Digital eye strain:Prevalence, measurement and amelioration

Abstract

Digital device usage has increased substantially in recent years across all age groups, so that extensive daily use for both social and professional purposes is now normal. Digital eye strain (DES), also known as computer vision syndrome, encompasses a range of ocular and visual symptoms, and estimates suggest its prevalence may be 50% or more among computer users. Symptoms fall into two main categories: those linked to accommodative or binocular vision stress, and external symptoms linked to dry eye. Although symptoms are typically transient, they may be frequent and persistent, and have an economic impact when vocational computer users are affected. DES may be identified and measured using one of several available questionnaires, or objective evaluations of parameters such as critical flicker–fusion frequency, blink rate and completeness, accommodative function and pupil characteristics may be used to provide indices of visual fatigue. Correlations between objective and subjective measures are not always apparent. A range of management approaches exist for DES including correction of refractive error and/or presbyopia, management of dry eye, incorporating regular screen breaks and consideration of vergence and accommodative problems. Recently, several authors have explored the putative role of blue light-filtering spectacle lenses on treating DES, with mixed results. Given the high prevalence of DES and near-universal use of digital devices, it is essential that eye care practitioners are able to provide advice and management options based on quality research evidence.

Publication DOI: https://doi.org/10.1136/bmjophth-2018-000146
Divisions: College of Health & Life Sciences > School of Optometry > Optometry
College of Health & Life Sciences > School of Optometry > Optometry & Vision Science Research Group (OVSRG)
College of Health & Life Sciences
College of Health & Life Sciences > School of Optometry > Vision, Hearing and Language
Additional Information: © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Publication ISSN: 2397-3269
Last Modified: 19 Mar 2024 08:14
Date Deposited: 09 May 2018 07:40
PURE Output Type: Article
Published Date: 2018-04-16
Accepted Date: 2018-03-27
Authors: Sheppard, Amy L (ORCID Profile 0000-0003-0035-8267)
Wolffsohn, James S. (ORCID Profile 0000-0003-4673-8927)

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