Dermatology in Student-Run Clinics in the United States: Scoping Review
Bibliographic record
Abstract
Background: Student-run clinics (SRCs) for dermatology hold potential to significantly advance skin-related health equity, and a comprehensive analysis of these clinics may inform strategies for optimizing program effectiveness. Objective: We aimed to perform a scoping review of the literature about dermatology SRCs across the United States. Methods: We conducted systematic literature searches of Ovid MEDLINE, Ovid Embase, and Scopus on March 1, 2023, and June 19, 2024. No date, language, or paper-type restrictions were included in the search strategy. A total of 229 references were uploaded to Covidence for screening by 2 independent reviewers (SK and LL), and 23 full-text documents were assessed for eligibility. After an additional 8 documents were identified through a gray literature search, a total of 31 studies were included in the final analysis. Inclusion criteria were as follows: (1) studies set in an SRC, which was operationally led by medical students and could render condition-relevant treatments to patients, with dermatology care; (2) published in English; (3) within the United States; (4) included characterization of any of the following: logistics, care, patients, or design; and (5) included all study or document types, including gray literature that was not peer reviewed (eg, conference abstracts, preprints, and letters to the editor). Exclusion criteria were (1) papers not published in English and (2) those with duplicated data or that were limited in scope or not generalizable. Data were extracted qualitatively using Microsoft Excel to categorize the studies by several domains, including clinic location, demographics, services offered, and barriers to care. Results: There are at least 19 dermatology SRCs across the United States. The most common conditions encountered included atopic dermatitis; acne; fungal infections; benign nevi; psoriasis; and neoplasms, such as basal cell carcinoma, squamous cell carcinoma, and melanoma. Key facilitators for the clinics included faculty oversight, attending physician participation for biopsy histopathology, and dedicated program coordinators. Major barriers included lack of follow-up, medication nonadherence, and patient no-shows. Conclusions: Dermatology SRCs serve a diverse patient population, many of whom are underrepresented in traditional dermatology settings. This scoping review provides insights to help build stronger program foundations that better address community dermatologic health needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".