ArticleJMIR mHealth and uHealth2022
Assessing the Risk Factors For Diagnosed Symptomatic Dry Eye Using a Smartphone App: Cross-sectional Study.
Article in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Comparison of ocular surface assessment outcomes between healthy controls and patients with obstructive sleep apnea-hypopnea syndrome: a meta-analysis of the literature.Frontiers in physiology · 2023Pooled it
- A scoping review of integrated blink analysis technologies for ocular surface diseases.Eye (London, England) · 2026Review
- BlinkNet-Q: A Deep Learning-Based Software for Real-Time Blink Rate Quantification and Incomplete-Blink Pattern Recognition.Translational vision science & technology · 2026Article
- Article
- A Narrative Review on the Diagnosis of Dry Eye Disease: Insights from the Italian Dry Eye Consensus (IDEC) Group.Ophthalmology and therapy · 2026Review
- Prevalence of dry eye disease symptoms and impact on quality-of-life among hospital staff during the COVID-19 pandemic.Scientific reports · 2025Article
- A smartphone-based blink training application for alleviating dry eye signs and symptoms.NPJ digital medicine · 2025Article
- Smartphone App-Based and Paper-Based Patient-Reported Outcomes Using a Disease-Specific Questionnaire for Dry Eye Disease: Randomized Crossover Equivalence Study.Journal of medical Internet research · 2023Article
- Clinical Utility of Smartphone Applications in Ophthalmology: A Systematic Review.Ophthalmology scienceReview
Corrections and comments
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Authors and funding
17 authors at 8 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDry 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.
objectiveThe 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.
methodsThis 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.
resultsThe 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).
conclusionsThis 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.
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