Literature DB >> 23914275

Validation of the da Vinci Surgical Skill Simulator across three surgical disciplines: A pilot study.

Tarek Alzahrani1, Richard Haddad, Abdullah Alkhayal, Josée Delisle, Laura Drudi, Walter Gotlieb, Shannon Fraser, Simon Bergman, Frank Bladou, Sero Andonian, Maurice Anidjar.   

Abstract

OBJECTIVE: In this paper, we evaluate face, content and construct validity of the da Vinci Surgical Skills Simulator (dVSSS) across 3 surgical disciplines.
METHODS: In total, 48 participants from urology, gynecology and general surgery participated in the study as novices (0 robotic cases performed), intermediates (1-74) or experts (≥75). Each participant completed 9 tasks (Peg board level 2, match board level 2, needle targeting, ring and rail level 2, dots and needles level 1, suture sponge level 2, energy dissection level 1, ring walk level 3 and tubes). The Mimic Technologies software scored each task from 0 (worst) to 100 (best) using several predetermined metrics. Face and content validity were evaluated by a questionnaire administered after task completion. Wilcoxon test was used to perform pair wise comparisons.
RESULTS: The expert group comprised of 6 attending surgeons. The intermediate group included 4 attending surgeons, 3 fellows and 5 residents. The novices included 1 attending surgeon, 1 fellow, 13 residents, 13 medical students and 2 research assistants. The median number of robotic cases performed by experts and intermediates were 250 and 9, respectively. The median overall realistic score (face validity) was 8/10. Experts rated the usefulness of the simulator as a training tool for residents (content validity) as 8.5/10. For construct validity, experts outperformed novices in all 9 tasks (p < 0.05). Intermediates outperformed novices in 7 of 9 tasks (p < 0.05); there were no significant differences in the energy dissection and ring walk tasks. Finally, experts scored significantly better than intermediates in only 3 of 9 tasks (matchboard, dots and needles and energy dissection) (p < 0.05).
CONCLUSIONS: This study confirms the face, content and construct validities of the dVSSS across urology, gynecology and general surgery. Larger sample size and more complex tasks are needed to further differentiate intermediates from experts.

Entities:  

Year:  2013        PMID: 23914275      PMCID: PMC3713157          DOI: 10.5489/cuaj.419

Source DB:  PubMed          Journal:  Can Urol Assoc J        ISSN: 1911-6470            Impact factor:   1.862


  17 in total

1.  Introduction and validation of the American Urological Association Basic Laparoscopic Urologic Surgery skills curriculum.

Authors:  Robert M Sweet; Rebekah Beach; Francois Sainfort; Priyanka Gupta; Troy Reihsen; Lauren H Poniatowski; Elspeth M McDougall
Journal:  J Endourol       Date:  2011-11-15       Impact factor: 2.942

2.  Robotic suturing on the FLS model possesses construct validity, is less physically demanding, and is favored by more surgeons compared with laparoscopy.

Authors:  Dimitrios Stefanidis; William W Hope; Daniel J Scott
Journal:  Surg Endosc       Date:  2010-12-24       Impact factor: 4.584

3.  The college should be instrumental in adapting simulators to education.

Authors:  Gerald B Healy
Journal:  Bull Am Coll Surg       Date:  2002-11

4.  FLS assessment of competency using simulated laparoscopic tasks.

Authors:  Gerald M Fried
Journal:  J Gastrointest Surg       Date:  2007-10-23       Impact factor: 3.452

5.  Face, content, and construct validity of dV-trainer, a novel virtual reality simulator for robotic surgery.

Authors:  Patrick A Kenney; Matthew F Wszolek; Justin J Gould; John A Libertino; Alireza Moinzadeh
Journal:  Urology       Date:  2009-04-10       Impact factor: 2.649

6.  VR robotic surgery: randomized blinded study of the dV-Trainer robotic simulator.

Authors:  Thomas S Lendvay; Pasquale Casale; Robert Sweet; Craig Peters
Journal:  Stud Health Technol Inform       Date:  2008

7.  Validation, correlation, and comparison of the da Vinci trainer(™) and the daVinci surgical skills simulator(™) using the Mimic(™) software for urologic robotic surgical education.

