title: Virtual reality robotic surgical simulation: an analysis of gynecology trainees.
abstract: OBJECTIVE
  To analyze the learning curves of gynecology trainees on several virtual reality da Vinci Skills Simulator exercises.
  
  
  METHODS
  Prospective cohort pilot study.
  
  
  METHODS
  Academic hospital-based gynecology training program.
  
  
  METHODS
  Novice robotic surgeons from a gynecology training program.
  
  
  METHODS
  Novice robotic surgeons from an academic gynecology training program completed 10 repetitions of 4 exercises on the da Vinci Skills Simulator: matchboard, ring and rail, suture sponge, and energy switching. Performance metrics measured included time to completion, economy of instrument movement, excessive force, collisions, master workspace range, missed targets, misapplied energy, critical errors, and overall score. Statistical analyses were conducted to define the learning curve for trainees and the optimal number of repetitions for each exercise.
  
  
  RESULTS
  A total of 34 participants were enrolled, of which 9 were medical students, 22 were residents, and 3 were fellows. There was a significant improvement in performance between the 1st and 10th repetitions across multiple metrics for all exercises. Senior trainees performed the suture exercise significantly faster than the junior trainees during the first and last repetitions (p = 0.004 and p = 0.003, respectively). However, the performance gap between seniors and juniors narrowed significantly by the 10th repetition. The mean number of repetitions required to achieve performance plateau ranged from 6.4 to 9.3.
  
  
  CONCLUSIONS
  Virtual reality robotic simulation improves ability through repetition at all levels of training. Further, a performance plateau may exist during a single training session. Larger studies are needed to further define the most high-yield simulator exercises, the ideal number of repetitions, and recommended intervals between training sessions to improve operative performance.
authors.affiliation: Department of Gynecology and Obstetrics, Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: Sangini S
authors.initials: SS
authors.lastname: Sheth
authors.affiliation: Department of Gynecology and Obstetrics, Johns Hopkins Medical Institutions, Baltimore, Maryland; Department of Obstetrics and Gynecology, Section of Gynecologic Oncology, Greater Baltimore Medical Center, Baltimore, Maryland.
authors.forename: Amanda N
authors.initials: AN
authors.lastname: Fader
authors.affiliation: Department of Gynecology and Obstetrics, Johns Hopkins Medical Institutions, Baltimore, Maryland; Department of Obstetrics and Gynecology, Section of Gynecologic Oncology, Greater Baltimore Medical Center, Baltimore, Maryland.
authors.forename: Ana I
authors.initials: AI
authors.lastname: Tergas
authors.affiliation: Department of Gynecology and Obstetrics, Johns Hopkins Medical Institutions, Baltimore, Maryland; Department of Obstetrics and Gynecology, Section of Gynecologic Oncology, Greater Baltimore Medical Center, Baltimore, Maryland.
authors.forename: Christina L
authors.initials: CL
authors.lastname: Kushnir
authors.affiliation: Department of Gynecology and Obstetrics, Johns Hopkins Medical Institutions, Baltimore, Maryland. Electronic address: igreen5@jhmi.edu.
authors.forename: Isabel C
authors.initials: IC
authors.lastname: Green
mesh_terms: D000328:Adult; D015331:Cohort Studies; D005260:Female; D013509:Gynecologic Surgical Procedures / Q000193:education*; D006801:Humans; D059032:Learning Curve; D008297:Male; D010865:Pilot Projects; D011446:Prospective Studies; D012371:Robotics; D014584:User-Computer Interface
keywords: Patient Care; Practice-Based Learning and Improvement; computer simulation; gynecologic surgery; minimally invasive/education; robotics; surgical procedures