PD30-06 A NOVEL SYSTEM FOR TEACHING INTRAOPERATIVE LAPAROSCOPIC SKILLS USING STANDARDIZED COMMUNICATION AND AN ENDOSCOPIC MONITOR FRAME OF REFERENCE TOOL
Bibliographic record
Abstract
You have accessJournal of UrologyCME1 Apr 2023PD30-06 A NOVEL SYSTEM FOR TEACHING INTRAOPERATIVE LAPAROSCOPIC SKILLS USING STANDARDIZED COMMUNICATION AND AN ENDOSCOPIC MONITOR FRAME OF REFERENCE TOOL Kikachukwu Otiono, Jennifer Hoogenes, Kevin Kim, Bobby Shayegan, Anil Kapoor, Kevin Piercey, and Edward D. Matsumoto Kikachukwu OtionoKikachukwu Otiono More articles by this author , Jennifer HoogenesJennifer Hoogenes More articles by this author , Kevin KimKevin Kim More articles by this author , Bobby ShayeganBobby Shayegan More articles by this author , Anil KapoorAnil Kapoor More articles by this author , Kevin PierceyKevin Piercey More articles by this author , and Edward D. MatsumotoEdward D. Matsumoto More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003316.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Directional terminology in the operating room (OR) during laparoscopic surgery is a common source of confusion for trainees, as the spatial orientation of the on-screen operative field differs depending on the viewer’s perspective and frame of reference. We developed and evaluated the utility and feasibility of 2 endoscopic monitor screen overlays designed to standardize directional instruction. METHODS: For a baseline perspective on laparoscopic instruction, we video-recorded and qualitatively analyzed 20 teaching cases. We then designed and printed 2 transparent endoscopic monitor overlays: an alphanumeric grid (AG) and a clock. In a laparoscopic simulation lab, 63 medical students were randomized into 3 groups of 21: control, AG, and clock. AG and clock groups were given overlay-specific instructions. All groups completed 3 trials of 6 transfer tasks. Completion and error rates were recorded. We then trialed the overlays in 44 teaching cases in urology and general surgery (30 AG and 14 clock). All cases were video recorded, transcribed, and qualitatively analyzed. Participants completed follow-up experiential surveys with 6-point Likert scales of agreement and space for comments. RESULTS: In the baseline cases, instructors often used directional terms (e.g., screen left/right; up/down) and pointed to the screen during instruction. In the simulation study, the AG group demonstrated the lowest error rates which became significant by trial 3 (p=0.01). 6 instructors and 21 residents from urology (n=14) and general surgery (n=7) participated in the intraoperative evaluation of the overlays. Instructors rated the AG higher than the clock in improving efficiency and hand-eye coordination (p’s<0.001) and agreed that it should be used in the residency program. Trainees rated the AG higher in improving operative technique and confidence in the OR (p’s<0.001). Instructors were more likely to recommend use of the AG over the clock (p=0.004). CONCLUSIONS: We showed that an AG overlay used with standardized commands significantly improved instruction and learning during simulated and live laparoscopic cases. Further work will involve the evaluation of the economy of motion and errors while using the overlay. This could lead to the use of a heads-up display for laparoscopic and robotic training. Further exploration of instructor-trainee discourse is necessary when considering the development and implementation of new methods to improve intraoperative teaching in the era of competency-based medical education. Source of Funding: McMaster Surgical Associates, McMaster University, Hamilton, Ontario, Canada © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e833 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Kikachukwu Otiono More articles by this author Jennifer Hoogenes More articles by this author Kevin Kim More articles by this author Bobby Shayegan More articles by this author Anil Kapoor More articles by this author Kevin Piercey More articles by this author Edward D. Matsumoto More articles by this author Expand All 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.011 |
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".