Signing On: A New Chapter in Medical Education for Inclusive Care; Scoping Review
Bibliographic record
Abstract
Patients with sensory disabilities, including deafness and hearing loss (D&HH), continue to face significant communication barriers with healthcare providers, adversely affecting the quality of care they receive. Despite this, only a limited number of medical schools incorporate formal education on Deaf awareness into their curricula. This review aims to investigate how deaf competency training can be integrated into medical education to enhance student awareness and improve health outcomes for the D&HH community. Articles were sourced from PubMed, EMBASE, and OVID Medline using MeSH terms and keywords. Articles were included if they were published in English, focused on medical students, and discussed the benefits of Deaf awareness and American Sign Language (ASL) training. Exclusion criteria included relevance to non-medical students, non-medical contexts, non-full articles, and retracted studies. The review found that various forms of professional development workshops significantly increased Deaf awareness and improved attitudes among medical students. Notably, these workshops fostered a deeper understanding of the unique challenges faced by the D&HH community, highlighting the importance of effective communication strategies in clinical settings. However, the limited literature on Deaf awareness training in medical curricula, coupled with small sample sizes in existing studies, restricts the ability to draw definitive conclusions. To address these gaps, future research should focus on developing clinically relevant and specialty-specific Deaf awareness training programs, while also considering longer workshop durations to enhance effectiveness. Such initiatives could contribute to improved health outcomes for the D&HH community by equipping future healthcare professionals with the necessary skills to provide inclusive care. ---------- Les patients ayant des handicaps sensoriels, y compris la surdité et la perte d’audition, continuent d’être confrontés à d’importants obstacles à la communication avec les prestataires de soins de santé, ce qui nuit à la qualité des soins qu’ils reçoivent. Malgré cela, seul un nombre limité d’écoles de médecine intègrent un enseignement formel sur la sensibilisation à la surdité. Cette revue étudie la manière dont la formation aux compétences en matière de la surdité peut être intégrée dans l’enseignement médical afin de sensibiliser les étudiants et d’améliorer les résultats en matière de santé pour la communauté sourde et malentendante (SM). Les articles ont été recherchés dans PubMed, EMBASE et OVID Medline en utilisant des termes et des mots-clés MeSH (acronyme anglais : Medical Subject Headings). Les études ont été retenues si elles étaient publiées en anglais, si elles portaient sur des étudiants en médecine et si elles traitaient des avantages de la sensibilisation à la surdité et de la formation à la langue des signes américaine (acronyme anglais : ASL). Les critères d’exclusion comprenaient les études non pertinentes pour les étudiants en médecine, les contextes non médicaux, les articles incomplets et les études rétractées. La revue a analysé neuf articles pertinents couvrant un total de 959 participants. Il a été constaté que les ateliers de développement professionnel augmentaient de manière significative la sensibilisation à la surdité et amélioraient les attitudes des étudiants en médecine. Ces ateliers ont notamment favorisé une meilleure compréhension des défis uniques auxquels est confrontée la communauté SM, soulignant l’importance de stratégies de communication efficaces dans les milieux cliniques. Cependant, la littérature limitée sur la formation à la sensibilisation à la surdité dans les programmes d’études médicales, associée à la petite taille des échantillons dans les études existantes, limite la capacité à tirer des conclusions définitives. Les recherches futures devraient donner la priorité à l’élaboration de programmes de formation à la sensibilisation à la surdité cliniquement pertinents et spécifiques à une spécialité, tout en envisageant également des durées d’atelier plus longues pour améliorer l’efficacité. De telles initiatives pourraient en fin de compte améliorer les résultats en matière de santé pour la communauté SM et promouvoir des soins de santé plus inclusifs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".