(034) EDI QUALITY IMPROVEMENT IN REPRODUCTIVE MEDICAL EDUCATION: A WORKED MODEL
Notice bibliographique
Résumé
Abstract Introduction Countless patients face challenges obtaining holistic generalist care and experience health disparities related to race/ethnicity and social structural determinants of health (SSDOH). Revisions to medical curriculum are necessary to ensure that graduates can competently provide care that is socially accountable and aligns with the needs of patients. Evidence supports the inclusion of generalist and equity, diversity and inclusion (EDI) content in curriculum to foster such competency. However, a 2022 study conducted at our medical school revealed a lack of generalism and EDI content in the case based learning (CBL) curriculum. An evidence-based process for assessing existing CBL curriculum for generalist content exists, but no process for revision has been described. While a process to revise EDI content in CBL curriculum exists, no studies to date have focused on reproductive medicine and urology content and the unique challenges associated with this area of medicine, such as the additional impact of stigma, trauma and discrimination related to pregnancy-related choice, sexual orientation or gender diversity. Objective To enhance generalist and EDI content within the Reproductive Medicine and Urology Course (RMUC) CBL curriculum. Further, to develop a worked model for enhancing generalist and EDI content in an existing CBL reproductive medicine and urology curriculum. Lastly, to provide medical graduates with the tools to provide care that is socially accountable and aligns with the current needs of patients. Methods We evaluated and revised five CBL cases in our medical school’s RMUC curriculum. We employed the Toronto Generalism Assessment Tool (T-GAT) to assess generalism, and adapted guidelines from Krishnan et al. to assess and implement the necessary changes related to EDI. Upon completion, we re-evaluated the RMUC CBL curriculum to ensure the incorporation of generalism and EDI content. We also used existing revision processes described by Bruner et al. to guide our overall approach. Results RMUC CBL cases were modified and our methods documented. Through this process, several challenges were identified and include difficulties with: (1) obtaining images due to lack of commercially available content that includes members of equity-deserving groups, (2) the time needed to appropriately incorporate SDOH already present in the cases, and (3) detecting content that was subtly paternalistic or missing a trauma-informed approach. Conclusions Generalism and EDI were lacking within the RMUC curriculum. Development of a worked model, accompanied by reflections on navigating encounters challenges, is underway. This will serve as a guide to others wishing to incorporate generalism and EDI into their reproductive medicine education programs. Disclosure No.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,007 | 0,004 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».