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Five levels of performance and two subscales identified in the computer-vision symptom scale (CVSS17) by Rasch, factor, and discriminant analysis

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  • Mariano González-Pérez
  • Rosario Susi
  • Ana Barrio
  • Beatriz Antona

Abstract

Purpose: To quantify the levels of performance (symptom severity) of the computer-vision symptom scale (CVSS17), confirm its bifactorial structure as detected in an exploratory factor analysis, and validate its factors as subscales. Methods: By partial credit model (PCM), we estimated CVSS17 measures and the standard error for every possible raw score, and used these data to determine the number of different performance levels in the CVSS17. In addition, through discriminant analysis, we checked that the scale's two main factors could classify subjects according to these determined levels of performance. Finally, a separate Rasch analysis was performed for each CVSS17 factor to assess their measurement properties when used as isolated scales. Results: We identified 5.8 different levels of performance. Discriminant functions obtained from sample data indicated that the scale's main factors correctly classified 98.4% of the cases. The main factors: Internal symptom factor (ISF) and external symptom factor (ESF) showed good measurement properties and can be considered as subscales. Conclusion: CVSS17 scores defined five different levels of performance. In addition, two main factors (ESF and ISF) were identified and these confirmed by discriminant analysis. These subscales served to assess either the visual or the ocular symptoms attributable to computer use.

Suggested Citation

  • Mariano González-Pérez & Rosario Susi & Ana Barrio & Beatriz Antona, 2018. "Five levels of performance and two subscales identified in the computer-vision symptom scale (CVSS17) by Rasch, factor, and discriminant analysis," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-16, August.
    • Handle: RePEc:plo:pone00:0202173
    DOI: 10.1371/journal.pone.0202173
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    Cited by:

    1. Ana Rosa Barrio & Mariano González-Pérez & Clara Heredia-Pastor & Jacobo Enríquez-Fuentes & Beatriz Antona, 2022. "Spanish Cross-Cultural Adaptation, Rasch Analysis and Validation of the Ocular Comfort Index (OCI) Questionnaire," IJERPH, MDPI, vol. 19(22), pages 1-14, November.
    2. Gemma Caterina Maria Rossi & Federica Bettio & Mariano González-Pérez & Aba Briola & Gemma Ludovica Maria Pasinetti & Luigia Scudeller, 2022. "The 17-Item Computer Vision Symptom Scale Questionnaire (CVSS17): Translation, Validation and Reliability of the Italian Version," IJERPH, MDPI, vol. 19(5), pages 1-17, February.

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