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Face and content validation of a Virtual Translumenal Endoscopic Surgery Trainer (VTEST™)

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Abstract

Background

Natural orifice translumenal endoscopic surgery (NOTES) is an emerging surgical paradigm, where peritoneal access is achieved through one of the natural orifices of the body. It is being reported as a safe and feasible surgical technique with significantly reduced external scarring. Virtual Translumenal Endoscopic Surgical Trainer (VTEST™) is the first virtual reality simulator for the NOTES. The VTEST™ simulator was developed to train surgeons in the hybrid transvaginal NOTES cholecystectomy procedure. The initial version of the VTEST™ simulator underwent face validation at the 2013 Natural Orifice Surgery Consortium for Assessment and Research (NOSCAR) summit. Several areas of improvement were identified as a result, and the corresponding modifications were implemented in the simulator. This manuscript outlines the results of the subsequent evaluation study, performed in order to assess the face and content validity of the latest VTEST™ simulator.

Methods

Twelve subjects participated in an institutional review board-approved study that took place at the 2014 NOSCAR summit. Six of the 12 subjects, who are experts with NOTES experience, were used for face and content validation. The subjects performed the hybrid transvaginal NOTES cholecystectomy procedure on VTEST™ that included identifying the Calot’s triangle, clipping and cutting the cystic duct/artery, and detaching the gallbladder. The subjects then answered five-point Likert scale feedback questionnaires for face and content validity.

Results

Overall, subjects rated 12/15 questions as 3.0 or greater (60 %), for face validity questions regarding the realism of the anatomical features, interface, and the tasks. Subjects also highly rated the usefulness of the simulator in learning the fundamental NOTES technical skills (3.50 ± 0.84). Content validity results indicate a high level of usefulness of the VTEST™ for training prior to operating room experience (4.17 ± 0.75).

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Acknowledgments

This work is supported by NIH/NIBIB 5R01EB010037, 1R01EB009362, 2R01EB005807.

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Authors and Affiliations

  1. Center for Modeling, Simulation and Imaging in Medicine (CeMSIM), Rensselaer Polytechnic Institute, 110, 8th Street, Troy, NY, 12180, USA

    Denis Dorozhkin, Arun Nemani, Woojin Ahn, Saurabh Dargar, Ganesh Sankaranarayanan & Suvranu De

  2. Gastrointestinal Surgery, Yale School of Medicine, Yale University, New Haven, CT, USA

    Kurt Roberts

  3. Computer Science Department, University of Central Arkansas, Conway, AR, USA

    Tansel Halic

  4. Biomedical, Industrial and Human Factors Engineering, College of Engineering and Computer Science, Wright State University, Dayton, OH, USA

    Jinling Wang & Caroline G. L. Cao

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  1. Denis Dorozhkin
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  2. Arun Nemani
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  3. Kurt Roberts
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  4. Woojin Ahn
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  6. Saurabh Dargar
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  7. Jinling Wang
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  8. Caroline G. L. Cao
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  9. Ganesh Sankaranarayanan
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  10. Suvranu De
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Corresponding author

Correspondence to Suvranu De.

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Disclosures

Dr. Kurt Roberts: NovaTract Surgical (ownership, intellectual property). Drs. Denis Dorozhkin, Arun Nemani, Woojin Ahn, Tansel Halic, Saurabh Dargar, Jinling Wang, Caroline Cao, Ganesh Sankaranarayanan, and Suvranu De have no conflicts of interest or financial ties to disclose.

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Dorozhkin, D., Nemani, A., Roberts, K. et al. Face and content validation of a Virtual Translumenal Endoscopic Surgery Trainer (VTEST™). Surg Endosc 30, 5529–5536 (2016). https://doi.org/10.1007/s00464-016-4917-7

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  • DOI: https://doi.org/10.1007/s00464-016-4917-7

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