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Using network analysis to explore the validity and influential items of the Parkinson’s Disease Questionnaire-39
Quality of life (QoL) in people with Parkinson´s disease (PD) is commonly measured with the PD questionnaire-39 (PDQ-39), but its factor structure and construct validity have been questioned. To develop effective interventions to improve QoL, it is crucial to understand the connection between differ...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10156662/ https://www.ncbi.nlm.nih.gov/pubmed/37138003 http://dx.doi.org/10.1038/s41598-023-34412-4 |
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author | Schönenberg, Aline Santos García, Diego Mir, Pablo Wu, Jian-Jun Heimrich, Konstantin G. Mühlhammer, Hannah M. Prell, Tino |
author_facet | Schönenberg, Aline Santos García, Diego Mir, Pablo Wu, Jian-Jun Heimrich, Konstantin G. Mühlhammer, Hannah M. Prell, Tino |
author_sort | Schönenberg, Aline |
collection | PubMed |
description | Quality of life (QoL) in people with Parkinson´s disease (PD) is commonly measured with the PD questionnaire-39 (PDQ-39), but its factor structure and construct validity have been questioned. To develop effective interventions to improve QoL, it is crucial to understand the connection between different PDQ-39 items and to assess the validity of PDQ-39 subscales. With a new approach based on network analysis using the extended Bayesian Information Criterion Graphical Least Absolute Shrinkage and Selection Operator (EBICglasso) followed by factor analysis, we mostly replicated the original PDQ-39 subscales in two samples of PD patients (total N = 977). However, model fit was better when the “ignored” item was categorized into the social support instead of the communication subscale. In both study cohorts, “depressive mood”, “feeling isolated”, “feeling embarrassed”, and “having trouble getting around in public/needing company when going out” were identified as highly connected variables. This network approach can help to illustrate the relationship between different symptoms and direct interventional approaches in a more effective manner. |
format | Online Article Text |
id | pubmed-10156662 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-101566622023-05-05 Using network analysis to explore the validity and influential items of the Parkinson’s Disease Questionnaire-39 Schönenberg, Aline Santos García, Diego Mir, Pablo Wu, Jian-Jun Heimrich, Konstantin G. Mühlhammer, Hannah M. Prell, Tino Sci Rep Article Quality of life (QoL) in people with Parkinson´s disease (PD) is commonly measured with the PD questionnaire-39 (PDQ-39), but its factor structure and construct validity have been questioned. To develop effective interventions to improve QoL, it is crucial to understand the connection between different PDQ-39 items and to assess the validity of PDQ-39 subscales. With a new approach based on network analysis using the extended Bayesian Information Criterion Graphical Least Absolute Shrinkage and Selection Operator (EBICglasso) followed by factor analysis, we mostly replicated the original PDQ-39 subscales in two samples of PD patients (total N = 977). However, model fit was better when the “ignored” item was categorized into the social support instead of the communication subscale. In both study cohorts, “depressive mood”, “feeling isolated”, “feeling embarrassed”, and “having trouble getting around in public/needing company when going out” were identified as highly connected variables. This network approach can help to illustrate the relationship between different symptoms and direct interventional approaches in a more effective manner. Nature Publishing Group UK 2023-05-03 /pmc/articles/PMC10156662/ /pubmed/37138003 http://dx.doi.org/10.1038/s41598-023-34412-4 Text en © The Author(s) 2023 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 Schönenberg, Aline Santos García, Diego Mir, Pablo Wu, Jian-Jun Heimrich, Konstantin G. Mühlhammer, Hannah M. Prell, Tino Using network analysis to explore the validity and influential items of the Parkinson’s Disease Questionnaire-39 |
title | Using network analysis to explore the validity and influential items of the Parkinson’s Disease Questionnaire-39 |
title_full | Using network analysis to explore the validity and influential items of the Parkinson’s Disease Questionnaire-39 |
title_fullStr | Using network analysis to explore the validity and influential items of the Parkinson’s Disease Questionnaire-39 |
title_full_unstemmed | Using network analysis to explore the validity and influential items of the Parkinson’s Disease Questionnaire-39 |
title_short | Using network analysis to explore the validity and influential items of the Parkinson’s Disease Questionnaire-39 |
title_sort | using network analysis to explore the validity and influential items of the parkinson’s disease questionnaire-39 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10156662/ https://www.ncbi.nlm.nih.gov/pubmed/37138003 http://dx.doi.org/10.1038/s41598-023-34412-4 |
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