Perceptual-motor vision training approaches for the prevention of computer vision syndrome in college students: A narrative review.

Computer Vision Syndrome (CVS), also referred to as Digital Eye Strain (DES), is a common condition among college students and other digital-device users and is associated with prolonged near work, reduced blinking, and sustained visual attention. Conventional preventive strategies, including ergonomic optimization and scheduled visual breaks, primarily address environmental risk factors but do not directly target the perceptual-motor mechanisms underlying visual fatigue and oculomotor inefficiency. Perceptual-Motor Vision Training (PMVT) is an emerging complementary, non-pharmacological approach designed to enhance accommodation, vergence, oculomotor control, visuomotor integration, and visual information processing through structured visuomotor exercises. This narrative review synthesizes evidence from vision science, motor learning, and applied performance research to evaluate the potential role of PMVT in preventing or mitigating CVS-related visual fatigue in college students. Available evidence suggests that PMVT may improve selected visual and visuomotor functions. However, because most supporting studies involve athletic, pediatric, clinical, or non-CVS populations, its effectiveness for preventing CVS in healthy college students remains unproven. PMVT should therefore be considered an investigational complementary approach alongside ergonomic and behavioral strategies. Despite promising theoretical and preliminary empirical support, current evidence is limited by heterogeneous outcome measures, a scarcity of randomized controlled trials in non-athletic populations, and insufficient specification of training dosage and protocols. Future interdisciplinary research is required to establish standardized perceptual-motor metrics, determine dose-response relationships, and evaluate the clinical effectiveness and feasibility of PMVT as a low-cost complementary intervention for reducing digital task-related visual fatigue and improving visual performance in student populations.