Virtual Reality Compared with Bench-Top Simulation in the Acquisition of Arthroscopic Skill
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Notice bibliographique
Résumé
BACKGROUND: Work-hour restrictions as set forth by the Accreditation Council for Graduate Medical Education (ACGME) and other governing bodies have forced training programs to seek out new learning tools to accelerate acquisition of both medical skills and knowledge. As a result, competency-based training has become an important part of residency training. The purpose of this study was to directly compare arthroscopic skill acquisition in both high-fidelity and low-fidelity simulator models and to assess skill transfer from either modality to a cadaveric specimen, simulating intraoperative conditions. METHODS: Forty surgical novices (pre-clerkship-level medical students) voluntarily participated in this trial. Baseline demographic data, as well as data on arthroscopic knowledge and skill, were collected prior to training. Subjects were randomized to 5-week independent training sessions on a high-fidelity virtual reality arthroscopic simulator or on a bench-top arthroscopic setup, or to an untrained control group. Post-training, subjects were asked to perform a diagnostic arthroscopy on both simulators and in a simulated intraoperative environment on a cadaveric knee. A more difficult surprise task was also incorporated to evaluate skill transfer. Subjects were evaluated using the Global Rating Scale (GRS), the 14-point arthroscopic checklist, and a timer to determine procedural efficiency (time per task). Secondary outcomes focused on objective measures of virtual reality simulator motion analysis. RESULTS: Trainees on both simulators demonstrated a significant improvement (p < 0.05) in arthroscopic skills compared with baseline scores and untrained controls, both in and ex vivo. The virtual reality simulation group consistently outperformed the bench-top model group in the diagnostic arthroscopy crossover tests and in the simulated cadaveric setup. Furthermore, the virtual reality group demonstrated superior skill transfer in the surprise skill transfer task. CONCLUSIONS: Both high-fidelity and low-fidelity simulation trainings were effective in arthroscopic skill acquisition. High-fidelity virtual reality simulation was superior to bench-top simulation in the acquisition of arthroscopic skills, both in the laboratory and in vivo. Further clinical investigation is needed to interpret the importance of these results.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle