title: da Vinci skills simulator for assessing learning curve and criterion-based training of robotic basic skills.
abstract: OBJECTIVE
  To answer 2 research questions: what are the learning curve patterns of novices on the da Vinci skills simulator parameters and what parameters are appropriate for criterion-based robotic training.
  
  
  METHODS
  A total of 17 novices completed 2 simulator sessions within 3 days. Each training session consisted of a warming-up exercise, followed by 5 repetitions of the "ring and rail II" task. Expert participants (n = 3) performed a warming-up exercise and 3 repetitions of the "ring and rail II" task on 1 day. We analyzed all 9 parameters of the simulator.
  
  
  RESULTS
  Significant learning occurred on 5 parameters: overall score, time to complete, instrument collision, instruments out of view, and critical errors within 1-10 repetitions (P <.05). Economy of motion and excessive instrument force only showed improvement within the first 5 repetitions. No significant learning on the parameter drops and master workspace range was found. Using the expert overall performance score (n = 3) as a criterion (overall score 90%), 9 of 17 novice participants met the criterion within 10 repetitions.
  
  
  CONCLUSIONS
  Most parameters showed that basic robotic skills are learned relatively quickly using the da Vinci skills simulator, but that 10 repetitions were not sufficient for most novices to reach an expert level. Some parameters seemed inappropriate for expert-based criterion training because either no learning occurred or the novice performance was equal to expert performance.
authors.affiliation: Department of Urology, Catharina Hospital Eindhoven, The Netherlands. wmbrinkman@gmail.com
authors.forename: Willem M
authors.initials: WM
authors.lastname: Brinkman
authors.forename: Jan-Maarten
authors.initials: JM
authors.lastname: Luursema
authors.forename: Bas
authors.initials: B
authors.lastname: Kengen
authors.forename: Barbara M A
authors.initials: BM
authors.lastname: Schout
authors.forename: J Alfred
authors.initials: JA
authors.lastname: Witjes
authors.forename: Ruud L
authors.initials: RL
authors.lastname: Bekkers
mesh_terms: D002983:Clinical Competence; D003198:Computer Simulation; D059032:Learning Curve; D012371:Robotics / Q000193:education*