ABSTRACT
Purpose: The present work style and lifestyle have increased the digital device use. Therefore, an increase in digital eyestrain is to be expected. We undertook a survey during coronavirus disease 2019 (COVID-19) pandemic to investigate the practice of 20/20/20 rule and its association with digital device use and asthenopic symptoms. While this rule is commonly advised, little is known about its validity. Methods: An online survey form was disseminated through social media and emails. The questions for eye-related symptoms were similar to the convergence insufficiency symptom survey (CISS). Participants with age ≥5 years were included, with parents completing the survey for children (≤16 years). Results: A total of 432 participants (mean ± standard deviation [SD]: 26.06 ± 13.92 years) were enrolled, of which 125 responses were for children. The 20/20/20 rule was practiced only by 34% of the participants either regularly (n = 38) or occasionally (n = 109). Those who had complaints of burning sensation and headache tended to practice this rule. Among adult participants, more females (47%) practiced this rule when compared to males (23%). Also, adult females significantly (P = 0.04) had more symptoms score when compared to males. In children, no such gender difference was found. Conclusion: Only one-third of participants practice the 20/20/20 rule at least occasionally. More number of adult females being symptomatic and practicing in greater number could be due to higher prevalence of dry eye condition in females. While the symptom of burning sensation could be related to dry eye, that of headache could be related to refractive error or binocular vision dysfunctions.
Subject(s)
Asthenopia , COVID-19 , Dry Eye Syndromes , Male , Adult , Female , Child , Humans , Child, Preschool , Asthenopia/diagnosis , Asthenopia/epidemiology , Asthenopia/etiology , COVID-19/epidemiology , Vision Disorders/diagnosis , Headache , Dry Eye Syndromes/diagnosis , Dry Eye Syndromes/epidemiologyABSTRACT
This study evaluates the progression of visual fatigue induced by visual display terminal (VDT) using automatically detected blink features. A total of 23 subjects were recruited to participate in a VDT task, during which they were required to watch a 120-min video on a laptop and answer a questionnaire every 30 min. Face video recordings were captured by a camera. The blinking and incomplete blinking images were recognized by automatic detection of the parameters of the eyes. Then, the blink features were extracted including blink number (BN), mean blink interval (Mean_BI), mean blink duration (Mean_BD), group blink number (GBN), mean group blink interval (Mean_GBI), incomplete blink number (IBN), and mean incomplete blink interval (Mean_IBI). The results showed that BN and GBN increased significantly, and that Mean_BI and Mean_GBI decreased significantly over time. Mean_BD and Mean_IBI increased and IBN decreased significantly only in the last 30 min. The blink features automatically detected in this study can be used to evaluate the progression of visual fatigue.