Strategies to Improve Acquistion of Technical Skill in Surgical Residents: From Screening Technical Ability at the Time of Selection to Incorporating Performance Adjuncts during Training
Bibliographic record
Abstract
Introduction: Evidence suggests that not all trainees reach technical competence. Therefore the purposes of the included studies were to improve resident selection by investigating screening tools (visual spatial tests (VSTs) and technical tasks (TTs)) that may predict technical ability of incoming trainees, and to determine whether metal practice is beneficial as a performance enhancement strategy during training.\nMethods: Screening with VSTs as a predictor of laparoscopic ability was evaluated using the PicSOr, cube comparison (CC) and card rotation (CR) tests and correlated to technical performance on the camera navigation (LCN) and laparoscopic circle cut (LCC) tasks. To screen trainees using TTs, a Delphi of Canadian general surgery (GS) program directors (PD), was performed to gain consensus on the simulated TTs best suited for incoming trainees. K-mean clustering learning curve (LC) analysis was used to determine acquisition of TTs. Next, mental practice was evaluated in a randomized control trial to assess its impact on advanced laparoscopic technical performance. \nResults: Thirty-seven residents were screened using VSTs. Residents who scored higher on the CC test had more accurate LCN path length (rs(PL) =-0.36, p=0.03) and angle path (rs(AP) =-0.426, p=0.01) scores. Eleven of 14 GS PDs participated in the Delphi, and consensus was reached that both basic laparoscopic and open skills would be appropriate for the assessment of TTs. LC analysis of 65 students revealed that 7-15% of trainees did not reach proficiency in laparoscopic skills. These students demonstrated poor innate ability, and remained disadvantaged with inconsistent performance throughout their LC. During training, mental practice significantly improved technical performance (p =0â 003). \nConclusion: LC analysis of simulated technical skills proved more dependable than VSTs to screen for technical ability in novice trainees, while mental practice is an affective adjunct to technical skills performance and would be a beneficial addition to skills training for senior residents.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".