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Record W4416210711 · doi:10.1302/1358-992x.2025.13.021

RANDOMIZED CONTROLLED TRIAL COMPARING THE EFFICACY OF IMMERSIVE VIRTUAL REALITY AND TRADITIONAL PHYSICAL ARTHROSCOPY SIMULATORS IN ARTHROSCOPIC TRAINING

2025· article· en· W4416210711 on OpenAlexaff
Robert Koucheki, Matthew J. Raleigh, Trina Hauer, Jesse Wolfstadt, J. Larouche, David Backstein, Jaskarndip Chahal, Peter C. Ferguson, Johnathan R. Lex

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVirtual realityRandomized controlled trialSession (web analytics)ArthroscopyTask (project management)Virtual trainingSimulation trainingTraining (meteorology)

Abstract

fetched live from OpenAlex

Surgical simulation using virtual reality (VR) technology is a novel, risk-free modality for developing the technical skills of surgical trainees. This study aimed to compare the development of arthroscopic skills following training with an immersive VR arthroscopy simulator to a physical arthroscopy simulator. Eligible participants were randomized into one of four groups: VR3 (three VR training sessions), VR1 (one VR training session), physical simulator, and no training (Figure 1). Participants were medical students with no previous arthroscopy experience. Training metrics and testing performance were evaluated using the global rating scale (GRS) scoring system and standardized rater assessments. Qualitative questionnaires were administered to assess participant experiences and perceptions of the simulators. Out of 38 initial respondents, 29 participants met eligibility criteria and were randomized. The training metrics analysis showed that the VR3 training group exhibited significantly better performance over time compared to the VR1 group. Intragroup analysis within the VR3 group revealed improvements in precision, rotating, periscoping, and object tracking skills from first session to last session. The physical simulator group had significantly better GRS scores in terms of instrumental and camera dexterity compared to the no training group (Figure 2). No other significant differences were found among the four groups in all other components of the GRS. VR3 had a shorter task completion time compared to the VR1 and no training groups. Change in confidence levels did not vary significantly among the groups. The repeated use of the physical arthroscopy simulator was perceived to provide additional benefit and continued learning compared to the VR groups (p=0.039). Participants reported high levels of enjoyment, learning, and understanding across all groups. Strengths and limitations of both the IVR and physical simulators were identified based on participant feedback. The findings of this study suggest that non-anatomic VR and physical arthroscopy simulators provide similar training benefits, with physical arthroscopy simulators demonstrating slightly more favorable outcomes in some training metrics. However, VR, may be a viable option for arthroscopic training due to its cost-effectiveness and portability. These findings highlight the potential of VR in surgical education. For any figures or tables, please contact the authors directly.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.046
GPT teacher head0.324
Teacher spread0.278 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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