A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study

• Published in: Journal of medical Internet research Vol. 24; no. 7; p. e27310
• Main Authors: Deiner, Michael S, Kaur, Gurbani, McLeod, Stephen D, Schallhorn, Julie M, Chodosh, James, Hwang, Daniel H, Lietman, Thomas M, Porco, Travis C
• Format: Journal Article
• Language: English
• Published: Canada Gunther Eysenbach MD MPH, Associate Professor 05.07.2022; JMIR Publications
• Subjects: Application programming interface; Cardiovascular disease; Conjunctivitis; Coronaviruses; COVID-19; Epidemics; Eye diseases; Eye Diseases - diagnosis; Health informatics; Health surveillance; Humans; Influenza; Infodemiology; Information sources; Internet; Original Paper; Pandemics; Patients; Public health; Search Engine; Search engines; Social networks; Time series; Timing; Trends; Underserved populations; United States > US; vision; diurnal eye conditions; web-based search; hebdomadal; infodemiology; information seeking; eye conditions; online search; conjunctivitis; dry eye; pink eye
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/27310

Studies suggest diurnal patterns of occurrence of some eye conditions. Leveraging new information sources such as web-based search data to learn more about such patterns could improve the understanding of patients' eye-related conditions and well-being, better inform timing of clinical and remote eye care, and improve precision when targeting web-based public health campaigns toward underserved populations. To investigate our hypothesis that the public is likely to consistently search about different ophthalmologic conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to ophthalmologic conditions such as conjunctivitis. We assessed whether search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other. We designed a study to analyze and compare hourly search data for eye-related and control search terms, using time series regression models with trend and periodicity terms to remove outliers and then estimate diurnal effects. We planned a Google Trends setting, extracting data from 10 US states for the entire year of 2018. The exposure was internet search, and the participants were populations who searched through Google's search engine using our chosen study terms. Our main outcome measures included cyclical hourly and day-of-week web-based search patterns. For statistical analyses, we considered P<.001 to be statistically significant. Distinct diurnal (P<.001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented those reported from prior clinical studies. Of the eye-related terms, "pink eye" showed the largest diurnal amplitude-to-mean ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. By contrast, "dry eyes" had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening-to-morning period and peaking in early morning. The frequency of web-based searches for various eye conditions can show cyclic patterns according to time of the day or week. Further studies to understand the reasons for these variations may help supplement the current clinical understanding of ophthalmologic symptom presentation and improve the timeliness of patient messaging and care interventions.