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. 2024 Jul 1;13(1):1-15.
doi: 10.51329/mehdiophthal1489. eCollection 2024.

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

Affiliations

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

Mohammed Iqbal et al. Med Hypothesis Discov Innov Ophthalmol. .

Abstract

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.

Keywords: CVS-F4; CVS-Smart; CVS-Smart score; asthenopia; computer; computer vision system; dry eye; eyestrain; machine intelligence; point prevalence; smartphones; visual fatigue.

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Conflict of interest statement

None.

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References

    1. American Optometric Association. ‘Computer vision syndrome’. 2024. [Accessed: January 09, 2024]. Available at: https://www.aoa.org/patients-and-public/caring-for-your-vision/protectin....
    1. Iqbal M, Said O, Ibrahim O, Soliman A. Visual Sequelae of Computer Vision Syndrome: A Cross-Sectional Case-Control Study. J Ophthalmol. 2021;2021:6630286. - PMC - PubMed
    1. Alamri A, Amer KA, Aldosari AA, Althubait BMS, Alqahtani MS, Al Mudawi AAM, et al. Computer vision syndrome: Symptoms, risk factors, and practices. J Family Med Prim Care. 2022;11(9):5110–5115. - PMC - PubMed
    1. Cantó-Sancho N, Ronda E, Cabrero-García J, Casati S, Carta A, Porru S, et al. Rasch-Validated Italian Scale for Diagnosing Digital Eye Strain: The Computer Vision Syndrome Questionnaire IT©. Int J Environ Res Public Health. 2022;19(8):4506. - PMC - PubMed
    1. González-Pérez M, Susi R, Antona B, Barrio A, González E. The Computer-Vision Symptom Scale (CVSS17): development and initial validation. Invest Ophthalmol Vis Sci. 2014;55(7):4504–11. - PubMed

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