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Rasch analysis for development and reduction of Symptom Questionnaire for Visual Dysfunctions (SQVD)
To develop the Symptom Questionnaire for Visual Dysfunctions (SQVD) and to perform a psychometric analysis using Rasch method to obtain an instrument which allows to detect the presence and frequency of visual symptoms related to any visual dysfunction. A pilot version of 33 items was carried out on...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295373/ https://www.ncbi.nlm.nih.gov/pubmed/34290288 http://dx.doi.org/10.1038/s41598-021-94166-9 |
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author | Cantó-Cerdán, Mario Cacho-Martínez, Pilar Lara-Lacárcel, Francisco García-Muñoz, Ángel |
author_facet | Cantó-Cerdán, Mario Cacho-Martínez, Pilar Lara-Lacárcel, Francisco García-Muñoz, Ángel |
author_sort | Cantó-Cerdán, Mario |
collection | PubMed |
description | To develop the Symptom Questionnaire for Visual Dysfunctions (SQVD) and to perform a psychometric analysis using Rasch method to obtain an instrument which allows to detect the presence and frequency of visual symptoms related to any visual dysfunction. A pilot version of 33 items was carried out on a sample of 125 patients from an optometric clinic. Rasch model (using Andrich Rating Scale Model) was applied to investigate the category probability curves and Andrich thresholds, infit and outfit mean square, local dependency using Yen’s Q3 statistic, Differential item functioning (DIF) for gender and presbyopia, person and item reliability, unidimensionality, targeting and ordinal to interval conversion table. Category probability curves suggested to collapse a response category. Rasch analysis reduced the questionnaire from 33 to 14 items. The final SQVD showed that 14 items fit to the model without local dependency and no significant DIF for gender and presbyopia. Person reliability was satisfactory (0.81). The first contrast of the residual was 1.908 eigenvalue, showing unidimensionality and targeting was − 1.59 logits. In general, the SQVD is a well-structured tool which shows that data adequately fit the Rasch model, with adequate psychometric properties, making it a reliable and valid instrument to measure visual symptoms. |
format | Online Article Text |
id | pubmed-8295373 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-82953732021-07-23 Rasch analysis for development and reduction of Symptom Questionnaire for Visual Dysfunctions (SQVD) Cantó-Cerdán, Mario Cacho-Martínez, Pilar Lara-Lacárcel, Francisco García-Muñoz, Ángel Sci Rep Article To develop the Symptom Questionnaire for Visual Dysfunctions (SQVD) and to perform a psychometric analysis using Rasch method to obtain an instrument which allows to detect the presence and frequency of visual symptoms related to any visual dysfunction. A pilot version of 33 items was carried out on a sample of 125 patients from an optometric clinic. Rasch model (using Andrich Rating Scale Model) was applied to investigate the category probability curves and Andrich thresholds, infit and outfit mean square, local dependency using Yen’s Q3 statistic, Differential item functioning (DIF) for gender and presbyopia, person and item reliability, unidimensionality, targeting and ordinal to interval conversion table. Category probability curves suggested to collapse a response category. Rasch analysis reduced the questionnaire from 33 to 14 items. The final SQVD showed that 14 items fit to the model without local dependency and no significant DIF for gender and presbyopia. Person reliability was satisfactory (0.81). The first contrast of the residual was 1.908 eigenvalue, showing unidimensionality and targeting was − 1.59 logits. In general, the SQVD is a well-structured tool which shows that data adequately fit the Rasch model, with adequate psychometric properties, making it a reliable and valid instrument to measure visual symptoms. Nature Publishing Group UK 2021-07-21 /pmc/articles/PMC8295373/ /pubmed/34290288 http://dx.doi.org/10.1038/s41598-021-94166-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Cantó-Cerdán, Mario Cacho-Martínez, Pilar Lara-Lacárcel, Francisco García-Muñoz, Ángel Rasch analysis for development and reduction of Symptom Questionnaire for Visual Dysfunctions (SQVD) |
title | Rasch analysis for development and reduction of Symptom Questionnaire for Visual Dysfunctions (SQVD) |
title_full | Rasch analysis for development and reduction of Symptom Questionnaire for Visual Dysfunctions (SQVD) |
title_fullStr | Rasch analysis for development and reduction of Symptom Questionnaire for Visual Dysfunctions (SQVD) |
title_full_unstemmed | Rasch analysis for development and reduction of Symptom Questionnaire for Visual Dysfunctions (SQVD) |
title_short | Rasch analysis for development and reduction of Symptom Questionnaire for Visual Dysfunctions (SQVD) |
title_sort | rasch analysis for development and reduction of symptom questionnaire for visual dysfunctions (sqvd) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295373/ https://www.ncbi.nlm.nih.gov/pubmed/34290288 http://dx.doi.org/10.1038/s41598-021-94166-9 |
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