MP73-06 IMPACT OF SURGICAL COACHING ON FACULTY TEACHING SKILLS AND TRAINEE LEARNING EXPERIENCE
Bibliographic record
Abstract
You have accessJournal of UrologySurgical Technology & Simulation: Training & Skills Assessment (MP73)1 May 2024MP73-06 IMPACT OF SURGICAL COACHING ON FACULTY TEACHING SKILLS AND TRAINEE LEARNING EXPERIENCE Hailey Silverii, Nicolas Fernandez, Jennifer Ahn, Maya Gopalan, Apeksha Gupta, Thomas Lendvay, Kathleen Kieran, Byron Joyner, Margarett Shnorhavorian, Mark Cain, and Paul Merguerian Hailey SilveriiHailey Silverii , Nicolas FernandezNicolas Fernandez , Jennifer AhnJennifer Ahn , Maya GopalanMaya Gopalan , Apeksha GuptaApeksha Gupta , Thomas LendvayThomas Lendvay , Kathleen KieranKathleen Kieran , Byron JoynerByron Joyner , Margarett ShnorhavorianMargarett Shnorhavorian , Mark CainMark Cain , and Paul MerguerianPaul Merguerian View All Author Informationhttps://doi.org/10.1097/01.JU.0001009564.26544.1c.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Surgical coaching has been shown to improve surgeons' teaching abilities; however, such a coaching model has not been formally studied within pediatric urology. In this study, we implemented an expert coaching model focused on faculty development and aimed to assess the impact of the model on surgeon teaching abilities and the trainee experience. METHODS: Survey data were collected via REDCap-hosted anonymous surveys including de novo designed questions for trainee environment collected by operating room staff (360 Review), Zwisch scale (ZS) collected by coach, coachee, and trainee to assess trainee autonomy, and the Systematic Evaluation of Teaching Qualities (SETQ) completed by trainees following each case in the model (see Figure 1). The survey data from quarter 1 (July 1, 2023 -September 30, 2023) were analyzed descriptively. RESULTS: Fifteen cases were included within the quarter: six open cases and nine robotic cases. Trainee level ranged from PGY 2-PGY 7. There was at least 1 trainee present for all cases, and 2 trainees present for 46.7% of cases . OR staff response rate for 360 Review surveys was 48.0%. Trainee response rate for assessments (SETQ, ZS) was 54.5%, while coach and coachee response rates were 100% and 93.3% respectively (ZS). 360 Review surveys suggest an overwhelmingly positive and engaging environment for trainees (Figure 2). ZAS aligned only 28.6% between coach-coachee, and 50% of the time between coach-trainee and coachee-trainee dyads. ZAS varied per case but trended upwards with advanced training. SETQ scores varied between coachees; however, median scores were consistently above 4 for all domains (on a scale of 1-5). CONCLUSIONS: Early data from a newly implemented coaching program suggest that the trainee environment is positive, though perception of autonomy differs between stakeholders. Teaching evaluations are overall positive but further data are needed to assess whether improvement in coachee SETQ scores is seen with further coaching. The faculty goal-setting coaching model may be applicable, and beneficial to primary resident training paradigms. Download PPTDownload PPT Source of Funding: Training and Human Performance Research Grant. Intuitive Foundation. Grant Awarded for 7/2023-6/2024 © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e1183 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Hailey Silverii More articles by this author Nicolas Fernandez More articles by this author Jennifer Ahn More articles by this author Maya Gopalan More articles by this author Apeksha Gupta More articles by this author Thomas Lendvay More articles by this author Kathleen Kieran More articles by this author Byron Joyner More articles by this author Margarett Shnorhavorian More articles by this author Mark Cain More articles by this author Paul Merguerian 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.668 | 0.221 |
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".