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. 2022 Apr 8;19(8):4506.
doi: 10.3390/ijerph19084506.

Rasch-Validated Italian Scale for Diagnosing Digital Eye Strain: The Computer Vision Syndrome Questionnaire IT©

Natalia Cantó-Sancho  1 , Elena Ronda  2   3 , Julio Cabrero-García  4 , Stefano Casati  5 , Angela Carta  6   7 , Stefano Porru  6   7 , Mar Seguí-Crespo  1   2
Affiliations

Rasch-Validated Italian Scale for Diagnosing Digital Eye Strain: The Computer Vision Syndrome Questionnaire IT©

Natalia Cantó-Sancho et al. Int J Environ Res Public Health. .

Abstract

The use of digital devices affects eye health; this can influence the performance of workers. To assess this impact, validated patient-reported outcome questionnaires are needed. The purpose of this study was to validate the psychometric properties of the Italian version of the Computer Vision Syndrome Questionnaire (CVS-Q©) using Rasch analysis. Two hundred and forty-one Italian workers completed an ad hoc questionnaire on anamnesis and exposure to digital devices, and the Italian version of the CVS-Q©. Subsequently, a battery involving three clinical ocular surface and tear tests was performed. The reliability and validity of the scale was assessed using the Andrich Rating Scale Model, and the prevalence of computer vision syndrome (CVS) was calculated. A good fit of both items and persons to the predictions of the Rasch model was observed, with acceptable reliability, unidimensionality, and no or minimal severe differences as a function of gender or age; moreover, good test-retest repeatability, adequate values of sensitivity, reliability, and area under the curve, and adequate construct validity based on clinical tests were obtained. Workers with a questionnaire score ≥ 7 were found to present with CVS. The prevalence of CVS was 76.6%. The CVS-Q IT© is a valid and reliable scale to assess CVS in Italian workers who use digital devices.

Keywords: Rasch model; asthenopia; psychometrics; surveys and questionnaires; validation study.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Category response probability curves for the CVS-Q IT©.
Figure 2
Figure 2
Information function of the CVS-Q IT©.
Figure 3
Figure 3
Item–person map for the CVS-Q IT©.
Figure 4
Figure 4
Receiver operator characteristic curve of the CVS-Q IT©.
Figure 5
Figure 5
Percentage of workers who presented each symptom according to frequency and intensity.
See this image and copyright information in PMC

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