Literature DB >> 25481802

An effective repetitive training schedule to achieve skill proficiency using a novel robotic virtual reality simulator.

Sung Gu Kang1, Byung Ju Ryu2, Kyung Sook Yang3, Young Hwii Ko4, Seok Cho1, Seok Ho Kang1, Vipul R Patel5, Jun Cheon6.   

Abstract

PURPOSE: A robotic virtual reality simulator (Mimic dV-Trainer) can be a useful training method for the da Vinci surgical system. Herein, we investigate several repetitive training schedules and determine which is the most effective.
METHODS: A total of 30 medical students were enrolled and were divided into 3 groups according to the training schedule. Group 1 performed the task 1 hour daily for 4 consecutive days, group II performed the task on once per week for 1 hour for 4 consecutive weeks, and group III performed the task for 4 consecutive hours in 1 day. The effects of training were investigated by analyzing the number of repetitions and the time required to complete the "Tube 2" simulation task when the learning curve plateau was reached. The point at which participants reached a stable score was evaluated using the cumulative sum control graph.
RESULTS: The average time to complete the task at the learning curve plateau was 150.3 seconds in group I, 171.9 seconds in group II, and 188.5 seconds in group III. The number of task repetitions required to reach the learning curve plateau was 45 repetitions in group I, 36 repetitions in group II, and 39 repetitions in group III. Therefore, there was continuous improvement in the time required to perform the task after 40 repetitions in group I only. There was a significant correlation between improvement in each trial interval and attempt, and the correlation coefficient (0.924) in group I was higher than that in group II (0.899) and group III (0.838).
CONCLUSION: Daily 1-hour practice sessions performed for 4 consecutive days resulted in the best final score, continuous score improvement, and effective training while minimizing fatigue. This repetition schedule can be used for effectively training novices in future.
Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Medical Knowledge; Patient Care; Practice-Based Learning and Improvement; education; learning curve; robotics; simulator

Mesh:

Year:  2014        PMID: 25481802     DOI: 10.1016/j.jsurg.2014.06.023

Source DB:  PubMed          Journal:  J Surg Educ        ISSN: 1878-7452            Impact factor:   2.891


  9 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

Review 2.  Simulation-based training in robot-assisted surgery: current evidence of value and potential trends for the future.

Authors:  Michael I Hanzly; Tareq Al-Tartir; Syed Johar Raza; Atif Khan; Mohammad Manan Durrani; Thomas Fiorica; Phillip Ginsberg; James L Mohler; Boris Kuvshinoff; Khurshid A Guru
Journal:  Curr Urol Rep       Date:  2015-06       Impact factor: 3.092

3.  Can teenage novel users perform as well as General Surgery residents upon initial exposure to a robotic surgical system simulator?

Authors:  A Mehta; S Patel; W Robison; T Senkowski; J Allen; E Shaw; C Senkowski
Journal:  J Robot Surg       Date:  2017-06-05

Review 4.  Learning Curves for Robotic Surgery: a Review of the Recent Literature.

Authors:  Giorgio Mazzon; Ashwin Sridhar; Gerald Busuttil; James Thompson; Senthil Nathan; Tim Briggs; John Kelly; Greg Shaw
Journal:  Curr Urol Rep       Date:  2017-09-23       Impact factor: 3.092

5.  Concurrent and predictive validation of robotic simulator Tube 3 module.

Authors:  Jae Yoon Kim; Seung Bin Kim; Jong Hyun Pyun; Hyung Keun Kim; Seok Cho; Jeong Gu Lee; Je Jong Kim; Jun Cheon; Seok Ho Kang; Sung Gu Kang
Journal:  Korean J Urol       Date:  2015-11-03

6.  Current and Future Trends in Life Sciences Training: Questionnaire Study.

Authors:  William Magagna; Nicole Wang; Kyle Peck
Journal:  JMIR Med Educ       Date:  2020-04-24

7.  Spacing Repetitions Over Long Timescales: A Review and a Reconsolidation Explanation.

Authors:  Christopher D Smith; Damian Scarf
Journal:  Front Psychol       Date:  2017-06-20

8.  Learning curve patterns generated by a training method for laparoscopic small bowel anastomosis.

Authors:  Jose Carlos Manuel-Palazuelos; María Riaño-Molleda; José Luis Ruiz-Gómez; Jose Ignacio Martín-Parra; Carlos Redondo-Figuero; José María Maestre
Journal:  Adv Simul (Lond)       Date:  2016-05-25

9.  Virtual Reality in Medical Students' Education: Scoping Review.

Authors:  Haowen Jiang; Sunitha Vimalesvaran; Jeremy King Wang; Kee Boon Lim; Sreenivasulu Reddy Mogali; Lorainne Tudor Car
Journal:  JMIR Med Educ       Date:  2022-02-02
  9 in total

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