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Periodic Trends in Internet Searches for Ocular Symptoms in the US

Periodic Trends in Internet Searches for Ocular Symptoms in the US Purpose To identify periodic trends in internet searches for ocular symptoms and to determine the seasonal peaks and troughs. Methods This cross-sectional study examined publicly available Google Trends data from the United States (01/01/2015 to 12/31/2019). A list of common ocular symptoms was compiled from the American Academy of Ophthalmology Eye Health website and Wills Eye Manual. Ocular symptoms were stratified into categories involving vision change, eye pain, or eye redness. The search volume over time for each term was modeled using periodic regression functions and the goodness-of-fit was reported. Fisher’s exact tests were used to compare the characteristics of periodic vs. non-periodic query terms. Results Seasonal trends were demonstrated by 45% (48/106) of the ocular symptoms included in this investigation. Search terms with best fit to the periodic model included stye (r2 = 0.89), pink eye (r2 = 0.82), dry eye (r2 = 0.76), blurry vision (r2 = 0.72), and swollen eye (r2 = 0.71). Periodic search terms were more likely to involve eye redness (21% vs. 11%, p = .014) and less likely to involve vision change (11% vs. 36%; p < .001). Periodic queries involving eye redness most often peaked in the spring and those involving eye pain peaked in the summer. Conclusion Ocular symptom queries directly reflect seasonal trends for allergic eye disease and ocular trauma. Search query analyses can serve as accurate epidemiological tools with research and real-world clinical applications. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Ophthalmic Epidemiology Taylor & Francis

Periodic Trends in Internet Searches for Ocular Symptoms in the US

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References (16)

Publisher
Taylor & Francis
Copyright
© 2022 Taylor & Francis Group, LLC
ISSN
1744-5086
eISSN
0928-6586
DOI
10.1080/09286586.2022.2119260
Publisher site
See Article on Publisher Site

Abstract

Purpose To identify periodic trends in internet searches for ocular symptoms and to determine the seasonal peaks and troughs. Methods This cross-sectional study examined publicly available Google Trends data from the United States (01/01/2015 to 12/31/2019). A list of common ocular symptoms was compiled from the American Academy of Ophthalmology Eye Health website and Wills Eye Manual. Ocular symptoms were stratified into categories involving vision change, eye pain, or eye redness. The search volume over time for each term was modeled using periodic regression functions and the goodness-of-fit was reported. Fisher’s exact tests were used to compare the characteristics of periodic vs. non-periodic query terms. Results Seasonal trends were demonstrated by 45% (48/106) of the ocular symptoms included in this investigation. Search terms with best fit to the periodic model included stye (r2 = 0.89), pink eye (r2 = 0.82), dry eye (r2 = 0.76), blurry vision (r2 = 0.72), and swollen eye (r2 = 0.71). Periodic search terms were more likely to involve eye redness (21% vs. 11%, p = .014) and less likely to involve vision change (11% vs. 36%; p < .001). Periodic queries involving eye redness most often peaked in the spring and those involving eye pain peaked in the summer. Conclusion Ocular symptom queries directly reflect seasonal trends for allergic eye disease and ocular trauma. Search query analyses can serve as accurate epidemiological tools with research and real-world clinical applications.

Journal

Ophthalmic Epidemiology – Taylor & Francis

Published: Jul 4, 2023

Keywords: google trends; infodemiology; ocular trauma; eye infection; allergic eye disease

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