Competency in Orthopaedic Surgery: Student Perceptions and Objective Knowledge Assessment
Bibliographic record
Abstract
Identifying knowledge gaps and predictors of performance are proven ways to implement changes to a curriculum. This cross-sectional study investigates the subjective and objective competency of 52 medical students at McGill University in musculoskeletal (MSK) medicine, with a focus on orthopaedic surgery. We surveyed medical students to assess their confidence levels in orthopaedic surgery and their perceptions of its teaching. The students then completed a 25-question orthopaedics-focused exam as an objective assessment of their knowledge. Descriptive statistics were calculated, exam performance was compared across academic years, predictors of exam scores were analyzed, and student self-assessment accuracy was evaluated. Students reported lower confidence in orthopaedic surgery than in many other specialties, exam scores varied significantly across academic years (p = 0.007), and predicted exam performance was the only significant predictor of test score in multiple linear regression (R2 = 0.313, p = 0.025). Calibration analysis revealed a substantial miscalibration, where students with higher predicted scores tended to overestimate their performance, while those with lower predictions tended to underestimate themselves (intercept = 27.2, slope = 0.54). A Bland–Altman plot demonstrated wide limits of agreement between predicted and actual scores (mean bias −1.2%, 95% LoA −35.0% to +32.6%). These findings highlight meaningful orthopaedic knowledge gaps and miscalibrated self-assessment, emphasizing the need for targeted, structured educational interventions in the MSK curriculum.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".