Use of a Virtual Reality Simulator for Tendon Repair Training: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Virtual reality (VR) simulators have become widespread tools for training medical students and residents in medical schools. Students using VR simulators are provided with a 3D human model to observe the details by using multiple senses and they can participate in an environment that is similar to reality. OBJECTIVE: The aim of this study was to promote a new approach consisting of a shared and independent study platform for medical orthopedic students, to compare traditional tendon repair training with VR simulation of tendon repair, and to evaluate future applications of VR simulation in the academic medical field. METHODS: In this study, 121 participants were randomly allocated to VR or control groups. The participants in the VR group studied the tendon repair technique via the VR simulator, while the control group followed traditional tendon repair teaching methods. The final assessment for the medical students involved performing tendon repair with the "Kessler tendon repair with 2 interrupted tendon repair knots" (KS) method and the "Bunnell tendon repair with figure 8 tendon repair" (BS) method on a synthetic model. The operative performance was evaluated using the global rating scale. RESULTS: Of the 121 participants, 117 participants finished the assessment and 4 participants were lost to follow-up. The overall performance (a total score of 35) of the VR group using the KS method and the BS method was significantly higher (P<.001) than that of the control group. Thus, participants who received VR simulator training had a significantly higher score on the global rating scale than those who received traditional tendon repair training (P<.001). CONCLUSIONS: Our study shows that compared with the traditional tendon repair method, the VR simulator for learning tendon suturing resulted in a significant improvement of the medical students in the time in motion, flow of operation, and knowledge of the procedure. Therefore, VR simulator development in the future would most likely be beneficial for medical education and clinical practice. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2100046648; http://www.chictr.org.cn/hvshowproject.aspx?id=90180.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".