Extended screen time and dry eye in youth.

PURPOSE: Extended screen time amongst youth is a pervasive global phenomenon, with wide-ranging implications for health and quality of life. Dry eye disease is increasingly reported as emerging in paediatric populations and is associated with modified blinking behaviour during extended screen time. This study sought to evaluate spontaneous blink rates, dry eye symptomology and screen use habits of young extended screen time users. METHODS: Attendees of a gaming convention in Auckland, NZ, completed a self-directed iPad-based survey on personal screen use habits and ocular symptoms using the 5-item Dry Eye Questionnaire (DEQ-5) and the Symptom Assessment in Dry Eye (SANDE) questionnaire. Blink rate was covertly and concomitantly recorded using the front-facing iPad camera and quantified by automated software. A validated, self-assessment blink test was administered as a proxy for tear film stability measurements. RESULTS: A total of 456 respondents (mean age ± SD: 24 ± 10 years, range: 13 - 75, 38% female) reported an average weekly screen time of 43.7 ± 24.4 h. DEQ-5 and SANDE scores were 10 ± 3 and 34 ± 19; 90% of respondents qualified as symptomatic for dry eye disease (DEQ-5 ≥ 6). Blink test results suggested a tear film stability < 10 s in 24% of cases. Poorer symptomology correlated with increased screen use, elevated blink rates and reduced proxy tear film stability (r = 0.15 to 0.22, all p < 0.01). CONCLUSION: Extended screen time in a young population was associated with blinking behaviour and symptomology consistent with patients with dry eye. Implementing routine clinical screening, educational interventions, and developing official guidance on safe screen use may help prevent an accelerated degradation of ocular surface health and quality of life in young people.

Demographic and lifestyle risk factors of dry eye disease subtypes: A cross-sectional study.

PURPOSE: To evaluate demographic and lifestyle factors associated with aqueous deficient and evaporative dry eye disease. METHODS: A total of 1125 general public visitors (707 females, mean ± SD age, 33 ± 21, range 5-90 years) at the Royal Society Summer Science Exhibition were recruited in a cross-sectional study. A demographic and lifestyle factor questionnaire was administered, and dry eye symptomology (DEQ-5 score), ocular surface characteristics (conjunctival hyperaemia, and infrared meibography), and tear film parameters (tear meniscus height, non-invasive breakup time, and lipid layer grade) were evaluated for the left eye of each participant within a single session. The diagnostic criteria for dry eye disease subtypes were adapted from the rapid non-invasive dry eye assessment algorithm. RESULTS: Overall, 428 (38%) participants fulfilled the diagnostic criteria for dry eye disease, 161 (14%) with aqueous deficient dry eye disease, and 339 (30%) with evaporative dry eye disease. Multivariate logistic regression demonstrated that advancing age, female sex, reduced sleep duration, higher psychological stress, and poorer self-perceived health status were independently associated with aqueous deficient dry eye disease (all p < 0.05). Significant risk factors for evaporative dry eye disease included advancing age, East and South Asian ethnicity, contact lens wear, increased digital device screen exposure, higher psychological stress, and poorer self-perceived health status (all p < 0.05). CONCLUSIONS: Both subtypes of dry eye disease were associated with several unique and shared demographic and lifestyle factors. The findings of this study could inform future research design investigating the utility of targeted screening and risk factor modification for the prevention and management of dry eye disease.

Mobile app Aston contrast sensitivity test.

BACKGROUND: Contrast detection is an important aspect of the assessment of visual function; however, clinical tests evaluate limited spatial frequencies and contrasts. This study validates the accuracy and inter-test repeatability of a swept-frequency near and distance mobile app Aston contrast sensitivity test, which overcomes this limitation compared to traditional charts. METHOD: Twenty subjects wearing their full refractive correction underwent contrast sensitivity testing on the new near application (near app), distance app, CSV-1000 and Pelli-Robson charts with full correction and with vision degraded by 0.8 and 0.2 Bangerter degradation foils. In addition repeated measures using the 0.8 occluding foil were taken. RESULTS: The mobile apps (near more than distance, p = 0.005) recorded a higher contrast sensitivity than printed tests (p < 0.001); however, all charts showed a reduction in measured contrast sensitivity with degradation (p < 0.001) and a similar decrease with increasing spatial frequency (interaction > 0.05). Although the coefficient of repeatability was lowest for the Pelli-Robson charts (0.14 log units), the mobile app charts measured more spatial frequencies, took less time and were more repeatable (near: 0.26 to 0.37 log units; distance: 0.34 to 0.39 log units) than the CSV-1000 (0.30 to 0.93 log units). The duration to complete the CSV-1000 was 124 ± 37 seconds, Pelli-Robson 78 ± 27 seconds, near app 53 ± 15 seconds and distance app 107 ± 36 seconds. CONCLUSIONS: While there were differences between charts in contrast levels measured, the new Aston near and distance apps are valid, repeatable and time-efficient method of assessing contrast sensitivity at multiple spatial frequencies.

