MP17-07 FIVE YEARS OF COMPETENCT-BASED MEDICAL EDUCATION IN CANADIAN UROLOGY: A NATIONAL SURVEY OF RESIDENT AND FACULTY SATISFACTION AND PERSPECTIVES
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Résumé
You have accessJournal of UrologyEducation Research I (MP17)1 May 2024MP17-07 FIVE YEARS OF COMPETENCT-BASED MEDICAL EDUCATION IN CANADIAN UROLOGY: A NATIONAL SURVEY OF RESIDENT AND FACULTY SATISFACTION AND PERSPECTIVES David-Dan Nguyen, Marie-Lyssa Lafontaine, Uday Mann, Nicolas Siron, Julien Letendre, Mélanie Aubé-Péterkin, Keith Rourke, Trustin Domes, Jason Lee, and Naeem Bhojani David-Dan NguyenDavid-Dan Nguyen , Marie-Lyssa LafontaineMarie-Lyssa Lafontaine , Uday MannUday Mann , Nicolas SironNicolas Siron , Julien LetendreJulien Letendre , Mélanie Aubé-PéterkinMélanie Aubé-Péterkin , Keith RourkeKeith Rourke , Trustin DomesTrustin Domes , Jason LeeJason Lee , and Naeem BhojaniNaeem Bhojani View All Author Informationhttps://doi.org/10.1097/01.JU.0001008628.15460.84.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: In 2018, the Royal College of Physicians and Surgeons of Canada introduced Competency-Based Medical Education (CBME) into the curriculum of Canadian urology residency programs, aligning with the global trend seen in several other countries. This research endeavors to delve into the perspectives of program directors and senior residents within the 13 Canadian urology residency programs regarding their experiences and perceptions of CBME. METHODS: Two online surveys were developed based on a scoping review of CBME literature and reviewed by urology medical education experts. The first survey, comprising 41 questions, was for residents, while the second, with 43 questions, was for program directors/faculty. These surveys included both qualitative and quantitative questions, exploring various aspects of CBME, such as critical activities, early outcomes, unintended consequences, overall satisfaction, and ongoing challenges. The surveys were distributed to Canadian urology residency program directors, faculty members, Post-Graduate Year 4 (PGY-4), and PGY-5 residents from January to April 2023. Respondents anonymously rated their agreement or disagreement with statements using a five-point Likert Scale, where scores ranged from 1 (strongly disagree/very dissatisfied) to 5 (strongly agree/very satisfied). Descriptive analyses considered scores of 4 or 5 as agreement/satisfaction and scores of 1 or 2 as disagreement/dissatisfaction. RESULTS: Twenty-nine faculty members (including 10/13 [77%] program directors) and 33/63 (53%) of senior residents. Among all respondents, 73% are dissatisfied with CBME (70% of faculty members and 75% of senior residents). Most respondents have experienced anxiety and/or fatigue associated with CBD (88% of faculty members and 70% of senior residents). CBD is burdensome for residents who overwhelmingly trigger assessment requests (90% of residents) while faculty members are overwhelmed by the number of assessments requested (80% of faculty). Both faculty members (80%) and residents (95%) find that CBD is time-consuming. A majority (>70%) of respondents find that CBD has failed to de-emphasize time-based learning, individualize pathways of progression, identify struggling fashion in a timelier fashion, and enhance the quality of feedback provided. However, most respondents (>60%) find that CBD has established clear learning expectations and training stages for trainees and increased the quantity of feedback while not compromising patient care. Senior residents favored a return to a time-based model (58%), whereas faculty members were divided between improving CBME or returning to a time-based model, while program directors leaned towards improving CBME (70%). CONCLUSIONS: There is a prevailing sense of dissatisfaction with CBME within Canadian urology, as perceived by senior residents and faculty members. CBME adversely impacts the well-being of both faculty and residents, leading to increased stress and fatigue, while falling short of delivering personalized medical education. CBME has positively impacted medical education by providing a structured and transparent framework for trainee advancement. This valuable insight calls for informed decisions and continuous efforts to enhance CBME in urology. Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e293 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information David-Dan Nguyen More articles by this author Marie-Lyssa Lafontaine More articles by this author Uday Mann More articles by this author Nicolas Siron More articles by this author Julien Letendre More articles by this author Mélanie Aubé-Péterkin More articles by this author Keith Rourke More articles by this author Trustin Domes More articles by this author Jason Lee More articles by this author Naeem Bhojani More articles by this author Expand All Advertisement PDF downloadLoading ...
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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,002 |
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 ».