Arthroscopic Training Courses Improve Trainee Arthroscopy Skills: A Simulation‐Based Prospective Trial
Bibliographic record
Abstract
PURPOSE: To evaluate the correlation between timed task performance on an arthroscopy shoulder simulator and participation in a standardized expert shoulder arthroscopy educational course. METHODS: Orthopaedic trainees were voluntarily recruited from over 25 residency programs throughout the United States and Canada. Each trainee was tested on arrival at the Arthroscopy Association of North America orthopaedic learning center on a virtual reality arthroscopy shoulder simulator, and his or her performance was objectively scored. Each trainee's postgraduate year level was recorded, as was his or her experience in residency with shoulder arthroscopy as measured by Accreditation Council for Graduate Medical Education case-log totals. After the focused 4-day training curriculum consisting of didactics and cadaveric experience, each trainee was re-evaluated on the same simulator. Statistical analysis was performed to determine if participation in the course was associated with changes in simulation performance from before to after assessment. RESULTS: Forty-eight trainees completed the testing. On completion of the course, trainees showed significant improvements in all objective measures recorded by the simulator. Total probe distance needed to complete the task decreased by 42% (from 420.4 mm to 245.3 mm, P < .001), arthroscope tip distance traveled decreased by 59% (from 194.1 mm to 80.2 mm, P < .001), and time to completion decreased by 38% (from 66.8 seconds to 41.6 seconds, P < .001). Highly significant improvements in all 3 measures suggest improved instrument handling, anatomic recognition, and arthroscopy-related visual-spatial ability. CONCLUSIONS: This study shows objective improvement in orthopaedic trainee basic arthroscopy skill and proficiency after a standardized 4-day arthroscopy training curriculum. The results validate the Arthroscopy Association of North America resident training course and its curriculum with objective evidence of benefit. LEVEL OF EVIDENCE: Level III, prospective study of nonconsecutive participants.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".