Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology
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 s...
Ausführliche Beschreibung
Autor*in: |
Lucy V. Cobbs [verfasserIn] Hytham Al-Hindi [verfasserIn] Cherie Fathy [verfasserIn] Raziyeh Mahmoudzadeh [verfasserIn] Tara Uhler [verfasserIn] David Xu [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2023 |
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Übergeordnetes Werk: |
In: Journal of Academic Ophthalmology - Thieme Medical Publishers, Inc., 2020, 15(2023), 01, Seite e93-e98 |
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Übergeordnetes Werk: |
volume:15 ; year:2023 ; number:01 ; pages:e93-e98 |
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DOI / URN: |
10.1055/s-0043-1768025 |
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Katalog-ID: |
DOAJ089326040 |
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520 | |a 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. | ||
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10.1055/s-0043-1768025 doi (DE-627)DOAJ089326040 (DE-599)DOAJ8636000b32ef453783514046405d4a11 DE-627 ger DE-627 rakwb eng RE1-994 Lucy V. Cobbs verfasserin aut Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. vitreoretinal education online medical education tools medical education technology visual learning Ophthalmology Hytham Al-Hindi verfasserin aut Cherie Fathy verfasserin aut Raziyeh Mahmoudzadeh verfasserin aut Tara Uhler verfasserin aut David Xu verfasserin aut In Journal of Academic Ophthalmology Thieme Medical Publishers, Inc., 2020 15(2023), 01, Seite e93-e98 (DE-627)890800456 (DE-600)2897840-7 24754757 nnns volume:15 year:2023 number:01 pages:e93-e98 https://doi.org/10.1055/s-0043-1768025 kostenfrei https://doaj.org/article/8636000b32ef453783514046405d4a11 kostenfrei http://www.thieme-connect.de/DOI/DOI?10.1055/s-0043-1768025 kostenfrei https://doaj.org/toc/2475-4757 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2023 01 e93-e98 |
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10.1055/s-0043-1768025 doi (DE-627)DOAJ089326040 (DE-599)DOAJ8636000b32ef453783514046405d4a11 DE-627 ger DE-627 rakwb eng RE1-994 Lucy V. Cobbs verfasserin aut Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. vitreoretinal education online medical education tools medical education technology visual learning Ophthalmology Hytham Al-Hindi verfasserin aut Cherie Fathy verfasserin aut Raziyeh Mahmoudzadeh verfasserin aut Tara Uhler verfasserin aut David Xu verfasserin aut In Journal of Academic Ophthalmology Thieme Medical Publishers, Inc., 2020 15(2023), 01, Seite e93-e98 (DE-627)890800456 (DE-600)2897840-7 24754757 nnns volume:15 year:2023 number:01 pages:e93-e98 https://doi.org/10.1055/s-0043-1768025 kostenfrei https://doaj.org/article/8636000b32ef453783514046405d4a11 kostenfrei http://www.thieme-connect.de/DOI/DOI?10.1055/s-0043-1768025 kostenfrei https://doaj.org/toc/2475-4757 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2023 01 e93-e98 |
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10.1055/s-0043-1768025 doi (DE-627)DOAJ089326040 (DE-599)DOAJ8636000b32ef453783514046405d4a11 DE-627 ger DE-627 rakwb eng RE1-994 Lucy V. Cobbs verfasserin aut Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. vitreoretinal education online medical education tools medical education technology visual learning Ophthalmology Hytham Al-Hindi verfasserin aut Cherie Fathy verfasserin aut Raziyeh Mahmoudzadeh verfasserin aut Tara Uhler verfasserin aut David Xu verfasserin aut In Journal of Academic Ophthalmology Thieme Medical Publishers, Inc., 2020 15(2023), 01, Seite e93-e98 (DE-627)890800456 (DE-600)2897840-7 24754757 nnns volume:15 year:2023 number:01 pages:e93-e98 https://doi.org/10.1055/s-0043-1768025 kostenfrei https://doaj.org/article/8636000b32ef453783514046405d4a11 kostenfrei http://www.thieme-connect.de/DOI/DOI?10.1055/s-0043-1768025 kostenfrei https://doaj.org/toc/2475-4757 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2023 01 e93-e98 |
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10.1055/s-0043-1768025 doi (DE-627)DOAJ089326040 (DE-599)DOAJ8636000b32ef453783514046405d4a11 DE-627 ger DE-627 rakwb eng RE1-994 Lucy V. Cobbs verfasserin aut Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. vitreoretinal education online medical education tools medical education technology visual learning Ophthalmology Hytham Al-Hindi verfasserin aut Cherie Fathy verfasserin aut Raziyeh Mahmoudzadeh verfasserin aut Tara Uhler verfasserin aut David Xu verfasserin aut In Journal of Academic Ophthalmology Thieme Medical Publishers, Inc., 2020 15(2023), 01, Seite e93-e98 (DE-627)890800456 (DE-600)2897840-7 24754757 nnns volume:15 year:2023 number:01 pages:e93-e98 https://doi.org/10.1055/s-0043-1768025 kostenfrei https://doaj.org/article/8636000b32ef453783514046405d4a11 kostenfrei http://www.thieme-connect.de/DOI/DOI?10.1055/s-0043-1768025 kostenfrei https://doaj.org/toc/2475-4757 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2023 01 e93-e98 |
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10.1055/s-0043-1768025 doi (DE-627)DOAJ089326040 (DE-599)DOAJ8636000b32ef453783514046405d4a11 DE-627 ger DE-627 rakwb eng RE1-994 Lucy V. Cobbs verfasserin aut Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. vitreoretinal education online medical education tools medical education technology visual learning Ophthalmology Hytham Al-Hindi verfasserin aut Cherie Fathy verfasserin aut Raziyeh Mahmoudzadeh verfasserin aut Tara Uhler verfasserin aut David Xu verfasserin aut In Journal of Academic Ophthalmology Thieme Medical Publishers, Inc., 2020 15(2023), 01, Seite e93-e98 (DE-627)890800456 (DE-600)2897840-7 24754757 nnns volume:15 year:2023 number:01 pages:e93-e98 https://doi.org/10.1055/s-0043-1768025 kostenfrei https://doaj.org/article/8636000b32ef453783514046405d4a11 kostenfrei http://www.thieme-connect.de/DOI/DOI?10.1055/s-0043-1768025 kostenfrei https://doaj.org/toc/2475-4757 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2023 01 e93-e98 |
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Cobbs</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose Ophthalmology residency training heavily relies on visual and pattern recognition-based learning. 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Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology |
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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. |
abstractGer |
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. |
abstract_unstemmed |
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. |
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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. 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