Characteristics and Perspectives of Human Trafficking Education: A Survey of U.S. Medical School Administrators and Students.

Objective: To assess the timing, duration, methodology, and content of human trafficking (HT) curricula in U.S. medical schools. Methods: An anonymous, cross-sectional survey was sent through email and phone to administrators of 199 U.S. allopathic and osteopathic medical schools. A supplementary survey was sent to students and faculty through email listservs and social media links. Data collection occurred from April to October 2020 and findings were analyzed through SAS software. All study measures were approved by the institutional review board. Results: Administrators were from 22 states and 34 schools (n = 51/199 schools; response rate: 25.6%) and n = 41 responded to all questions. Of these, 32% (13/41) self-identified as deans, 34.1% (14/41) as faculty, and 29.3% (12/41) as other administrators. Less than half (41.5%, n = 17/41) reported an HT curriculum. There was a wide range in length (average = 3 hours) and when present was almost always mandatory (n = 51, 88.2%). Few curricula mentioned labor (23.5%) or organ (5.9%) trafficking, or at-risk populations such as lesbian, gay, bisexual, trans, queer, and intersex (LGBTQI) members (13.7%), foreign nationals (7.8%), victims of political conflict (3.9%), and indigenous peoples (2.0%). Students and staff (n = 242) were from 34 states and 83 schools, and n = 36 (27.5%) reported a curriculum. Less than half (44.4%) felt the length (average 4.1 hours) was sufficient. Conclusions: Less than half of respondents reported an HT curriculum. It is unclear how well this curriculum prepares students to treat victim-survivors of HT. Future work is necessary to incorporate effective education on HT for trainees and evaluate patient outcomes after curricular implementation.

Reevaluating Corticosteroid Classification Models in Patient Patch Testing.

Importance: Individuals with allergic contact dermatitis to one topical corticosteroid may also react to other corticosteroids. Corticosteroid classification models have been proposed to predict such copositivity, recommend representative screening corticosteroids, and guide allergen avoidance. Objective: To use patient data to determine copositivity patterns between corticosteroids and evaluate against previous corticosteroid classification models. Design, Setting, and Participants: This qualitative study included a retrospective analysis of the Mayo Clinic Contact Dermatitis Group corticosteroid patch test data from 2010 to 2019. Among patients undergoing patch testing with the Mayo Clinic's standard or steroid series who consented to research participation, 5637 patients were included in the analysis. Copositivity rates were determined between corticosteroids and analyzed by hierarchical clustering for comparison to previous classification models. Main Outcomes and Measures: The frequency of patch test positivity to each of the analyzed corticosteroids was noted and compared with previously published patch test positivity rates. Copositivity rates between each pair of corticosteroids were determined, and overall copositivity patterns were analyzed and evaluated against known steroid classes. Results: A total of 49 472 individual patches were applied to 5637 patients, testing 18 corticosteroids. Patch test positivity rates ranged between 0.3% and 4.7%. The fluocinonide positivity rate corresponded to the highest copositivity rate with other corticosteroids (mean [SD], 50.7% [26.1%]). Tixocortol-21-pivalate, 0.1%, and tixocortol-21-pivalate, 1%, positivity rates corresponded to the lowest copositivity rates (mean [SD], 4.1% [1.7%] and 3.6% [1.4%], respectively). Hierarchical clustering elucidated patterns that did not support previous corticosteroid classification models. Conclusions and Relevance: In this qualitative study, copositivity rates were variable between corticosteroids, and overall patch test positivity for allergy to topical corticosteroids was rare. Previously published corticosteroid classifications are not supported by real patient-derived data and may not be accurate in predicting corticosteroid copositivity.