Low-fidelity simulation models in urology resident's microsurgery training

Acta Cir Bras. 2023 Dec 1:38:e386523. doi: 10.1590/acb386523. eCollection 2023.

Abstract

Purpose: To evaluate the gain of microsurgical skills and competencies by urology residents, using low-fidelity experimental models.

Methods: The study involved the use of training boards, together with a low-fidelity microsurgery simulator, developed using a 3D printer. The model consists in two silicone tubes, coated with a resin, measuring 10 cm in length and with internal and external diameters of 0.5 and 1.5 mm. The support for the ducts is composed by a small box, developed with polylactic acid. The evaluation of the gain of skills and competencies in microsurgery occurred throughout a training course consisting of five training sessions. The first sessions (S1-S4) took place at weekly intervals and the last session (S5) was performed three months after S4. During sessions, were analyzed: the speed of performing microsurgical sutures in the pre and post-training and the performance of each resident through the Objective Structure Assessment of Technical Skill (OSATS) and Student Satisfaction Self-Confidence tools in Learning (SSSCL).

Results: There was a decrease in the time needed to perform the anastomosis (p=0.0019), as well as a progressive increase in the score in the OSATS over during sessions S1 to S4. At S5, there was a slightly decrease in performance (p<0.0001), however, remaining within the expected plateau for the gain of skills and competences. The SSSCL satisfaction scale showed an overall approval rating of 96.9%, with a Cronback alpha coefficient of 83%.

Conclusions: The low-fidelity simulation was able to guarantee urology residents a solid gain in skills and competencies in microsurgery.

MeSH terms

  • Anastomosis, Surgical / education
  • Clinical Competence
  • Humans
  • Internship and Residency*
  • Microsurgery / education
  • Simulation Training*
  • Urology* / education