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CC BY-NC-ND 4.0 · Journal of Academic Ophthalmology 2023; 15(01): e93-e98
DOI: 10.1055/s-0043-1768025
Research Article

Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology

Authors

  • Lucy V. Cobbs 

    1   Retina Service, Wills Eye Hospital, Mid Atlantic Retina, Thomas Jefferson University, Philadelphia, Pennsylvania
    2   Department of Ophthalmology, Wills Eye Hospital, Thomas Jefferson University, Philadelphia, Pennsylvania

  • Hytham Al-Hindi

    3   College of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas

  • Cherie Fathy

    1   Retina Service, Wills Eye Hospital, Mid Atlantic Retina, Thomas Jefferson University, Philadelphia, Pennsylvania
    2   Department of Ophthalmology, Wills Eye Hospital, Thomas Jefferson University, Philadelphia, Pennsylvania
    4   Cornea Service, Wilmer Eye Institute, Johns Hopkins University, Baltimore, Maryland

  • Raziyeh Mahmoudzadeh

    1   Retina Service, Wills Eye Hospital, Mid Atlantic Retina, Thomas Jefferson University, Philadelphia, Pennsylvania

  • Tara Uhler

    2   Department of Ophthalmology, Wills Eye Hospital, Thomas Jefferson University, Philadelphia, Pennsylvania

  • David Xu

    1   Retina Service, Wills Eye Hospital, Mid Atlantic Retina, Thomas Jefferson University, Philadelphia, Pennsylvania
    2   Department of Ophthalmology, Wills Eye Hospital, Thomas Jefferson University, Philadelphia, Pennsylvania
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Abstract

Purpose Ophthalmology residency training heavily relies on visual and pattern recognition-based learning. In parallel with traditional reference texts, online internet search via Google Image Search (GIS) is commonly used and offers an accessible fund of reference images for ophthalmology trainees seeking rapid exposure to images of retinal pathology. However, the accuracy and quality of this tool within this context is unknown. We aim to evaluate the accuracy and quality of GIS images of selected retinal pathologies.

Methods A cross-sectional study was performed of GIS of 15 common and 15 rare retinal diseases drawn from the American Academy of Ophthalmology residency textbook series. A total of 300 evaluable image results were assessed for accuracy of images and image source accountability in consultation with a vitreoretinal surgeon.

Results A total of 377 images were reviewed with 77 excluded prior to final analysis. A total of 288 (96%) search results accurately portrayed the retinal disease being searched, whereas 12 (4%) were of an erroneous diagnosis. More images of common retinal diseases were from patient education Web sites than were images of rare diseases (p < 0.01). Significantly more images of rare retinal diseases were found in peer-reviewed sources (p = 0.01).

Conclusions GIS search results yielded a modest level of accuracy for the purposes of ophthalmic education. Despite the ease and rapidity of accessing multimodal retinal imaging examples, this tool may best be suited as a supplementary resource for learning among residents due to limited accuracy, lack of sufficient supporting information, and the source Web site's focus on patient education.

Keywords

vitreoretinal education - online medical education tools - medical education technology - visual learning


Publication History

Received: 14 August 2022

Accepted: 01 March 2023

Article published online:
12 April 2023

© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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