Person:
Susi García, María Del Rosario

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First Name
María Del Rosario
Last Name
Susi García
URI
https://hdl.handle.net/20.500.14352/77434
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Estudios estadísticos
Department
Estadística y Ciencia de los Datos
Area
Estadística e Investigación Operativa
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2014 - 201912020 - 20221
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Item Type: Publication × Subject: 617.75 ×

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    The Computer-Vision Symptom Scale (CVSS17): Development and Initial Validation
    (IOVS (Investigative Ophthalmology & Vision Science, 2014) González Pérez, Mariano; Susi García, María Del Rosario; Antona Peñalba, Beatriz; Barrio de Santos, Ana Rosa; González Díaz-Obregón, Enrique
    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 test–retest 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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    From linear questionnaires to computer-adaptive tests: Content development and calibration of the Digital Eye Strain Computer Adaptive Test (DESCAT)
    (2022) Susi García, María Del Rosario; González Pérez, Mariano; Barrio De Santos, Ana Rosa; Antona Peñalba, Beatriz
    We published in 2015 a linear Rasch-based scale (Computer Vision Symptom Scale, aka CVSS17) for measuring the computer-related visual and ocular symptoms in workers using video-display terminals. Because Computer adaptive testing (CAT) is currently considered a more efficient and less time-consuming (for test-takers) method than traditional linear questionnaires, we decided to create a new CAT for assessing these symptoms in general population. Therefore, the aim of our study is to identify content for this new CAT and to calibrate the items included in it.