September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Effectiveness of Ophthalmic Surgical Simulation Training vs. Paper Based Manual Training on physiologic tremor and speed in dominant and non-dominant hands
Author Affiliations & Notes
  • Yonwook Justin Kim
    Veterans Affairs Boston Healthcare System, Jamaica Plains, Massachusetts, United States
    Department of Ophthalmology, Boston University School of Medicine, Boston, Massachusetts, United States
  • Abhishek R Payal
    Veterans Affairs Boston Healthcare System, Jamaica Plains, Massachusetts, United States
    Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts, United States
  • Luis A Gonzalez
    Veterans Affairs Boston Healthcare System, Jamaica Plains, Massachusetts, United States
  • Mary K Daly
    Veterans Affairs Boston Healthcare System, Jamaica Plains, Massachusetts, United States
    Department of Ophthalmology, Boston University School of Medicine, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Yonwook Kim, None; Abhishek Payal, None; Luis Gonzalez, None; Mary Daly, None
  • Footnotes
    Support  This material is the result of work supported with resources and the use of facilities at the Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA.
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 940. doi:
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    • Get Citation

      Yonwook Justin Kim, Abhishek R Payal, Luis A Gonzalez, Mary K Daly; Effectiveness of Ophthalmic Surgical Simulation Training vs. Paper Based Manual Training on physiologic tremor and speed in dominant and non-dominant hands. Invest. Ophthalmol. Vis. Sci. 2016;57(12):940.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Ophthalmic surgeries are bimanual but currently there is little data on targeted training for both dominant and non-dominant hands. We hypothesized that EyeSi simulator training and paper based manual training would improve speed, reduce tremor, and decrease the performance gap between dominant and non-dominant hands.

Methods : In this prospective crossover study, nineteen subjects (18 medical students and one resident) completed training sessions of simulator anti-tremor modules and paper based tremor spirography with their dominant and non-dominant hands. Data on baseline performance, a series of training tasks and an evaluation test at the end of each session were recorded. We compared the overall simulator scores, number of paper errors, average tremor value (as calculated by the simulator), and time to complete baseline and final tasks, using analysis of variance and nonparametric tests.

Results : In the paper module, subjects significantly decreased the overall time in both dominant and non-dominant hands (P <.001) from baseline to final tasks, while the number of errors did not change. In the simulator module, participants achieved a higher score (P<.001) in less time (P <.001) in both dominant and non-dominant hands after training. The improvement in scores was comparable (P=.79) between hands. The simulator tremor values did not differ significantly at baseline or final tasks for both hands (P=.37 for baseline, P=.83 for final). Before the training, non-dominant hands took longer than dominant hands to complete tasks on both paper (P=.003) and simulator (P=.04) modules. After the training, non-dominant speed still lagged behind that of the the dominant hand on the paper module (P=.005) but improved to the level of dominant hands on the simulator (P=.07). Overall the participants found the simulator helpful in improving the speed of their non-dominant hand.

Conclusions : Structured repetitive simulator training and paper-based training can improve speed in both dominant and non-dominant hands, but does not appear to reduce tremor. Simulator training may be helpful in decreasing the performance gap between dominant and non-dominant hands.

Disclaimer: The opinions expressed are those of the authors and not necessarily those of the Department of Veterans Affairs or the United States Government.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

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