MP17-07 FIVE YEARS OF COMPETENCT-BASED MEDICAL EDUCATION IN CANADIAN UROLOGY: A NATIONAL SURVEY OF RESIDENT AND FACULTY SATISFACTION AND PERSPECTIVES
Bibliographic record
Abstract
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 ...
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".