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Record W2088035138 · doi:10.1097/sla.0000000000000254

Individualized Deliberate Practice on a Virtual Reality Simulator Improves Technical Performance of Surgical Novices in the Operating Room

2013· article· en· W2088035138 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnals of Surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineVirtual realityTask (project management)CurriculumMedical physicsRating scaleLaparoscopic cholecystectomyPhysical therapyRandomized controlled trialLearning curveEducational measurementSimulationSurgeryComputer scienceHuman–computer interactionPsychology

Abstract

fetched live from OpenAlex

In Brief Objective: The purpose of this study was to investigate whether individualized deliberate practice on a virtual reality (VR) simulator results in improved technical performance in the operating room. Background: Training on VR simulators has been shown to improve technical performance in the operating room (OR). Currently described VR curricula consist of trainees practicing the same tasks until expert proficiency is reached. It has yet to be investigated whether the individualized deliberate practice, where curricula tasks vary depending on prior levels of technical proficiency, would translate into the OR. Methods: This single-blinded prospective trial randomized 16 novice surgical residents to a deliberate practice (DP) group and a conventional residency training group. Both groups performed a laparoscopic cholecystectomy in the OR that was video-recorded. Technical performance of DP group residents in the OR was assessed using 3 validated assessment tools. A score of less than 60% on any component of the assessment tool resulted in the trainee practicing a specific task on the VR simulator. The DP group practiced on the simulator as per their individualized schedule. Both groups then performed another laparoscopic cholecystectomy. A blinded expert assessed the OR recordings using a validated global rating scale. Results: Although both groups had similar technical abilities preintervention [DP: median score, 13.5 (9.3–15.0); control: median score, 14.5 (9.3–17.8); P = 0.45], the DP residents had a superior technical performance postintervention [DP: median score, 17.0 (15.3–18.5); control: median score, 12.5 (7.5–14.0); P = 0.03]. Of 8 DP residents, 6 practiced 5 basic VR tasks (median 1 trial to pass), and 7 of 8 practiced 2 advanced tasks (median 4 trials to pass). Conclusions: A curriculum of deliberate individualized practice on a VR simulator improves technical performance in the OR. This has implications to greatly improve the feasibility of implementing simulation-based curricula in residency training programs, rather then having them being limited to research protocols. Currently described simulation-based curricula consist of trainees practicing the same tasks until expert proficiency is reached. It has yet to be investigated whether the individualized deliberate practice, where curricula tasks vary depending on prior levels of technical proficiency, would translate into the operating room. This randomized controlled trial effectively demonstrates that deliberate practice on a virtual reality simulator results in an improvement in technical skills in a real clinical situation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.184
GPT teacher head0.397
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it