Background Learning curves are essential in understanding skill acquisition and improvement, especially in complex medical procedures such as obstetrics and gynecology. Simulation training through virtual reality (VR) offers a promising way to enhance surgical skills in obstetrics and gynecology. This study aims to review studies that have used VR simulation for obstetrics and gynecology education and examined its learning curves.
Methods This is a systematic review study that was conducted according to the PRISMA guidelines. A search was conducted using the keywords virtual reality, learning curve, gynecology & obstetrics in online databases including PubMed/MEDLINE, Embase, Web of Science, Scopus, Cochrane library, Google Scholar, SID, MagIran, and Elmnet for relevant studies published until March 2024. Selected studies underwent data extraction and quality assessment. Quantitative synthesis involved pooling or combining data to draw a composite learning curve.
Results Twelve studies were included in the review, which included participants with various skill levels from novice to expert. VR simulations significantly improved the performance. Experienced surgeons consistently outperformed novices. Learning curves differed significantly between novices and experts. Novices showed significant improvements with the increase of iterations, especially after the second to sixth iterations, while experts showed shorter learning curves, with improvements occurred much earlier, indicating their higher baseline skills. The composite learning curve depicted performance improvement with increasing iterations, peaking at 84.01% at the fifth iteration, indicating effective skill acquisition over time, albeit with potential fluctuations or leveling off thereafter.
Conclusion VR offers a promising platform for increasing surgical skills in obstetrics and gynecology, with favorable learning curves showing significant improvements over time, especially among novices.
Type of Study:
Review |
Subject:
Special Received: 2024/02/23 | Accepted: 2023/05/16 | Published: 2023/07/1