TY  - JOUR
AU  - Kasetsuwan, Ngamjit
AU  - Suwan-Apichon, Olan
AU  - Lekhanont, Kaevalin
AU  - Chuckpaiwong, Varintorn
AU  - Reinprayoon, Usanee
AU  - Chantra, Somporn
AU  - Puangsricharern, Vilavun
AU  - Pariyakanok, Lalida
AU  - Prabhasawat, Pinnita
AU  - Tesavibul, Nattaporn
AU  - Chaidaroon, Winai
AU  - Tananuvat, Napaporn
AU  - Hirunpat, Chakree
AU  - Prakairungthong, Nauljira
AU  - Sansanayudh, Wiwan
AU  - Chirapapaisan, Chareenun
AU  - Phrueksaudomchai, Pakornkit
PY  - 2022
DA  - 2022/6/22
TI  - Assessing the Risk Factors For Diagnosed Symptomatic Dry Eye Using a Smartphone App: Cross-sectional Study
JO  - JMIR Mhealth Uhealth
SP  - e31011
VL  - 10
IS  - 6
KW  - blink rate
KW  - dry eye
KW  - smartphone application
KW  - maximum blink interval
KW  - prevalence
KW  - mHealth
KW  - epidemiology
KW  - screening
KW  - risk factors
KW  - symptoms
KW  - ophthalmology
KW  - vision
AB  - 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. 
SN  - 2291-5222
UR  - https://mhealth.jmir.org/2022/6/e31011
UR  - https://doi.org/10.2196/31011
UR  - http://www.ncbi.nlm.nih.gov/pubmed/35731569
DO  - 10.2196/31011
ID  - info:doi/10.2196/31011
ER  -