An, VVG, Mirza, Y, Mazomenos, E orcid.org/0000-0003-0357-5996 et al. (3 more authors) (2018) Arthroscopic simulation using a knee model can be used to train speed and gaze strategies in knee arthroscopy. The Knee, 25 (6). pp. 1214-1221. ISSN 0968-0160
Abstract
Purpose
This study aimed to determine the effect of a simulation course on gaze fixation strategies of participants performing arthroscopy.
Methods
Participants (n = 16) were recruited from two one-day simulation-based knee arthroscopy courses, and were asked to undergo a task before and after the course, which involved identifying a series of arthroscopic landmarks. The gaze fixation of the participants was recorded with a wearable eye-tracking system. The time taken to complete the task and proportion of time participants spent with their gaze fixated on the arthroscopic stack, the knee model, and away from the stack or knee model were recorded.
Results
Participants demonstrated a statistically decreased completion time in their second attempt compared to the first attempt (P = 0.001). In their second attempt, they also demonstrated improved gaze fixation strategies, with a significantly increased amount (P = 0.008) and proportion of time (P = 0.003) spent fixated on the screen vs. knee model.
Conclusion
Simulation improved arthroscopic skills in orthopaedic surgeons, specifically by improving their gaze control strategies and decreasing the amount of time taken to identify and mark landmarks in an arthroscopic task.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2018, Elsevier B.V. All rights reserved. This is an author produced version of an article published in The Knee. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Arthroscopy; Simulation training; Surgical education |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Mar 2020 14:57 |
Last Modified: | 05 Mar 2020 14:57 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.knee.2018.05.019 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:158070 |
Download
Filename: Mazomenos_ARTHROSIM%20Submission_Manuscript_Final%20Knee%20R1.pdf
Licence: CC-BY-NC-ND 4.0