PD6-06 VALIDATION OF A NOVEL INANIMATE URETEROSCOPY TRAINING MODEL AND A SIMULATION-BASED FLEXIBLE URETEROSCOPY TRAINING COURSE
Bibliographic record
Abstract
You have accessJournal of UrologyTechnology & Instruments: Surgical Education & Skills Assessment I1 Apr 2014PD6-06 VALIDATION OF A NOVEL INANIMATE URETEROSCOPY TRAINING MODEL AND A SIMULATION-BASED FLEXIBLE URETEROSCOPY TRAINING COURSE Andrea Lantz, Udi Blankstein, R.John D'A. Honey, Michael Ordon, Kenneth T. Pace, and Jason Y. Lee Andrea LantzAndrea Lantz More articles by this author , Udi BlanksteinUdi Blankstein More articles by this author , R.John D'A. HoneyR.John D'A. Honey More articles by this author , Michael OrdonMichael Ordon More articles by this author , Kenneth T. PaceKenneth T. Pace More articles by this author , and Jason Y. LeeJason Y. Lee More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.514AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES By creating a low-stakes learning environment that permits deliberate practice and timely feedback, simulation-based training (SBT) modalities have grown in popularity over recent years. The educational value of surgical simulators, however, is only as good as the curriculum in which they are utilized. We designed a simulation-based flexible ureteroscopy (fURS) training course utilizing a novel inanimate training model (Cook® URS model). We set out to evaluate the new curriculum and validate the Cook® URS model. METHODS A SBT curriculum was designed for Jr level (PGY1-3) urology residents at the University of Toronto and included a didactic lecture, focusing on fundamental urolithiasis management principles and basic fURS techniques, a hands-on demonstration of the various instrumentation and skills required for fURS, and 3 independent practice sessions using the Cook® URS model. Both baseline pre-test and post-course assessment of fURS skill was conducted for a standardized task; fURS with basket manipulation of lower pole stone into the upper pole. Performances were video recorded and later reviewed by 2 blinded experts using a validated assessment device. RESULTS A total of 10 residents participated in the fURS course. There was a significant difference in mean pre- and post-course task completion times (15.8 vs 9.4 mins, p<0.01) and performance scores (19.20 vs 25.25, p<0.01). Eighty percent of participants rated the Cook® URS model as realistic (≥4/5, mean=4.20) and 5 independent endourology experts rated the model as useful as a training device (≥4/5, mean=4.90), providing both face and content validity. There was also significant correlation (p<0.05) between prior fURS experience and mean overall performance scores, task completion times, passing ratings, movement efficiency, instrument handling, and flow of procedure scores (Figure 1), demonstrating construct validity for the Cook® URS model. The fURS global rating scale demonstrated good reliability, (Cronbach’s alpha = 0.848). CONCLUSIONS Our study demonstrated that a SBT curriculum for fURS can lead to improved short-term technical skills amongst Jr level urology residents. The Cook® URS model demonstrated face, content and construct validity. Further study is required. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e132 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Andrea Lantz More articles by this author Udi Blankstein More articles by this author R.John D'A. Honey More articles by this author Michael Ordon More articles by this author Kenneth T. Pace More articles by this author Jason Y. Lee More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".