June 2023
Volume 64, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2023
Expert vs. Novice Review of Ophthalmic Data: An Oculography Study of Optic Neuropathies
Author Affiliations & Notes
  • Atharv Chintamani Patwardhan
    Neuro-Ophthalmology, Stanford University School of Medicine, Stanford, California, United States
  • Andrew Raphael Berneshawi
    Neuro-Ophthalmology, Stanford University School of Medicine, Stanford, California, United States
  • Miaomiao Yu
    Neuro-Ophthalmology, Stanford University School of Medicine, Stanford, California, United States
  • Yaping Joyce Liao
    Neuro-Ophthalmology, Stanford University School of Medicine, Stanford, California, United States
  • Footnotes
    Commercial Relationships   Atharv Patwardhan None; Andrew Berneshawi None; Miaomiao Yu None; Yaping Liao None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 4109. doi:
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      Atharv Chintamani Patwardhan, Andrew Raphael Berneshawi, Miaomiao Yu, Yaping Joyce Liao; Expert vs. Novice Review of Ophthalmic Data: An Oculography Study of Optic Neuropathies. Invest. Ophthalmol. Vis. Sci. 2023;64(8):4109.

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

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Abstract

Purpose : Infrared oculography (IO) uses eye-tracking to characterize gaze patterns via saccades and fixations. IO can characterize subjective phenomena, such as the difference in approach to tasks between novices and experts. Ophthalmology, a field underrepresented in medical school, could benefit from IO to determine where experts and novices differ most, guiding education efforts. To investigate this, we tracked the eyes of novices and experts while they reviewed ophthalmic clinical reports.

Methods : We collected 1200-Hz infrared oculography data while 7 neuro-ophthalmologists and 11 medical students and residents reviewed 12 neuro-ophthalmic cases. Each case file contained 4 slides: Fundus Photograph (FP), Humphrey Visual Field (HVF), Ocular Coherence Tomography (OCT), and 2 multiple-choice diagnosis questions. Diagrams on each slide were outlined as areas of interest (AOI). Novices viewed a 20-minute neuro-ophthalmology training video after case 6.

Results : There was a significant interaction of expertise, training, and AOIs in the total time spent within each AOI (F (10, 80) = 1.95, p = .050). Visualizations indicated that experts were more selective when viewing AOIs, with a larger disparity in time spent across different AOIs, while novices spent more time within AOIs overall. The training video only reduced the time (seconds) novices looked at the patient history AOI on the FP slide, (pre-training, novice: 7624 (2239), expert: 4730 (450); post-training, novice: 5781 (1553), expert: 5255 (1686), t (14.38) = -2.28, p = .038). Novice answer choices were not significantly different from chance, before or after training, while expert answers were cohesive in their diagnoses.

Conclusions : IO was able to demonstrate that a short traditional training had minimal effects on novice performance, both in terms of gaze and quiz answers. IO was also able to characterize and distinguish expert and novice gaze patterns. These findings suggest that IO characterization can be used to inform educational tools and monitor novice progress.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.

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