Application of stereoscopic visualization on surgical skill acquisition in novices
Bibliographic record
Abstract
This study examines the influence of monoscopic vs. stereoscopic visualization in novice trainees performing the MISTELS, a validated laparoscopic skill evaluation system consisting of 5 distinct tasks. We hypothesize a difference in performance based on visualization modality. First and second year medical students (n=31) performed the MISTELS battery of tasks using either monoscopic or stereoscopic visualization displays. Regression analysis indicates performance was not correlated to participant manual dexterity or visual spatial ability (p>;0.05). Monoscopic visualization was shown to produce significantly better performance in the peg transfer task alone (p=0.001), with visualization modality producing no significant difference in performance of the remaining tasks (p>;0.05). Qualitatively, 57.1% of participants believed their performance was aided by stereoscopic visualization. Most participants rated the peg transfer task the least difficult task (60%), and the intracorporeal knot‐tying task the most difficult (65.9%). These results suggest the intrinsic difficulty of the MISTELS tasks may exceed a novice user's skill, rendering no benefit with additional 3D cues in naïve surgical trainees, and may serve to increase cognitive load, potentially decrease skill acquisition and learning. Grant Funding Source : Summer Research Training Program, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Canada
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".