The Computer-Vision Symptom Scale (CVSS17): Development and Initial Validation

Abstract

PURPOSE. To develop a questionnaire (in Spanish) to measure computer-related visual and ocular symptoms (CRVOS). METHODS. A pilot questionnaire was created by consulting the literature, clinicians, and video display terminal (VDT) workers. The replies of 636 subjects completing the questionnaire were assessed using the Rasch model and conventional statistics to generate a new scale, designated the Computer-Vision Symptom Scale (CVSS17). Validity and reliability were determined by Rasch fit statistics, principal components analysis (PCA), person separation, differential item functioning (DIF), and item-person targeting. To assess construct validity, the CVSS17 was correlated with a Rasch-based visual discomfort scale (VDS) in 163 VDT workers, this group completed the CVSS17 twice in order to assess test-retest reliability (two-way single-measure intraclass correlation coefficient [ICC] and their 95% confidence intervals, and the coefficient of repeatability [COR]). RESULTS. The CVSS17 contains 17 items exploring 15 different symptoms. These items showed good reliability and internal consistency (mean square infit and outfit 0.88-1.17, eigenvalue for the first residual PCA component 1.37, person separation 2.85, and no DIF). Pearson's correlation with VDS scores was 0.60 (P < 0.001). Intraclass correlation coefficient for testretest reliability was 0.849 (95% confidence interval [CI], 0.800-0.887), and COR was 8.14. CONCLUSIONS. The Rasch-based linear-scale CVSS17 emerged as a useful tool to quantify CRVOS in computer workers.

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