Role for Assessment in Maintenance of Certification: Physician Perceptions of Assessment
Bibliographic record
Abstract
INTRODUCTION: The Royal College of Physicians and Surgeons of Canada modified its Maintenance of Certification (MOC) framework in 2011 to further incentivize assessment activities compared to group and self-learning. The purpose of this study was to explore physician's perceptions of their access to assessment activities, barriers to participation in assessment, and the need for the Royal College to further support its fellows in gaining access to assessment activities. METHODS: A questionnaire-based survey was sent to all participants of the MOC program as part of a program evaluation examining recent changes to the MOC program. RESULTS: 5259 respondents contributed responses. Most physicians were comfortable with the revised framework for assessment while approximately 40% were neutral regarding whether lack of access to self-assessment activities was a problem. Respondents expressed a need for more self-assessment programs particularly those developed outside of Canada. Neither a lack of feedback about performance or discomfort with recording performance gaps was perceived as a barrier to participation in assessment activities. Physician comments were consistent with the quantitative data and elaborated on the need to develop and recognize more assessment activities. DISCUSSION: Physicians accepted the revised MOC program framework but perceived difficulty in accessing assessment programs, activities, and tools. As the framework changed again January 2014, requiring all fellows and MOC program participants to completion of at least 25 credits in each section of the MOC program (including assessment) during their new 5-year MOC cycle, additional resources will be needed to support opportunities for physicians to engage in assessment.
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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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".