Skin of Color Representation in Hidradenitis Suppurativa Textbooks
Notice bibliographique
Résumé
Hidradenitis suppurativa (HS) is a chronic inflammatory skin condition characterized by the presence of abscesses, inflammatory nodules, and scar formation [1]. The prevalence of HS is higher in skin of color, and it presents more severely in these populations [1, 2]. The underrepresentation of darker skin tones in general dermatology textbooks and medical education resources has been well-described [3-5]. Examining skin of color (SoC) representation in condition-specific textbooks is necessary to determine if underrepresentation is also found in subspecialty areas. Therefore, the purpose of this study was to examine SoC representation in HS-specific textbooks. Four HS textbooks were reviewed (Table 1). Textbooks were selected with assistance from a medical librarian, and textbooks with digitally available images were included. Clinical photographs were rated according to the Fitzpatrick skin type (non-SoC were types I-III and SoC were types IV-VI) and the Hurley staging system (I-III), as applicable, and independently verified by a second reviewer. Diagrams, histopathology slides, medical imaging, illustrations, etc. were excluded. Depicted body region and presence of erythema/pigmentary changes was also extracted. SoC representation between textbooks and Hurley stage representation by SoC were compared via chi-squared tests. Statistical significance was determined at p < 0.05 (two-tailed). Statistically significant models were then compared using post hoc chi-squared tests (2 × 2 contingency tables) or Fisher's exact test. Statistical analyses were performed using SPSS Statistics 29 (IBM Corporation). Jemec GBE, Revuz J, Leyden JJ, eds. Hidradenitis Suppurativa. Berlin, Germany: Springer Berlin; 2006. Kimball AB, Jemec GBE, eds. Hidradenitis Suppurativa: A Disease Primer. Cham, Switzerland: Springer International Publishing; 2017. Micali G, ed. Hidradenitis Suppurativa: A Diagnostic Atlas. Hoboken, NJ: John Wiley & Sons; 2017. Shi VY, Hsiao JL, Lowes MA, Hamzavi IH, eds. A Comprehensive Guide to Hidradenitis Suppurativa. Philadelphia, PA: Elsevier; 2021. Note: only this textbook had a chapter dedicated to hidradenitis suppurativa presentation in skin of color In total, there were 460 unique images, of which 272 met inclusion criteria. Two hundred seventeen images (79.8%) were classified as non-SoC, and 55 images (20.2%) were SoC. There were 56 (20.6%) and 114 (41.9%) images for Hurley stages I and II/III, respectively. The most photographed body regions included the axilla (n = 88; 32.4%), inguinal/anogenital region (n = 65; 23.9%), buttock (n = 44; 16.2%), and chest (n = 9; 3.3%). The body region for 21 images (7.7%) was indeterminate. The remaining 45 images (16.5%) came from a variety of locations (i.e., abdomen, arm, back, head/neck, thigh, and multi-region). Erythema was noted in 179 images (65.8%), depigmentation in 28 images (10.3%), and post-inflammatory hyperpigmentation in 141 images (51.8%). There was a statistically significant difference in the proportion of SoC versus non-SoC images between textbooks (p = 0.01; Table 2a). One textbook had greater SoC representation compared to two others. No statistically significant difference was found in the proportion of SoC versus non-SoC images between Hurley stages (p = 0.74; Table 2b). SoC images are proportionally underrepresented overall despite increased disease burden in darker skin tones. Strengths of current resources include broad depiction of various disease stages, inflammatory changes, and body regions. As previously known, SoC underrepresentation is well-documented in general dermatology textbooks, but our findings suggest that underrepresentation extends to condition-specific textbooks as well. There is a continued need to improve representation of darker skin tones within textbook images to reflect global ethnic diversity as countries and populations become increasingly diverse. Accordingly, the emergence of digital image collections has the potential to revolutionize the representation of dermatologic disease in diverse skin tones. A variety of dermatologic journals and societies have curated SoC images to increase awareness of common and historically neglected disease [6]. These online resources are free, crowd-sourced, living visual atlases as opposed to the cross-sectional static depictions in traditional resources like textbooks. Although limitations still exist with regard to image volume and accessibility, these tools are slowly enacting change in the field of ethnic dermatology through technology and collaboration. Oswin Chang: methodology, data curation, investigation, formal analysis, visualization, writing – original draft, writing – review and editing. Jincheng Shi: conceptualization, methodology, data curation, investigation, visualization, writing – review and editing, supervision. The authors have nothing to report. The authors have nothing to report. The authors declare no conflicts of interest. The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».