Assessment of Skill Transfer From a 3D-Printed Knee Arthroscopy Simulator: A Randomized Controlled Trial
IntroductionArthroscopic surgery demands specialized skills, traditionally acquired via supervised clinical practice. Simulators offer a controlled training alternative. This study introduces a 3D-printed knee arthroscopy simulator and evaluates its effectiveness in skill transfer and acceptance in medical education, aiming to assess its utility for real arthroscopic procedures among medical students.MethodsForty final-year medical students with no prior arthroscopy experience were randomized into a simulated training group (3D-printed simulator) and a control group (video instruction). All participants performed a supervised diagnostic arthroscopy. Performance parameters (completion time, lookdowns, instrument loss, triangulation time, interventions) and Arthroscopic Surgery Skill Evaluation Tool (ASSET) scores were analyzed. Simulator acceptance was assessed via a Likert scale. Data were analyzed using appropriate parametric (Student's t-test) and non-parametric (Wilcoxon, McNemar) tests, with a significance level of 5%."ResultsThe simulated training group outperformed controls, completing arthroscopy 39% faster (<i>P</i> < .001), with 60% fewer lookdowns (<i>P</i> = .001), 59% fewer supervisor interventions (<i>P</i> < .001), 35% shorter triangulation time (<i>P</i> = .019), and 50% fewer instrument losses (<i>P</i> < .001). ASSET scores were significantly higher in all domains except safety. Participants strongly endorsed the simulator's utility and supported its integration into medical education.ConclusionThis study demonstrates the effectiveness of our low-cost, reproducible 3D-printed knee arthroscopy simulator as an effective tool for skill acquisition and transfer in individuals without prior arthroscopy experience. Training with the simulator significantly improves performance in real arthroscopic procedures.
Authors
- Álynson Larocca Kulcheski (ORCID: https://orcid.org/0000-0002-0132-6083)
- José Aguiomar Foggiatto (ORCID: https://orcid.org/0000-0001-5393-3654)
- Edmar Stieven Filho (ORCID: https://orcid.org/0000-0003-2869-4019)
- Carolline Popovicz Nunes (ORCID: https://orcid.org/0000-0002-9835-0185)
- Mário Massatomo Namba (ORCID: https://orcid.org/0000-0001-7841-3591)
- Camila Peixoto Fabri Milcent
- Paul André Alain Milcent (ORCID: https://orcid.org/0000-0001-5853-2702)
- André Luís Mion
Institutions
- Universidade Tecnológica Federal do Paraná (BR)
- Universidade Federal do Paraná (BR)
Publication Details
- Journal
- Surgical Innovation
- Published
- 2025-10-15
- DOI
- https://doi.org/10.1177/15533506251391050
- Primary Topic
- Surgical Simulation and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00