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Validation of the UW Virtual Reality TURP Simulator

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Validation of the UW Virtual Reality TURP Simulator Version 1.0 Presented By: Timothy Kowalewski Robert Sweet, MD Peter Oppenheimer Suzanne Weghorst – PowerPoint PPT presentation

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Title: Validation of the UW Virtual Reality TURP Simulator


1
Validation of the UW Virtual Reality TURP
Simulator
Version 1.0
Presented By Timothy Kowalewski Robert Sweet,
MD Peter Oppenheimer Suzanne Weghorst Jeff
Berkley, Ph.D
2
What is TURP?
  • Transuretheral Resection of the Prostate
  • Gold-standard for treating obstructive urinary
    symptoms
  • Challenging to teach and learn

3
Goals of the Project
  • Overall Project Goal
  • To help streamline urological procedure education
    with the aid of simulation technology
  • Specific Goals of This Study
  • Establish validation status of Version 1.0, UW
  • TURP Simulator as a training and assessment
    tool.

4
TURP a good model for Simulation
  • Objective assessment
  • High risk to patients
  • Apparent training gap
  • Common problem


Sweet, et al. Journal of Endourology. October,
2002.
5
TURP a good model for Simulation
  • Mainstay operation
  • Apparent demand
  • Amenable to current technology

98 TURP is the Gold Standard of
care

YES
75 Validated Simulator Useful after
Residency
6
Methods
  • Simulator Construction
  • ? Virtual anatomy and visual elements
  • ? Real-time force / tactile feedback
  • ? O.R. instrumentation
  • ? External physical model
  • ? Auditory cues

7
Methods
  • Simulator Construction
  • Training Video
  • ? Definition of task and errors
  • ? Statement of goal

Efficiently resect as much tissue as possible
while avoiding errors and
minimizing blood loss, amount of irrigant used,
coagulation current and number of
cuts
Special Thanks to Anthony Gallager, Ph.D
8
Methods
  • Simulator Construction
  • Training Video
  • Pre-Task Questionnaire
  • ? Demographics, gender, professional
    experience, education, video
  • game experience, TURP-related
    questions, etc
  • ? Stratification of database

9
Methods
  • Simulator Construction
  • Training Video
  • Pre-Task Questionnaire
  • Pre-Compiled, 5-minute Task
  • ? Three trained, non-medical technicians
  • ? Consistent, pre-determined responses
  • ? Privacy and Anonymity

10
Methods
  • Simulator Construction
  • Training Video
  • Pre-Task Questionnaire
  • Pre-Compiled, 5-minute Task
  • Post-Task Questionnaire
  • ? Critique of simulator according to its
    elements
  • ? Open feedback

11
Methods
  • Simulator Construction
  • Training Video
  • Pre-Task Questionnaire
  • Pre-Compiled, 5-minute Task
  • Post-Task Questionnaire
  • AUA Annual Conference
  • ? 72 Experts
  • ? 19 Trainees
  • ? 19 Novices

12
Metrics
  • Grams of tissue resected
  • Amount of irrigant used
  • Quantity of ambient blood
  • Number and severity of bleeding vessels
  • Instrument position and interaction
  • Number of cuts at tissue
  • 12 Hz resolution
  • Combinations thereof

13
Results Face Validity
  • Do you feel the UW TURP Simulator would be useful
    as a training tool?

14
Results Face Validity
  • Would you like to see it implemented into the
    curriculum of residency programs?

15
Results Face Validity
  • Do you feel it would be useful as a tool for
    accreditation?

16
Results Content Validity
  • Categorical Standardized Likert scale of global
    acceptability

17
Results Novices vs. Experts
Result of Levene-conditioned two-tailed T-test
quantifies resolving potential of selected
metrics to determine differences between novices
and experts.
18
Results Construct Validity
Performance of Errors
19
Construct/Concurrent Validity (Cross-sectional)
  • Metrics correlations mimicked the operating
    room.
  • Experts and trainees were more efficient at
    cutting than novices. (Plt.01)
  • Experts were more efficient at coagulating
    bleeders than trainees who were more efficient
    than novices. (Plt.05, Plt.01)
  • Performance among experts did not exhibit
    decay
  • Video game experience influenced performance in
    novices and experts only.

20
Conclusions
  • Established Face and Content Validity
  • Established Construct Validity (X-sectional)
  • Addressed Concurrent Validity (incomplete)
  • NO assessment predictive validity or longitudinal
    studies

- - - For Version 1.0 - - -
21
Version 2.0Predictive and Construct Validation
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