Authors: María del Mar Seguí, Julio Cabrero-García, Ana Crespo...

OBJECTIVES

To design and validate a questionnaire to measure visual symptoms related to exposure to computers in the workplace.

STUDY DESIGN AND SETTING

Our computer vision syndrome questionnaire (CVS-Q) was based on a literature review and validated through discussion with experts and performance of a pretest, pilot test, and retest. Content validity was evaluated by occupational health, optometry, and ophthalmology experts. Rasch analysis was used in the psychometric evaluation of the questionnaire. Criterion validity was determined by calculating the sensitivity and specificity, receiver operator characteristic curve, and cutoff point. Test-retest repeatability was tested using the intraclass correlation coefficient (ICC) and concordance by Cohen's kappa (κ).

RESULTS

The CVS-Q was developed with wide consensus among experts and was well accepted by the target group. It assesses the frequency and intensity of 16 symptoms using a single rating scale (symptom severity) that fits the Rasch rating scale model well. The questionnaire has sensitivity and specificity over 70% and achieved good test-retest repeatability both for the scores obtained [ICC = 0.802; 95% confidence interval (CI): 0.673, 0.884] and CVS classification (κ = 0.612; 95% CI: 0.384, 0.839).

CONCLUSION

The CVS-Q has acceptable psychometric properties, making it a valid and reliable tool to control the visual health of computer workers, and can potentially be used in clinical trials and outcome research.

Topics: Asthenopia; Computer Terminals; Confidence Intervals; Environmental Monitoring; Health Surveys; Humans; Occupational Diseases; Pilot Projects; ROC Curve; Sensitivity and Specificity; Surveys and Questionnaires; Syndrome

PubMed: 25744132
DOI: 10.1016/j.jclinepi.2015.01.015

Review

Authors: Sukanya Jaiswal, Lisa Asper, Jennifer Long...

Smartphone and tablet use in Australia and worldwide is reaching saturation levels and associated visual and ocular discomfort such as headaches, eyestrain, dry eyes and sore eyes are widespread. This review synthesises the available literature and considers these symptoms in the context of a binocular vision and/or ocular surface aetiology. Eye discomfort with smartphones and tablets is discussed alongside similar symptoms reported with desktop computer use. Handheld devices differ from computers in viewing position and distance, screen size and luminance, and patterns of use. Accommodation is altered with handheld device use, with increased lag and decreased amplitude. Smartphone and tablet use results in reduced fusional convergence and possibly a receded near point of convergence. This is similar to what happens with computer use. Findings related to blink rate with smartphone and tablet use are contradictory, perhaps due to the influence of task difficulty, and there is limited evidence related to blink amplitude. Reduced blink rate and amplitude are consistently reported with computer use. Use of handheld digital devices, like computers, may adversely impact tear stability. There is insufficient evidence to support the impact of handheld devices on tear volume, although this is reduced with computer use. The available literature does not conclusively link eye and visual discomfort symptoms reported with handheld digital devices, with changes in binocular vision, blinking or ocular surface. However, there is a gap in our understanding of symptoms which occur with smartphone and tablet use in the context of how these devices are used. In addition, studies are required in high users such as teenagers, and in patients with dry eye or accommodative/binocular vision anomalies, all of whom may have a higher risk of symptoms. A better understanding of symptom aetiology can guide clinical advice to minimise adverse impacts on visual and ocular surface health and discomfort.

Topics: Asthenopia; Computers; Computers, Handheld; Dry Eye Syndromes; Humans; Smartphone; Vision Disorders; Vision, Binocular

PubMed: 30663136
DOI: 10.1111/cxo.12851

Review

Authors: Chantal Coles-Brennan, Anna Sulley, Graeme Young...

Digital eye strain, an emerging public health issue, is a condition characterised by visual disturbance and/or ocular discomfort related to the use of digital devices and resulting from a range of stresses on the ocular environment. This review aims to provide an overview of the extensive literature on digital eye strain research with particular reference to the clinical management of symptoms. As many as 90 per cent of digital device users experience symptoms of digital eye strain. Many studies suggest that the following factors are associated with digital eye strain: uncorrected refractive error (including presbyopia), accommodative and vergence anomalies, altered blinking pattern (reduced rate and incomplete blinking), excessive exposure to intense light, closer working distance, and smaller font size. Since a symptom may be caused by one or more factors, a holistic approach should be adopted. The following management strategies have been suggested: (i) appropriate correction of refractive error, including astigmatism and presbyopia; (ii) management of vergence anomalies, with the aim of inducing or leaving a small amount of heterophoria (~1.5 Exo); (iii) blinking exercise/training to maintain normal blinking pattern; (iv) use of lubricating eye drops (artificial tears) to help alleviate dry eye-related symptoms; (v) contact lenses with enhanced comfort, particularly at end-of-day and in challenging environments; (vi) prescription of colour filters in all vision correction options, especially blue light-absorbing filters; and (vii) management of accommodative anomalies. Prevention is the main strategy for management of digital eye strain, which involves: (i) ensuring an ergonomic work environment and practice (through patient education and the implementation of ergonomic workplace policies); and (ii) visual examination and eye care to treat visual disorders. Special consideration is needed for people at a high risk of digital eye strain, such as computer workers and contact lens wearers.

