Initial experiences with RoSS surgical simulator in residency training: A validity and model analysis

Marc Colaco, Adrian Balica, Daniel Su, Joseph Barone

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Robotic surgery is an important new tool in many surgical procedures, and training curriculums must adapt to this new technology. Robotic surgical simulators have been developed as a means of providing training without the inherent risks of actual surgery. The purpose of this study is to evaluate the construct validity of the RoSS surgical simulator by correlating simulator performance with amount of time in training and to create a performance model in which time in training is a parameter. A total of eight residents with varying amounts of training were given access to the RoSS surgical simulator and were evaluated on performance of a simulated surgical task. This data was then used to create Akaike information criteria to compare goodness of fit. Participants were also given a questionnaire as to their experience with the simulator and their feelings about the use of simulators in training. Training time and performance within the simulator were shown to have a linear relationship. Correlations were high, with R2 values of 0. 95, 0. 94, and 0. 86 for each of the three performance metrics. Likelihood ratios were similarly high at 4. 25 × 109, 10,950, and 362. Participant opinion showed that residents feel that robotic training is an important part of their education and that the simulator is an effective supplement. The RoSS surgical simulator accurately corresponds to training level and is a valid evaluation tool of training experience. These findings are encouraging for the use of robotic simulators in surgical training.

Original languageEnglish (US)
Pages (from-to)71-75
Number of pages5
JournalJournal of Robotic Surgery
Volume7
Issue number1
DOIs
StatePublished - Mar 2013

All Science Journal Classification (ASJC) codes

  • Surgery
  • Health Informatics

Keywords

  • Patient simulation
  • Physical education and training
  • Residency
  • Robotics

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