Tablet App halometer for the assessment of dysphotopsia.

PURPOSE: To assess the validity and repeatability of the Aston Halometer. SETTING: University clinic, United Kingdom. DESIGN: Prospective, repeated-measures experimental study. METHODS: The halometer comprises a bright light-emitting-diode (LED) glare source in the center of an iPad4. Letters subtending 0.21° (~0.3 logMAR) were moved centrifugally from the LED in 0.05 degree steps in 8 orientations separated by 45 degrees for each of 4 contrast levels (1000, 500, 100, and 25 Weber contrast units [Cw]) in random order. Bangerter occlusion foils were inserted in front of the right eye to simulate monocular glare conditions in 20 subjects (mean age 27.7 ± 3.1 years). Subjects were positioned 2 meters from the screen in a dark room with the iPad controlled from an iPhone via Bluetooth operated by the researcher. The C-Quant straylight meter was also used with each of the foils to measure the level of straylight over the retina. Halometry and straylight repeatability was assessed at a second visit. RESULTS: Halo size increased with the different occlusion foils and target contrasts (F = 29.564, P < .001) as expected and in a pattern similar to straylight measures (F = 80.655, P < 0.001). Lower contrast letters showed better sensitivity but larger glare-obscured areas, resulting in ceiling effects caused by the screen's field-of-view, with 500 Cw being the best compromise. Intraobserver and interobserver repeatability of the Aston Halometer was good (500Cw: 0.84 to 0.93 and 0.53 to 0.73) and similar to the straylight meter. CONCLUSION: The halometer provides a sensitive, repeatable way of quantifying a patient-recognized form of disability glare in multiple orientations to add objectivity to subjectively reported discomfort glare.

Mobile app reading speed test.

AIM: To validate the accuracy and repeatability of a mobile app reading speed test compared with the traditional paper version. METHOD: Twenty-one subjects wearing their full refractive correction glasses read 14 sentences of decreasing print size between 1.0 and -0.1 logMAR, each consisting of 14 words (Radner reading speed test) at 40 cm with a paper-based chart and twice on iPad charts. Time duration was recorded with a stop watch for the paper chart and on the App itself for the mobile chart allowing critical print size (CPS) and optimal reading speed (ORS) to be derived objectively. RESULTS: The ORS was higher for the mobile app charts (194±29 wpm; 195±25 wpm) compared with the paper chart (166±20 wpm; F=57.000, p<0.001). The CPS was lower for the mobile app charts (0.17±0.20 logMAR; 0.18±0.17 logMAR) compared with the paper chart (0.25±0.17 logMAR; F=5.406, p=0.009). The mobile app test had a mean difference repeatability of 0.30±22.5 wpm, r=0.917 for ORS, and a CPS of 0.0±0.2 logMAR, r=0.769. CONCLUSIONS: Repeatability of the app reading speed test is as good (ORS) or better (CPS) than previous studies on the paper test. While the results are not interchangeable with paper-based charts, mobile app tablet-based tests of reading speed are reliable and rapid to perform, with the potential to capture functional visual ability in research studies and clinical practice.

Exploring the optimum step size for defocus curves.

PURPOSE: To evaluate the effect of reducing the number of visual acuity measurements made in a defocus curve on the quality of data quantified. SETTING: Midland Eye, Solihull, United Kingdom. DESIGN: Evaluation of a technique. METHODS: Defocus curves were constructed by measuring visual acuity on a distance logMAR letter chart, randomizing the test letters between lens presentations. The lens powers evaluated ranged between +1.50 diopters (D) and -5.00 D in 0.50 D steps, which were also presented in a randomized order. Defocus curves were measured binocularly with the Tecnis diffractive, Rezoom refractive, Lentis rotationally asymmetric segmented (+3.00 D addition [add]), and Finevision trifocal multifocal intraocular lenses (IOLs) implanted bilaterally, and also for the diffractive IOL and refractive or rotationally asymmetric segmented (+3.00 D and +1.50 D adds) multifocal IOLs implanted contralaterally. Relative and absolute range of clear-focus metrics and area metrics were calculated for curves fitted using 0.50 D, 1.00 D, and 1.50 D steps and a near add-specific profile (ie, distance, half the near add, and the full near-add powers). RESULTS: A significant difference in simulated results was found in at least 1 of the relative or absolute range of clear-focus or area metrics for each of the multifocal designs examined when the defocus-curve step size was increased (P<.05). CONCLUSION: Faster methods of capturing defocus curves from multifocal IOL designs appear to distort the metric results and are therefore not valid. FINANCIAL DISCLOSURE: No author has a financial or proprietary interest in any material or method mentioned.