title: Face and construct validation of a virtual peg transfer simulator.
abstract: BACKGROUND
  The Fundamentals of Laparoscopic Surgery (FLS) trainer box is now established as a standard for evaluating minimally invasive surgical skills. A particularly simple task in this trainer box is the peg transfer task which is aimed at testing the surgeon's bimanual dexterity, hand-eye coordination, speed, and precision. The Virtual Basic Laparoscopic Skill Trainer (VBLaST) is a virtual version of the FLS tasks which allows automatic scoring and real-time, subjective quantification of performance without the need of a human proctor. In this article we report validation studies of the VBLaST peg transfer (VBLaST-PT) simulator.
  
  
  METHODS
  Thirty-five subjects with medical background were divided into two groups: experts (PGY 4-5, fellows, and practicing surgeons) and novices (PGY 1-3). The subjects were asked to perform the peg transfer task on both the FLS trainer box and the VBLaST-PT simulator; their performance was evaluated based on established metrics of error and time. A new length of trajectory (LOT) metric has also been introduced for offline analysis. A questionnaire was used to rate the realism of the virtual system on a 5-point Likert scale.
  
  
  RESULTS
  Preliminary face validation of the VBLaST-PT with 34 subjects rated on a 5-point Likert scale questionnaire revealed high scores for all aspects of simulation, with 3.53 being the lowest mean score across all questions. A two-tailed Mann-Whitney test performed on the total scores showed significant (p = 0.001) difference between the groups. A similar test performed on the task time (p = 0.002) and the LOT (p = 0.004) separately showed statistically significant differences between the experts and the novices (p < 0.05). The experts appear to be traversing shorter overall trajectories in less time than the novices.
  
  
  CONCLUSIONS
  VBLaST-PT showed both face and construct validity and has promise as a substitute for the FLS for training peg transfer skills.
authors.affiliation: Center for Modeling, Simulation and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. arikav@rpi.edu
authors.forename: Venkata S
authors.initials: VS
authors.lastname: Arikatla
authors.forename: Ganesh
authors.initials: G
authors.lastname: Sankaranarayanan
authors.forename: Woojin
authors.initials: W
authors.lastname: Ahn
authors.forename: Amine
authors.initials: A
authors.lastname: Chellali
authors.forename: Suvranu
authors.initials: S
authors.lastname: De
authors.forename: G L
authors.initials: GL
authors.lastname: Caroline
authors.forename: John
authors.initials: J
authors.lastname: Hwabejire
authors.forename: Marc
authors.initials: M
authors.lastname: DeMoya
authors.forename: Steven
authors.initials: S
authors.lastname: Schwaitzberg
authors.forename: Daniel B
authors.initials: DB
authors.lastname: Jones
mesh_terms: D000328:Adult; D002983:Clinical Competence; D003198:Computer Simulation; D003199:Computer Systems; D004521:Educational Measurement / Q000379:methods*; D018961:Educational Technology / Q000295:instrumentation*; D056228:Feedback, Sensory; D006801:Humans; D010535:Laparoscopy / Q000193:education*; D008962:Models, Theoretical; D011214:Practice, Psychological; D011597:Psychomotor Performance; D012984:Software; D011795:Surveys and Questionnaires; D014110:Touch; D014584:User-Computer Interface