Literature DB >> 26681572

Effect of training frequency on the learning curve on the da Vinci Skills Simulator.

Ute Walliczek1, Arne Förtsch1, Philipp Dworschak2, Afshin Teymoortash1, Magis Mandapathil1, Jochen Werner1, Christian Güldner1.   

Abstract

BACKGROUND: The purpose of this study was to evaluate the effect of training on the performance outcome with the da Vinci Skills Simulator.
METHODS: Forty novices were enrolled in a prospective training curriculum. Participants were separated into 2 groups. Group 1 performed 4 training sessions and group 2 had 2 training sessions over a 4-week period. Five exercises were performed 3 times consecutively. On the last training day, a new exercise was added.
RESULTS: A significant skills gain from the first to the final practice day in overall performance, time to complete, and economy of motion was seen for both groups. Group 1 had a significantly better outcome in overall performance, time to complete, and economy of motion in all exercises. There was no significant difference found regarding the new exercise in group 1 versus group 2 in nearly all parameters.
CONCLUSION: Longer time distances between training sessions are assumed to play a secondary role, whereas total repetition frequency is crucial for improvement of technical performance.
© 2015 Wiley Periodicals, Inc. Head Neck 38: E1762-E1769, 2016. © 2015 Wiley Periodicals, Inc.

Entities:  

Keywords:  da Vinci Skills Simulator; otorhinolaryngology; robotic surgery; robotic surgery education; training frequency; transoral robotic surgery

Mesh:

Year:  2015        PMID: 26681572     DOI: 10.1002/hed.24312

Source DB:  PubMed          Journal:  Head Neck        ISSN: 1043-3074            Impact factor:   3.147


  9 in total

1.  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

Review 2.  Da Vinci© Skills Simulator™: is an early selection of talented console surgeons possible?

Authors:  Mark Meier; Kevin Horton; Hubert John
Journal:  J Robot Surg       Date:  2016-06-22

3.  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

4.  Transoral robotic submandibular sialadenectomy: how and when.

Authors:  Pasquale Capaccio; Filippo Montevecchi; Giuseppe Meccariello; Giovanni Cammaroto; Jeffery Scott Magnuson; Stefano Pelucchi; Lorenzo Bresciani; Claudio Vicini
Journal:  Gland Surg       Date:  2020-04

Review 5.  What happens while learning robotic lobectomy for lung cancer?

Authors:  Mehmet Oğuzhan Özyurtkan; Erkan Kaba; Alper Toker
Journal:  J Vis Surg       Date:  2017-03-10

6.  Evaluation of a 3D-Printed Transoral Robotic Surgery Simulator Utilizing Artificial Tissue.

Authors:  Alexander T Murr; Catherine J Lumley; Richard H Feins; Trevor G Hackman
Journal:  Laryngoscope       Date:  2021-12-09       Impact factor: 2.970

7.  Comparative Effectiveness of Teaching Obstetrics and Gynaecological Procedural Skills on Patients versus Models: A randomized trial.

Authors:  Shereen Zulfiqar Bhutta; Haleema Yasmin
Journal:  Pak J Med Sci       Date:  2018 Jul-Aug       Impact factor: 1.088

Review 8.  Systematic review of learning curves in robot-assisted surgery.

Authors:  N A Soomro; D A Hashimoto; A J Porteous; C J A Ridley; W J Marsh; R Ditto; S Roy
Journal:  BJS Open       Date:  2019-11-29

9.  The impact of tiredness on virtual reality robotic surgical skills.

Authors:  Alin Adrian Cumpanas; Razvan Bardan; Ovidiu Ferician; Silviu Constantin Latcu; Octavian Fulger Lazar; Ciprian Duta
Journal:  Wideochir Inne Tech Maloinwazyjne       Date:  2020-02-24       Impact factor: 1.195

  9 in total

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