Topics: Asthenopia; Computer Systems; Disease Management; Humans; Vision Disorders

PubMed: 29797453
DOI: 10.1111/cxo.12798

Meta-Analysis

Authors: Jian Wang, Mei Li, Daqiao Zhu...

BACKGROUND

Smartphone overuse has been cited as a potentially modifiable risk factor that can result in visual impairment. However, reported associations between smartphone overuse and visual impairment have been inconsistent.

OBJECTIVE

The aim of this systematic review was to determine the association between smartphone overuse and visual impairment, including myopia, blurred vision, and poor vision, in children and young adults.

METHODS

We conducted a systematic search in the Cochrane Library, PubMed, EMBASE, Web of Science Core Collection, and ScienceDirect databases since the beginning of the databases up to June 2020. Fourteen eligible studies (10 cross-sectional studies and 4 controlled trials) were identified, which included a total of 27,110 subjects with a mean age ranging from 9.5 to 26.0 years. We used a random-effects model for meta-analysis of the 10 cross-sectional studies (26,962 subjects) and a fixed-effects model for meta-analysis of the 4 controlled trials (148 subjects) to combine odds ratios (ORs) and effect sizes (ES). The I statistic was used to assess heterogeneity.

RESULTS

A pooled OR of 1.05 (95% CI 0.98-1.13, P=.16) was obtained from the cross-sectional studies, suggesting that smartphone overuse is not significantly associated with myopia, poor vision, or blurred vision; however, these visual impairments together were more apparent in children (OR 1.06, 95% CI 0.99-1.14, P=.09) than in young adults (OR 0.91, 95% CI 0.57-1.46,P=.71). For the 4 controlled trials, the smartphone overuse groups showed worse visual function scores compared with the reduced-use groups. The pooled ES was 0.76 (95% CI 0.53-0.99), which was statistically significant (P<.001).

CONCLUSIONS

Longer smartphone use may increase the likelihood of ocular symptoms, including myopia, asthenopia, and ocular surface disease, especially in children. Thus, regulating use time and restricting the prolonged use of smartphones may prevent ocular and visual symptoms. Further research on the patterns of use, with longer follow up on the longitudinal associations, will help to inform detailed guidelines and recommendations for smartphone use in children and young adults.

Topics: Adolescent; Adult; Cross-Sectional Studies; Humans; Smartphone; Young Adult

PubMed: 33289673
DOI: 10.2196/21923

Meta-Analysis Review

Authors: Sumeer Singh, Myra B McGuinness, Andrew J Anderson...

TOPIC

To evaluate the efficacy and safety of interventions for treating eye strain related to computer use relative to placebo or no treatment.

CLINICAL RELEVANCE

Computer use is pervasive and often associated with eye strain, referred to as computer vision syndrome (CVS). Currently, no clinical guidelines exist to help practitioners provide evidence-based advice about CVS treatments, many of which are marketed directly to patients. This systematic review and meta-analysis was designed to help inform best practice for eye care providers.

METHODS

Eligible randomized controlled trials (RCTs) were identified in Ovid MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, and trial registries, searched from inception through November 23, 2021. Eligible studies were appraised for risk of bias and were synthesized. The certainty of the body of evidence was judged using the Grading of Recommendations, Assessment, Development, and Evaluation system. Standardized mean differences (SMDs) were used when differently scaled measures were combined.

RESULTS

Forty-five RCTs, involving 4497 participants, were included. Multifocal lenses did not improve visual fatigue scores compared with single-vision lenses (3 RCTs; SMD, 0.11; 95% confidence interval [CI], -0.14 to 0.37; P = 0.38). Visual fatigue symptoms were not reduced by blue-blocking spectacles (3 RCTs), with evidence judged of low certainty. Relative to placebo, oral berry extract supplementation did not improve visual fatigue (7 RCTs; SMD, -0.27; 95% CI, -0.70 to 0.16; P = 0.22) or dry eye symptoms (4 RCTs; SMD, -0.10; 95% CI, -0.54 to 0.33; P = 0.65). Likewise, berry extract supplementation had no significant effects on critical flicker-fusion frequency (CFF) or accommodative amplitude. Oral omega-3 supplementation for 45 days to 3 months improved dry eye symptoms (2 RCTs; mean difference [MD], -3.36; 95% CI, -3.63 to -3.10 on an 18 unit scale; P < 0.00001) relative to placebo. Oral carotenoid supplementation improved CFF (2 RCTs; MD, 1.55 Hz; 95% CI, 0.42 to 2.67 Hz; P = 0.007) relative to placebo, although the clinical significance of this finding is unclear.

