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Skin Color Representation Within Podiatric Medical Education Materials
Chiara Edlin1, Elizabeth Gajardo-Stitt1, Erica Preblich1
1College of Podiatric Medicine & Surgery, Des Moines University, Des Moines, IA 50266, USA.
Background:
The ability to accurately diagnose dermatologic conditions in patients with various skin tones is an essential skill for the podiatric physician, as many lower extremity pathologies present differently depending on skin pigmentation. Our study sought to evaluate diversity of skin color representation in images used in lecture material within podiatric medical education at a single institution, as well as within commonly utilized textbooks.
Methods:
Images presented throughout the curriculum at our academic institution and those found in widely utilized podiatric textbooks were evaluated by three independent coders. Images were categorized based on skin tone via the Massey-Martin skin color scale.
Results:
A total of 5276 images were evaluated using the Massey-Martin skin color scale. Interrater reliability was assessed using a subsample of 90 images independently coded by all three raters, yielding a strong ordinally weighted Krippendorff's alpha (α = 0.905). Among those images used within our institutional podiatric curriculum, 86.34% of images were within the lightest skin color range (0-2), 11.7% were of medium skin color (3-5), and 1.96% contained darker skin tones (6-10). The average between the textbooks evaluated showed 82.1% were light, 15.4% were medium, and 2.5% were darker skin tones.
Conclusions:
Despite the growing diversity of the U.S. population, there remains a notable lack of darker skin tone representation in medical education, including disseminated course materials at our institution and within commonly used podiatry textbooks. This gap in diversity within educational resources can hinder the ability of healthcare professionals to provide comprehensive and equitable care, particularly when it comes to conditions that present differently across various skin tones. Declarations and Disclosures: No financial disclosures or conflicts of interest. No generative artificial intelligence was used in the writing of this work.
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