Assessing the Risk Factors For Diagnosed Symptomatic Dry Eye Using a Smartphone App: Cross-sectional Study

Background: Dry eye (DE) is a chronic inflammatory disease of the ocular surface of the eye that affects millions of people throughout the world. Smartphone use as an effective health care tool has grown exponentially. The "Dry eye or not?" app was created to evaluate the prevalence of sym...

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Main Authors: Ngamjit Kasetsuwan, Olan Suwan-Apichon, Kaevalin Lekhanont, Varintorn Chuckpaiwong, Usanee Reinprayoon, Somporn Chantra, Vilavun Puangsricharern, Lalida Pariyakanok, Pinnita Prabhasawat, Nattaporn Tesavibul, Winai Chaidaroon, Napaporn Tananuvat, Chakree Hirunpat, Nauljira Prakairungthong, Wiwan Sansanayudh, Chareenun Chirapapaisan, Pakornkit Phrueksaudomchai
Other Authors: Ramathibodi Hospital
Format: Article
Published: 2022
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/74450
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Institution: Mahidol University
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Summary:Background: Dry eye (DE) is a chronic inflammatory disease of the ocular surface of the eye that affects millions of people throughout the world. Smartphone use as an effective health care tool has grown exponentially. The "Dry eye or not?" app was created to evaluate the prevalence of symptomatic DE, screen for its occurrence, and provide feedback to users with symptomatic DE throughout Thailand. Objective: The purpose of this study was to compare the prevalence of symptomatic dry eye (DE), blink rate, maximum blink interval (MBI), and best spectacle-corrected visual acuity (BSCVA) between people with and without symptomatic DE and to identify risk factors for symptomatic DE in Thailand. Methods: This cross-sectional study sourced data from the "Dry eye or not?" smartphone app between November 2019 and July 2020. This app collected demographic data, Ocular Surface Disease Index (OSDI) score, blink rate, MBI, BSCVA, and visual display terminal (VDT) use data. The criterion for symptomatic DE was OSDI score ≥13. Results: The prevalence of symptomatic DE among individuals using this smartphone app in Thailand was 85.8% (8131/9482), with the Northeastern region of Thailand having the highest prevalence, followed by the Northern region. Worse BSCVA (median 0.20, IQR 0.40; P=.02), increased blink rate (median 18, IQR 16; P<.001), reduced MBI (median 8.90, IQR 10.80; P<.001), female sex (adjusted OR 1.83; 95% CI 1.59-2.09; P<.001), more than 6 hours of VDT use (adjusted OR 1.59; 95% CI 1.15-2.19; P=.004), and lower than bachelor's degree (adjusted OR 1.30; 95% CI 1.03-1.64; P=.02) were significantly associated with symptomatic DE. An age over 50 years (adjusted OR 0.77; 95% CI 0.60-0.99) was significantly less associated with symptomatic DE (P=.04). Conclusions: This smartphone DE app showed that the prevalence of symptomatic DE in Thailand was 85.8%. Signs and risk factors could be also evaluated with this smartphone DE app. Screening for DE by this app may allow for the development of strategic plans for health care systems in Thailand.