Evaluation and usability study of low-cost laparoscopic box trainer “Lap-Pack”: a 2-stage multicenter cohort study
Bibliographic record
Abstract
Introduction: Laparoscopic training is restricted in low resource settings due to limited access to specialist training equipment and financial constraints. This study aimed to evaluate simulation skills and usability of an original low-cost laparoscopic trainer, the “Lap-Pack,” developed at the University of Leeds, UK. Methods: Stage I evaluation was conducted in Kolkata (India) between March, 12 and 14, 2019. Laparoscopic simulation training was based on the 5 domains of fundamentals of laparoscopic surgery (FLS), which assessed skill acquisition across 7 rural surgeons from North-East India. The McGill Inanimate System for Training and Evaluation of Laparoscopic Skills (MISTELS) criteria was used to statistically analyze trainee performance between pretraining and posttraining sessions. Also, Lap-Pack was qualitatively compared with a commercial box trainer, Inovus Pyxus HD (IPHD). Stage II involved a multi-center usability study in 2 centers of India and the United Kingdom (2019). Seventy-eight participants performed 2 FLS tasks using Lap-Pack and provided scores on a 25-point questionnaire, including a preestablished Face-Validity Criteria and 4 evaluation categories—Usability, Camera, View, and, Material. Results: In stage I, the total posttraining MISTELS score for Lap-Pack was higher, that is 773.37 (SD: 183.67) than pretraining score, that is 351.2 (SD: 471.5). The posttraining scores showed laparoscopic skill acquisition with statistically significant ( P <0.05) difference for precision cutting, intracorporeal and extracorporeal knot. In stage II, Lap-Pack scored highly in Face-Validity with a combined mean score of 4.81 [95% confidence interval (CI): 4.52–5.09, P <0.05] out of a possible 6. It scored highest (scale: 1=low to 7=high) in Usability 6.14 (95% CI: 6.05–6.22, P <0.05) and Camera 6.14 (95% CI: 6.01–6.27, P <0.05). The “Lightweight” (6.46, 95% CI: 6.32–6.60, P <0.05) and “Portability” (6.35, 95% CI: 6.18–6.51, P <0.05) features of Lap-Pack were appreciated. Conclusion: The Lap-Pack is a suitable low fidelity simulator for laparoscopic training in a low-resource setting.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".