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. 2022 Feb 22;19(5):2517.
doi: 10.3390/ijerph19052517.

The 17-Item Computer Vision Symptom Scale Questionnaire (CVSS17): Translation, Validation and Reliability of the Italian Version

Gemma Caterina Maria Rossi  1 , Federica Bettio  1 , Mariano González-Pérez  2 , Aba Briola  1 , Gemma Ludovica Maria Pasinetti  3 , Luigia Scudeller  4
Affiliations

The 17-Item Computer Vision Symptom Scale Questionnaire (CVSS17): Translation, Validation and Reliability of the Italian Version

Gemma Caterina Maria Rossi et al. Int J Environ Res Public Health. .

Abstract

Background. To validate the 17-item Computer Vision Symptom Scale questionnaire (CVSS17) in Italian. Methods. Cross-sectional validation study on video terminal (VDT) users and a reference sample of subjects not working at a VDT (control group), cognitively able to respond to a health status interview. The Italian self-administered version of the CVSS17 questionnaire was administered to all participants. The reliability and validity of the Italian translation of the CVSS17 were tested using standard statistical methods for questionnaire validation. The Rasch analysis was performed as well. Results. A total of 216 subjects were enrolled. Concerning the reliability, the Cronbach’s alpha coefficient was 0.925 (from 0.917 to 0.924), and the test−retest stability was 0.91 (<0.001). Concerning the validity, the control group had significantly better scores, and there were good correlations between responses to the CVSS17 and analogous domains of the GSS. Conclusion. The Italian version of the CVSS17 has shown psychometric properties comparable to those of the Spanish version, having good validity, discriminatory power, internal consistency and reliability. The questionnaire is a specific measure of vision-related quality of life in Italian-speaking VDT workers and can be used both in clinical practice and for research purposes.

Keywords: COVID-19; CVSS17; VDT; asthenopia; computer vision symptom scale questionnaire; computer vision syndrome; dry eye; ocular surface; ocular surface disease; quality of life; video display terminal workers.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Reliability: test–retest for temporal stability of CVSS17 in a random subset of 20 subjects.
Figure 2
Figure 2
Principal components analysis of the Italian CVSS: scree plot and loadings plot (rotated varimax). (a) Explanation: this is a useful way to decide how many dimensions are represented by the data; it plots the dimensions as the X-axis and the corresponding eigenvalues (variance) as the Y-axis (the dimension with the largest eigenvalue has the most variance, dimensions with smaller or negative eigenvalues are negligible; traditionally, only eigenvalues >1 are considered relevant). Across subsequent dimensions, eigenvalues decline; the number of dimensions necessary to explain the data is indicated by the number of dimensions before the “elbow” (the point where the slope of the curve flattens out). Comment: in our questionnaire, the computer vision scale is well represented by a single dimension. (b) Explanation: it shows the loadings (correlations of the items with the dimension) for the two dimensions with highest variance in each area of awareness. Comment: most items are similarly correlated to the first dimension, and unevenly correlated with the second dimension retained in the analysis; these plots, besides confirming the findings from the multitrait/multi-item analysis, support the correct dimensionality of the questionnaire.
Figure 2
Figure 2
Principal components analysis of the Italian CVSS: scree plot and loadings plot (rotated varimax). (a) Explanation: this is a useful way to decide how many dimensions are represented by the data; it plots the dimensions as the X-axis and the corresponding eigenvalues (variance) as the Y-axis (the dimension with the largest eigenvalue has the most variance, dimensions with smaller or negative eigenvalues are negligible; traditionally, only eigenvalues >1 are considered relevant). Across subsequent dimensions, eigenvalues decline; the number of dimensions necessary to explain the data is indicated by the number of dimensions before the “elbow” (the point where the slope of the curve flattens out). Comment: in our questionnaire, the computer vision scale is well represented by a single dimension. (b) Explanation: it shows the loadings (correlations of the items with the dimension) for the two dimensions with highest variance in each area of awareness. Comment: most items are similarly correlated to the first dimension, and unevenly correlated with the second dimension retained in the analysis; these plots, besides confirming the findings from the multitrait/multi-item analysis, support the correct dimensionality of the questionnaire.
Figure 3
Figure 3
Boundary characteristic curves (BCC) from the graded response model (IRT analysis) of the Italian version of CVSS.
Figure 4
Figure 4
Category characteristic curves (CCC) and empirical proportions for each of the 17 CVSS items from the graded response model (IRT analysis) of the Italian version of the CVSS17.
Figure 5
Figure 5
Item information function (IIF) proportions for each of the 17 CVSS items from the graded response model (IRT analysis) of the Italian version of CVSS.
Figure 6
Figure 6
Test characteristic curve (TCC) from the partial credit model (IRT analysis) of the Italian version of CVSS.
Figure 7
Figure 7
Test characteristic curve (TCC): CVSS summated score vs. predicted score from the graded response model (IRT analysis) of the Italian version of the CVSS.
Figure 8
Figure 8
Test information function (TIF) from the graded response model (IRT analysis) of the Italian version of the CVSS.
See this image and copyright information in PMC

References

    1. Ostrovsky A., Ribak J., Pereg A., Gaton D. Effects of job-related stress and burnout on asthenopia among high-tech workers. Ergonomics. 2012;55:854–862. doi: 10.1080/00140139.2012.681808. - DOI - PubMed
    1. Portello J.K., Rosenfield M., Bababekova Y., Estrada J.M., Leon A. Computer-related visual symptoms in office workers. Ophthalmic Physiol. Opt. 2012;32:375–382. doi: 10.1111/j.1475-1313.2012.00925.x. - DOI - PubMed
    1. Sa E.C., Ferreira M., Jr., Rocha L.E. Risk factors for computer visual syndrome (CVS) among operators of two call centers in Sao Paulo, Brazil. Work. 2012;41:3568–3574. doi: 10.3233/WOR-2012-0636-3568. - DOI - PubMed
    1. Taino G., Ferrari M., Metad I., Fabris E., Imbriani M. Astenopia e lavoro al VDT: Studio di una popolazione di 191 lavoratori esposti al rischio mediante somministrazione di questionario anamnestico mirato a valutazione oftalmologica. Giornale Italiano di Medicina del Lavoro ed Ergonomia. 2006;28:487–497. - PubMed
    1. Hayes J.R., Sheedy J.E., Stelmack J.A., Heaney C.A. Computer Use, Symptoms, and Quality of Life. Optom. Vis. Sci. 2007;84:738–744. doi: 10.1097/OPX.0b013e31812f7546. - DOI - PubMed

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