2026-06-29T02:51:32Zhttps://docta.ucm.es/rest/oai/request
oai:docta.ucm.es:20.500.14352/1254792025-10-31T01:07:43Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense author Susi García, María Del Rosario author González Pérez, Mariano author Antona Peñalba, Beatriz author Barrio De Santos, Ana Rosa author Pérez-Garmendia, Carlos author Hoang, Kathleen author Rosenfield, Mark 2025-10-28T16:02:09Z 2025-10-28T16:02:09Z 2025-04 González-Pérez, M. et al. (2025) “English version of the Computer Vision Symptom Scale (CVSS17): Translation and Rasch analysis-based cultural adaptation,” PLoS One, 20(4), p. e0316936. Available at: https://doi.org/10.1371/journal.pone.0316936. 1932-6203 10.1371/ journal.pone.0316936 https://hdl.handle.net/20.500.14352/125479 https://doi.org/10.1371/ journal.pone.0316936 https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0316936 Background Because the CVSS17 was originally developed in Spanish, the objective of this study was to adapt it linguistically and culturally into English while evaluating its psychometric properties. Methods After translating and adapting the CVSS17 to English, 441 participants (aged 18 to 65 years) from a general population, recruited from an on-line panel, completed the English version (CVSS17ENG). To determine the measurement properties of CVSS17ENG, we used the partial credit model. To assess convergent validity, coefficients of correlation between CVSS17ENG and the Ocular Comfort Index or Visual Discomfort Scale were calculated. A subset of 218 subjects was tested for test-retest reliability. In addition, differences between CVSS17ENG and CVSS17 were tested through Differential Item Functioning (a Rasch sta-tistic used to check item bias). Results A total of 441 responses to CVSS17ENG (average age, 38.57; age range, 19–65; females, 50.24%) showed good fit to the Rasch model, good precision (person separation index = 2.73), and suboptimal targeting (-1.43). Residual principal component analysis suggested multidimensionality, but this was ruled out by a disattenuated correlation coefficient value of 0.82, and no DIF according to sex or age was found. Pearson correlation for CVSS17ENG-VDS was 0.54 (p < 0.01) and Spearman correlation for CVSS17ENG-Ocular Comfort Index was 0.66 (p < 0.001). For test– retest reliability, the limits of agreement were 9.39 and -8.61. Rasch analysis results were similar for CVSS17 and CVSS17ENG and there was no evidence of item bias based on gender or age. Conclusion The English version of CVSS17 demonstrates comparable performance to the original, indicating its suitability for clinicians and researchers to reliably assess Digital Eye Strain among English-speaking users of screen-based electronic devices. eng Attribution-NonCommercial-NoDerivatives 4.0 International English version of the computer vision symptom scale (cvss17): translation and rasch analysis-based cultural adaptation journal article 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URL https://docta.ucm.es/bitstreams/498ccc86-63cd-4f73-920b-4046c64b839b/download File MD5 d406d647d0fb6890e593ccaaeb3cded4 963959 application/pdf Plos ONE - 2025 - English version of the Computer Vision Symptom Scale_Open Access CC.pdf