@misc{10481/108351,
year = {2025},
month = {11},
url = {https://hdl.handle.net/10481/108351},
abstract = {Purpose: The objective of this study was to investigate differences in tear inflammatory molecules after digital and paper-based reading, examine the influence of cognitive load and explore their relationship with digital eye strain (DES) symptoms.
Methods: Twenty-four young adults completed four 30-minute reading tasks, each varying in cognitive demands (high vs. low) and reading media (digital vs. paper). After each task, unstimulated tear samples were collected and analyzed using multiplex bead assays to quantify the concentrations of 12 tear molecules. Participants also completed a questionnaire to assess visual symptomatology.
Results: Reading from a digital screen significantly increased tear concentrations of IL-1α (P = 0.02), IL-6 (P = 0.03), IL-8 (P = 0.004), TGF-α (P = 0.02), and TNF-β (P = 0.01) compared to reading printed text. High cognitive load was also associated with elevated IL-8 (P = 0.002) and TNF-β (P = 0.02) levels. Participants reported higher visual discomfort when using digital screens, with higher cognitive demand exacerbating these symptoms.
Correlation analyses revealed moderate positive relationships between the changes induced by the display type on IL-1α and DES symptoms (P = 0.02), and between IL and 6 (P = 0.02), TGF-α (P = 0.04) and TNF-β (P = 0.05) with cognitive load-induced discomfort. A subgroup analysis based on dry eye symptomatology revealed that individuals with fewer symptoms exhibited higher cytokine concentrations for IL-1α (P = 0.05) and TGF-α (P = 0.02).
Conclusions: Tear biomarkers could serve as objective tools for evaluating DES, offering a deeper understanding of the physiological mechanisms involved in the condition.},
publisher = {Elsevier},
keywords = {Computer vision syndrome},
keywords = {Visual discomfort},
keywords = {Dry eye},
title = {Tear molecule concentrations as potential biomarkers of digital eye strain},
doi = {10.1016/j.clae.2025.102572},
author = {Redondo Cabrera, Beatriz and Lara-Vazquez, Paula M. and Vera Vílchez, Jesús and Rosenfield, Mark},
}