DISCUSSION

We did not identify high-certainty evidence supporting the use of any of the therapies analyzed. Low-certainty evidence suggested that oral omega-3 supplementation reduces dry eye symptoms in symptomatic computer users.

Topics: Asthenopia; Carotenoids; Computers; Dry Eye Syndromes; Eyeglasses; Humans

PubMed: 35597519
DOI: 10.1016/j.ophtha.2022.05.009

Review

Authors: Sumeer Singh, Peter R Keller, Ljoudmila Busija...

BACKGROUND

'Blue-light filtering', or 'blue-light blocking', spectacle lenses filter ultraviolet radiation and varying portions of short-wavelength visible light from reaching the eye. Various blue-light filtering lenses are commercially available. Some claims exist that they can improve visual performance with digital device use, provide retinal protection, and promote sleep quality. We investigated clinical trial evidence for these suggested effects, and considered any potential adverse effects.

OBJECTIVES

To assess the effects of blue-light filtering lenses compared with non-blue-light filtering lenses, for improving visual performance, providing macular protection, and improving sleep quality in adults.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL; containing the Cochrane Eyes and Vision Trials Register; 2022, Issue 3); Ovid MEDLINE; Ovid Embase; LILACS; the ISRCTN registry; ClinicalTrials.gov and WHO ICTRP, with no date or language restrictions. We last searched the electronic databases on 22 March 2022.

SELECTION CRITERIA

We included randomised controlled trials (RCTs), involving adult participants, where blue-light filtering spectacle lenses were compared with non-blue-light filtering spectacle lenses.

DATA COLLECTION AND ANALYSIS

Primary outcomes were the change in visual fatigue score and critical flicker-fusion frequency (CFF), as continuous outcomes, between baseline and one month of follow-up. Secondary outcomes included best-corrected visual acuity (BCVA), contrast sensitivity, discomfort glare, proportion of eyes with a pathological macular finding, colour discrimination, proportion of participants with reduced daytime alertness, serum melatonin levels, subjective sleep quality, and patient satisfaction with their visual performance. We evaluated findings related to ocular and systemic adverse effects. We followed standard Cochrane methods for data extraction and assessed risk of bias using the Cochrane Risk of Bias 1 (RoB 1) tool. We used GRADE to assess the certainty of the evidence for each outcome.

MAIN RESULTS

We included 17 RCTs, with sample sizes ranging from five to 156 participants, and intervention follow-up periods from less than one day to five weeks. About half of included trials used a parallel-arm design; the rest adopted a cross-over design. A variety of participant characteristics was represented across the studies, ranging from healthy adults to individuals with mental health and sleep disorders. None of the studies had a low risk of bias in all seven Cochrane RoB 1 domains. We judged 65% of studies to have a high risk of bias due to outcome assessors not being masked (detection bias) and 59% to be at high risk of bias of performance bias as participants and personnel were not masked. Thirty-five per cent of studies were pre-registered on a trial registry. We did not perform meta-analyses for any of the outcome measures, due to lack of available quantitative data, heterogenous study populations, and differences in intervention follow-up periods. There may be no difference in subjective visual fatigue scores with blue-light filtering lenses compared to non-blue-light filtering lenses, at less than one week of follow-up (low-certainty evidence). One RCT reported no difference between intervention arms (mean difference (MD) 9.76 units (indicating worse symptoms), 95% confidence interval (CI) -33.95 to 53.47; 120 participants). Further, two studies (46 participants, combined) that measured visual fatigue scores reported no significant difference between intervention arms. There may be little to no difference in CFF with blue-light filtering lenses compared to non-blue-light filtering lenses, measured at less than one day of follow-up (low-certainty evidence). One study reported no significant difference between intervention arms (MD - 1.13 Hz lower (indicating poorer performance), 95% CI - 3.00 to 0.74; 120 participants). Another study reported a less negative change in CFF (indicating less visual fatigue) with high- compared to low-blue-light filtering and no blue-light filtering lenses. Compared to non-blue-light filtering lenses, there is probably little or no effect with blue-light filtering lenses on visual performance (BCVA) (MD 0.00 logMAR units, 95% CI -0.02 to 0.02; 1 study, 156 participants; moderate-certainty evidence), and unknown effects on daytime alertness (2 RCTs, 42 participants; very low-certainty evidence); uncertainty in these effects was due to lack of available data and the small number of studies reporting these outcomes. We do not know if blue-light filtering spectacle lenses are equivalent or superior to non-blue-light filtering spectacle lenses with respect to sleep quality (very low-certainty evidence). Inconsistent findings were evident across six RCTs (148 participants); three studies reported a significant improvement in sleep scores with blue-light filtering lenses compared to non-blue-light filtering lenses, and the other three studies reported no significant difference between intervention arms. We noted differences in the populations across studies and a lack of quantitative data. Device-related adverse effects were not consistently reported (9 RCTs, 333 participants; low-certainty evidence). Nine studies reported on adverse events related to study interventions; three studies described the occurrence of such events. Reported adverse events related to blue-light filtering lenses were infrequent, but included increased depressive symptoms, headache, discomfort wearing the glasses, and lower mood. Adverse events associated with non-blue-light filtering lenses were occasional hyperthymia, and discomfort wearing the spectacles. We were unable to determine whether blue-light filtering lenses affect contrast sensitivity, colour discrimination, discomfort glare, macular health, serum melatonin levels or overall patient visual satisfaction, compared to non-blue-light filtering lenses, as none of the studies evaluated these outcomes.