Authors:  Michael A Liss; Corollos Abdelshehid; Stephen Quach; Achim Lusch; Joseph Graversen; Jaime Landman; Elspeth M McDougall
Journal:  J Endourol       Date:  2012-10-02       Impact factor: 2.942

8.  da Vinci Skills Simulator construct validation study: correlation of prior robotic experience with overall score and time score simulator performance.

Authors:  Kyle T Finnegan; Anoop M Meraney; Ilene Staff; Steven J Shichman
Journal:  Urology       Date:  2012-06-15       Impact factor: 2.649

9.  Validity of the MISTELS simulator for laparoscopy training in urology.

Authors:  Breno Dauster; Andrew P Steinberg; Melina C Vassiliou; Simon Bergman; Donna D Stanbridge; Liane S Feldman; Gerald M Fried
Journal:  J Endourol       Date:  2005-06       Impact factor: 2.942

10.  Robotic-assisted minimally invasive surgery for gynecologic and urologic oncology: an evidence-based analysis.

Authors: 
Journal:  Ont Health Technol Assess Ser       Date:  2010-12-01
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  12 in total

Review 1.  Current state of virtual reality simulation in robotic surgery training: a review.

Authors:  Justin D Bric; Derek C Lumbard; Matthew J Frelich; Jon C Gould
Journal:  Surg Endosc       Date:  2015-08-25       Impact factor: 4.584

2.  Virtual reality robotic surgery simulation curriculum to teach robotic suturing: a randomized controlled trial.

Authors:  Daniel J Kiely; Walter H Gotlieb; Susie Lau; Xing Zeng; Vanessa Samouelian; Agnihotram V Ramanakumar; Helena Zakrzewski; Sonya Brin; Shannon A Fraser; Pira Korsieporn; Laura Drudi; Joshua Z Press
Journal:  J Robot Surg       Date:  2015-05-16

3.  Evaluation of different time schedules in training with the Da Vinci simulator.

Authors:  C Güldner; A Orth; P Dworschak; I Diogo; M Mandapathil; A Teymoortash; U Walliczek-Dworschak
Journal:  Surg Endosc       Date:  2017-03-09       Impact factor: 4.584

4.  Baseline urologic surgical skills among medical students: Differentiating trainees.

Authors:  Vishaal Gupta; Andrea G Lantz; Tarek Alzharani; Kirsten Foell; Jason Y Lee
Journal:  Can Urol Assoc J       Date:  2014-07       Impact factor: 1.862

5.  The effect of different training exercises on the performance outcome on the da Vinci Skills Simulator.

Authors:  U Walliczek-Dworschak; M Schmitt; P Dworschak; I Diogo; A Ecke; M Mandapathil; A Teymoortash; C Güldner
Journal:  Surg Endosc       Date:  2016-09-20       Impact factor: 4.584

6.  General surgery training and robotics: Are residents improving their skills?

Authors:  Brendan M Finnerty; Cheguevara Afaneh; Anna Aronova; Thomas J Fahey; Rasa Zarnegar
Journal:  Surg Endosc       Date:  2015-05-28       Impact factor: 4.584

7.  Sensor-based indicators of performance changes between sessions during robotic surgery training.

Authors:  Chuhao Wu; Jackie Cha; Jay Sulek; Chandru P Sundaram; Juan Wachs; Robert W Proctor; Denny Yu
Journal:  Appl Ergon       Date:  2020-09-19       Impact factor: 3.661

8.  Robotic simulation: validation and qualitative assessment of a general surgery resident training curriculum.

Authors:  Mia S Turbati; Matthew I Goldblatt; Jon C Gould; Rana M Higgins
Journal:  Surg Endosc       Date:  2022-08-24       Impact factor: 3.453

Review 9.  Simulation-based training and assessment in urological surgery.

Authors:  Abdullatif Aydin; Nicholas Raison; Muhammad Shamim Khan; Prokar Dasgupta; Kamran Ahmed
Journal:  Nat Rev Urol       Date:  2016-08-23       Impact factor: 14.432

10.  Face and content validity of the virtual reality simulator 'ScanTrainer®'.

Authors:  Amal Alsalamah; Rudi Campo; Vasilios Tanos; Gregoris Grimbizis; Yves Van Belle; Kerenza Hood; Neil Pugh; Nazar Amso
Journal:  Gynecol Surg       Date:  2017-09-12
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