title: Validation of the VBLaST: A Virtual Peg Transfer Task in Gynecologic Surgeons.
abstract: OBJECTIVE
  To validate the Virtual Basic Laparoscopic Skill Trainer (VBLaST-PT; the peg transfer task) for concurrent validity based on its ability to differentiate between novice, intermediate, and expert groups of gynecologists, and the gynecologists' subjective preference between the physical Fundamentals of Laparoscopic Surgery (FLS) system and the virtual reality system.
  
  
  METHODS
  Prospective study (Canadian Task Force II-2).
  
  
  METHODS
  Academic medical center.
  
  
  METHODS
  Obstetrics and gynecology residents (n = 18) and attending gynecologists (n = 9).
  
  
  METHODS
  Twenty-seven subjects were divided into 3 groups: novices (n = 9), intermediates (n = 9), and experts (n = 9). All subjects performed 10 trials of the peg transfer on each simulator. Assessment of laparoscopic performance was based on FLS scoring, whereas a questionnaire was used for subjective evaluation.
  
  
  RESULTS
  The performance scores in the 2 simulators were nearly identical. Experts performed better than intermediates and novices in both the FLS trainer and the VBLAST, and intermediates performed better than novices in both simulators. The results also show a significant learning effect on both trainers for all subgroups; however, the greatest learning effect was in the novice group for both trainers. Subjectively, 74% participants preferred the FLS over the VBLaST for training laparoscopic surgical skills.
  
  
  CONCLUSIONS
  This study demonstrates that the peg transfer task was reproduced well in the VBLaST in gynecologic surgeons and trainees. The VBLaST has the potential to be a valuable tool in laparoscopic training for gynecologic surgeons.
authors.affiliation: Department of Obstetrics and Gynecology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts. Electronic address: cawtrey@bidmc.harvard.edu.
authors.forename: Christopher
authors.initials: C
authors.lastname: Awtrey
authors.affiliation: Department of Computer Engineering, IBISC Laboratory, University of Evry, Evry, France; Department of Surgery, Cambridge Health Alliance, Harvard Medical School, Cambridge, Massachusetts.
authors.forename: Amine
authors.initials: A
authors.lastname: Chellali
authors.affiliation: Department of Surgery, Cambridge Health Alliance, Harvard Medical School, Cambridge, Massachusetts.
authors.forename: Steven
authors.initials: S
authors.lastname: Schwaitzberg
authors.affiliation: Center for Modeling, Simulation and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, New York.
authors.forename: Suvranu
authors.initials: S
authors.lastname: De
authors.affiliation: Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts.
authors.forename: Daniel
authors.initials: D
authors.lastname: Jones
authors.affiliation: Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, Ohio.
authors.forename: Caroline
authors.initials: C
authors.lastname: Cao
mesh_terms: D000328:Adult; D002983:Clinical Competence / Q000592:standards*; D003198:Computer Simulation; D005260:Female; D006801:Humans; D010535:Laparoscopy / Q000379:methods / Q000592:standards*; D059032:Learning Curve; D011446:Prospective Studies; D015203:Reproducibility of Results; D066231:Surgeons; D013647:Task Performance and Analysis; D014584:User-Computer Interface
keywords: Laparoscopy; Surgical education; Surgical skills; Virtual trainer