Investigating the Prevalence of Computer Vision Syndrome (CVS) Among Undergraduate Nursing Students: A Cross-Sectional Study

Digital Eye Strain: Updated Perspectives

Purpose

Digital eye strain (DES) is a growing worldwide concern because digital devices are prevalent in both our work and home lives. The purpose of this review was to summarize clinically relevant and evolving key topics related to DES.

Methods

A PubMed.gov search was conducted on or before June 8, 2024. No date restrictions were used during the primary search. The search was aimed at detecting all articles related to DES; thus, the search terms only included "digital eye strain" or "computer vision syndrome".

Results

The two most used, validated DES questionnaires are the Computer Vision Syndrome Questionnaire (CVS-Q) and Computer Vision Symptom Scale (CVSS17). The world-wide prevalence of DES ranges from 8.2% to 100% depending upon the subjects evaluated and the method used to evaluate them. The most common DES symptoms include headache, eye strain, eye redness, eye itching, tearing, photophobia, burning sensation, blurred vision, eye pain, neck and shoulder pain, and eye dryness. Ocular surface symptoms in DES are integrally tied to decreased blink frequency, which causes ocular surface desiccation, increased osmolarity, and dry eye-like symptoms. The most studied DES-specific treatments are improving subjects' environment, artificial tears, blinking exercises, and near work breaks.

Conclusion

DES is a highly prevalent condition that should be regularly screened for in clinic with a validated diagnosis instrument. While there are several treatment options, the community's treatment approach is evolving and primarily focused on treating the visual and dry eye-like symptoms associated with the condition.

Prevalence of computer vision syndrome during the COVID-19 pandemic: a systematic review and meta-analysis

BACKGROUND

Computer vision syndrome has become a significant public health problem, especially in developing countries. Therefore, this study aims to identify the prevalence of computer vision syndrome during the COVID-19 pandemic.

METHODS

A systematic review and meta-analysis of the literature was conducted using the databases PubMed, Scopus, Web of Science, and Embase up to February 22, 2023, using the search terms "Computer Vision Syndrome" and "COVID-19". Three authors independently performed study selection, quality assessment, and data extraction, and the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument was used to evaluate study quality. Heterogeneity was assessed using the statistical test I2, and the R version 4.2.3 program was used for statistical analysis.

RESULTS

A total of 192 studies were retrieved, of which 18 were included in the final meta-analysis. The total sample included 10,337 participants from 12 countries. The combined prevalence of computer vision syndrome was 74% (95% CI: 66, 81). Subgroup analysis based on country revealed a higher prevalence of computer vision syndrome in Pakistan (99%, 95% CI: 97, 100) and a lower prevalence in Turkey (48%, 95% CI: 44, 52). In addition, subgroup analysis based on study subjects showed a prevalence of 82% (95% CI: 74, 89) for computer vision syndrome in non-students and 70% (95% CI: 60, 80) among students.

CONCLUSION

According to the study, 74% of the participants experienced computer vision syndrome during the COVID-19 pandemic. Given this finding, it is essential to implement preventive and therapeutic measures to reduce the risk of developing computer vision syndrome and improve the quality of life of those affected.

TRIAL REGISTRATION

The protocol for this systematic review and meta-analysis was registered in the international registry of systematic reviews, the International Prospective Register of Systematic Reviews (PROSPERO), with registration number CRD42022345965.