Computer Vision Syndrome: Prevalence and Associated Risk Factors Among Computer-Using Bank Workers in Pakistan

Visual, ocular surface, and extraocular diagnostic criteria for determining the prevalence of computer vision syndrome: a cross-sectional smart-survey-based study

Background

The American Optometric Association defines computer vision syndrome (CVS), also known as digital eye strain, as "a group of eye- and vision-related problems that result from prolonged computer, tablet, e-reader and cell phone use". We aimed to create a well-structured, valid, and reliable questionnaire to determine the prevalence of CVS, and to analyze the visual, ocular surface, and extraocular sequelae of CVS using a novel and smart self-assessment questionnaire.

Methods

This multicenter, observational, cross-sectional, descriptive, survey-based, online study included 6853 complete online responses of medical students from 15 universities. All participants responded to the updated, online, fourth version of the CVS questionnaire (CVS-F4), which has high validity and reliability. CVS was diagnosed according to five basic diagnostic criteria (5DC) derived from the CVS-F4. Respondents who fulfilled the 5DC were considered CVS cases. The 5DC were then converted into a novel five-question self-assessment questionnaire designated as the CVS-Smart.

Results

Of 10 000 invited medical students, 8006 responded to the CVS-F4 survey (80% response rate), while 6853 of the 8006 respondents provided complete online responses (85.6% completion rate). The overall CVS prevalence was 58.78% (n = 4028) among the study respondents; CVS prevalence was higher among women (65.87%) than among men (48.06%). Within the CVS group, the most common visual, ocular surface, and extraocular complaints were eye strain, dry eye, and neck/shoulder/back pain in 74.50% (n = 3001), 58.27% (n = 2347), and 80.52% (n = 3244) of CVS cases, respectively. Notably, 75.92% (3058/4028) of CVS cases were involved in the Mandated Computer System Use Program. Multivariate logistic regression analysis revealed that the two most statistically significant diagnostic criteria of the 5DC were ≥2 symptoms/attacks per month over the last 12 months (odds ratio [OR] = 204177.2; P <0.0001) and symptoms/attacks associated with screen use (OR = 16047.34; P <0.0001). The CVS-Smart demonstrated a Cronbach's alpha reliability coefficient of 0.860, Guttman split-half coefficient of 0.805, with perfect content and construct validity. A CVS-Smart score of 7-10 points indicated the presence of CVS.

Conclusions

The visual, ocular surface, and extraocular diagnostic criteria for CVS constituted the basic components of CVS-Smart. CVS-Smart is a novel, valid, reliable, subjective instrument for determining CVS diagnosis and prevalence and may provide a tool for rapid periodic assessment and prognostication. Individuals with positive CVS-Smart results should consider modifying their lifestyles and screen styles and seeking the help of ophthalmologists and/or optometrists. Higher institutional authorities should consider revising the Mandated Computer System Use Program to avoid the long-term consequences of CVS among university students. Further research must compare CVS-Smart with other available metrics for CVS, such as the CVS questionnaire, to determine its test-retest reliability and to justify its widespread use.

Prevalence of computer vision syndrome: A systematic review and meta-analysis

PURPOSE

This review aimed to estimate the prevalence of computer vision syndrome (CVS) in the general population and subgroups.

METHODS

A search was conducted in the following the databases: PubMed, SCOPUS, EMBASE, and Web of Science until February 13, 2023. We included studies that assessed the prevalence of CVS in any population. The Joanna Briggs Institute's critical appraisal tool was used to evaluate the methodological quality. A meta-analysis of the prevalence of CVS was done using a random-effects model, assessing the sources of heterogeneity using subgroup and meta-regression analyses.

RESULTS

A total of 103 cross-sectional studies with 66 577 participants were included. The prevalence of CVS was 69.0% (95% CI: 62.3 to 75.3; I2: 99.7%), ranging from 12.1 to 97.3% across studies. Point prevalence was higher in women than in men (71.4 vs. 61.8%), university students (76.1%), Africa (71.2%), Asia (69.9%), contact lens wearers (73.1% vs. 63.8%) in studies conducted before the COVID-19 pandemic (72.8%), and in those that did not use the CVS-Q questionnaire (75.4%). In meta-regression, using the CVS-Q scale was associated with a lower prevalence of CVS.

CONCLUSION

Seven out of ten people suffer from CVS. Preventive strategies and interventions are needed to decrease the prevalence of this condition which can affect productivity and quality of life. Future studies should standardize a definition of CVS.

Computer Vision Syndrome Among the General Population in the Eastern Region of Libya: Prevalence and Risk Factors

Aim To assess the prevalence and determine the risk factors of computer vision syndrome among the general population in the Eastern region of Libya. Methods This study used a descriptive cross-sectional design and comprised a random sample of 407 Libyan adults from Eastern Libya. Data were collected using an online-based questionnaire. Statistical analysis of all the datasets was performed using SPSS software, version 21.0 (IBM Corp., Armonk, NY). Results The mean age of the participants was 32.1 years (SD=12.8), and most participants 281 (69%) were female. As for employment status, 261 (64.1%) were students, 70 (17.2%) were non-healthcare workers, and 46 (11.3%) were healthcare workers. The majority of participants, 353 (86.7%), used a computer seven days a week, with 187 (45.9%) of those participants using a computer for over six hours daily. Over one-third of participants, 157 (38.6%), had computer vision syndrome. Being over 45 years of age, being a student, and using a computer for over six hours a day were the main factors associated with computer vision syndrome. Neck pain was the most commonly reported complaint in 235 (57.5%). Conclusion Increased use of electronic devices is leading to a higher prevalence of computer vision syndrome. Our study emphasizes the need to raise awareness regarding computer vision syndrome among the general public and medical professionals.