human phenotypic diversity (e.g., skin tone, sex, body size, and age) across 11 commonly used anatomy atlases and textbooks in pre-clerkship medical education, published from 2015 to 2020. A systematic visual content analysis was conducted on 5001 images in which at least one phenotypic attribute was quantifiable. Anatomy images most prevalently portrayed light skin tones, males, persons with intermediate body sizes, and young to middle-aged adults. Of the 3883 images in which there was a codable skin tone, 81.2% (n = 3154) depicted light, 14.3% (n = 554) depicted intermediate, and 4.5% (n = 175) depicted dark skin tones. Of the 2384 images that could be categorized into a sex binary, 38.4% (n = 915) depicted females and 61.6% (n = 1469) depicted males. A male bias persisted across all whole-body and regional-body images, including those showing sex organs or those showing characteristics commonly associated with a specific sex (e.g. for males, facial hair and/or muscle hypertrophy). Within sex-specific contexts, darker skin was underrepresented, but male depictions displayed greater overall skin tone variation. Although most images could not be assigned to a body size or age category, when codable, these images overwhelmingly depicted adults (85.0%; 482 of 567) with smaller (34.7%; 93 of 268) or intermediate (64.6%; 173 of 268) body sizes. Ultimately, these outcomes provide reference metrics for monitoring ongoing and future efforts to address representation inequalities portrayed in anatomical imagery.
先前的研究表明，医学课程中的代表性不足会使医疗保健中的不平等现象永久化。本研究旨在量化 11 种在预科医学教育中常用的解剖学图谱和教科书，这些图谱和教科书在 2015 年至 2020 年期间出版，其中人类表型多样性（例如肤色、性别、体型和年龄）的普遍程度。对 5001 张可量化表型属性的图像进行了系统的视觉内容分析。解剖图像最常描绘浅肤色、男性、中等体型的人以及年轻到中年的成年人。在可编码肤色的 3883 张图像中，有 81.2%（n=3154）描绘浅色肤色，14.3%（n=554）描绘中间色肤色，4.5%（n=175）描绘深色肤色。在 2384 张可分为二元性别图像中，有 38.4%（n=915）描绘女性，61.6%（n=1469）描绘男性。在所有全身和局部身体图像中，都存在男性偏见，包括显示性器官或显示与特定性别相关的特征（例如男性的胡须和/或肌肉肥大）的图像。在特定性别的背景下，深色皮肤的代表性不足，但男性的描绘显示出更大的整体肤色变化。尽管大多数图像无法归入体型或年龄类别，但在可编码的情况下，这些图像绝大多数描绘的是成年人（85.0%；482/567），体型较小（34.7%；93/268）或中等（64.6%；173/268）。最终，这些结果为监测正在进行的和未来解决解剖图像中代表性不平等问题的努力提供了参考指标。
