From the Ocular Surface to Neurophysiology: An Integrative Review of Digital Eye Strain

从眼表到神经生理学:数码眼疲劳的综合综述

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Abstract

Digital eye strain is a cross-system condition that arises from interactions between visual physiology and digital displays. As the use of screens has grown in work, education, and everyday life, researchers have sought to describe this condition through symptom questionnaires (CVS‑Q, CVSS17, DESQ), measurements of the ocular surface and blinking, tests of accommodation and vergence, and, in related visual fatigue studies, neurophysiological methods such as electromyography and electroencephalography (EEG). Nevertheless, these methods have usually examined individual mechanisms separately. Interventions-ranging from lubricating the ocular surface and filtering blue light to ergonomic changes, task‑specific refractive correction, and scheduled micro‑breaks-have seldom been guided by a unified mechanistic framework. This review compiles evidence from 128 studies to identify six mechanistic domains relevant for clinical assessment. These include ocular surface and blink dynamics, accommodation and vergence, musculoskeletal load, device-related optical stress, cognitive load, and neural markers. A systematic search of PubMed/MEDLINE, Embase, Scopus, and Web of Science was carried out through September 30th, 2025, in accordance with PRISMA guidelines. Eligible studies included randomized trials, controlled interventions, cohort studies, and laboratory experiments, with methodological quality evaluated using the Mixed Methods Appraisal Tool. Results across pediatric, adolescent, working‑age, and presbyopic groups indicate that cognitive load reduces blinking and destabilizes accommodation. Binocular incongruence links visual effort with trapezius activation, and EEG markers can precede subjective fatigue. Interventions aligned with these mechanisms-such as ocular surface care, accommodative/vergence correction, ergonomic optimization, and micro‑break scheduling-are supported across all domains. The review proposes a mechanism‑based triage model to assist clinicians in prioritizing interventions based on the patient's exposure profile, breaking neuro‑ocular feedback loops, and preserving functional performance in individuals exposed to screens. The framework provides an actionable, mechanism‑first triage checklist for optometric practice.

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