AUTHORS' CONCLUSIONS

This systematic review found that blue-light filtering spectacle lenses may not attenuate symptoms of eye strain with computer use, over a short-term follow-up period, compared to non-blue-light filtering lenses. Further, this review found no clinically meaningful difference in changes to CFF with blue-light filtering lenses compared to non-blue-light filtering lenses. Based on the current best available evidence, there is probably little or no effect of blue-light filtering lenses on BCVA compared with non-blue-light filtering lenses. Potential effects on sleep quality were also indeterminate, with included trials reporting mixed outcomes among heterogeneous study populations. There was no evidence from RCT publications relating to the outcomes of contrast sensitivity, colour discrimination, discomfort glare, macular health, serum melatonin levels, or overall patient visual satisfaction. Future high-quality randomised trials are required to define more clearly the effects of blue-light filtering lenses on visual performance, macular health and sleep, in adult populations.

Topics: Adult; Humans; Eyeglasses; Asthenopia; Melatonin; Sleep; Light; Drug-Related Side Effects and Adverse Reactions

PubMed: 37593770
DOI: 10.1002/14651858.CD013244.pub2

Authors: James S Wolffsohn, Gareth Lingham, Laura E Downie...

Eye strain when performing tasks reliant on a digital environment can cause discomfort, affecting productivity and quality of life. Digital eye strain (the preferred terminology) was defined as "the development or exacerbation of recurrent ocular symptoms and/or signs related specifically to digital device screen viewing". Digital eye strain prevalence of up to 97% has been reported, due to no previously agreed definition/diagnostic criteria and limitations of current questionnaires which fail to differentiate such symptoms from those arising from non-digital tasks. Objective signs such as blink rate or critical flicker frequency changes are not 'diagnostic' of digital eye strain nor validated as sensitive. The mechanisms attributed to ocular surface disease exacerbation are mainly reduced blink rate and completeness, partial/uncorrected refractive error and/or underlying binocular vision anomalies, together with the cognitive demand of the task and differences in position, size, brightness and glare compared to an equivalent non-digital task. In general, interventions are not well established; patients experiencing digital eye strain should be provided with a full refractive correction for the appropriate working distances. Improving blinking, optimizing the work environment and encouraging regular breaks may help. Based on current, best evidence, blue-light blocking interventions do not appear to be an effective management strategy. More and larger clinical trials are needed to assess artificial tear effectiveness for relieving digital eye strain, particularly comparing different constituents; a systematic review within the report identified use of secretagogues and warm compress/humidity goggles/ambient humidifiers as promising strategies, along with nutritional supplementation (such as omega-3 fatty acid supplementation and berry extracts).

Topics: Humans; Quality of Life; Eye Diseases; Asthenopia; Tears; Life Style; Dry Eye Syndromes

PubMed: 37062428
DOI: 10.1016/j.jtos.2023.04.004

Review

Authors: Irina Andreea Pavel, Camelia Margareta Bogdanici, Vlad Constantin Donica...

Digital device usage has increased significantly in last decade among all age groups, both for educational and recreational purposes. Computer vision syndrome (CVS), also known as digital eye strain (DES), represents a range of ocular, musculoskeletal, and behavioral conditions caused by prolonged use of devices with digital screens. This paper reviews the principal environmental, ocular, and musculoskeletal causes for this condition. Due to the high prevalence of DES and frequent usage of digital devices, it is important that eye care practitioners be able to provide advice and management options based on quality research evidence.

Topics: Humans; Asthenopia; Computers; Syndrome; Risk Factors; Prevalence

PubMed: 36837613
DOI: 10.3390/medicina59020412