The mind’s scalpel in surgical education: a randomised controlled trial of mental imagery
Bibliographic record
Abstract
OBJECTIVE: To evaluate the role of mental imagery (MI) in resident training for a complex surgical procedure. DESIGN: Randomised controlled trial. SETTING: Eight centres across Canada and the USA. POPULATION: Junior gynaecology residents who had performed fewer than five vaginal hysterectomies (VH). METHODS: After performing a pretest VH, junior gynaecology residents were randomised to standard MI versus textbook reading (No MI) and then performed a test VH. Surgeons blinded to group evaluated resident performance on the pretest and test VH via global rating scales (GRS), procedure-specific scales and intraoperative parameters. Residents evaluated their own performance. MAIN OUTCOME MEASURE: Change in surgeon GRS score from pretest to test VH. The study was powered to detect a 20% difference in score change. RESULTS: Fifty residents completed the trial (24 MI, 26 No MI). There was no difference in GRS score change via blinded assessment from pretest to test evaluation between groups (mean change 13% [SD 17] versus 7% [SD 14], P = 0.192). There was no difference in procedure-specific score change. There was a significant difference in self-scored GRS score change between groups (mean change 19% [SD 12] versus 9% [SD 11], P = 0.005). Residents also felt more confident performing a VH (mean change 19% [SD 16] MI versus 11% [SD 10] No MI, P = 0.033). CONCLUSIONS: No difference was observed in the surgical performance of residents after MI. Improved resident self-confidence may be attributable to MI or the effect of unblinding on trial 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".