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Beyond factor analysis: Multidimensionality and the Parkinson’s Disease Sleep Scale-Revised

Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson’s disease (PD). The Parkinson’s Disease Sleep Scale (PDSS) and its variants (the Parkinson’s disease Sleep Scale-Revised; PDSS-R, and the Parkinson’s Disease Sleep Scale-2; PDSS-2) quantify a r...

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Autores principales: Pushpanathan, Maria E., Loftus, Andrea M., Gasson, Natalie, Thomas, Meghan G., Timms, Caitlin F., Olaithe, Michelle, Bucks, Romola S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5809063/
https://www.ncbi.nlm.nih.gov/pubmed/29432463
http://dx.doi.org/10.1371/journal.pone.0192394
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author Pushpanathan, Maria E.
Loftus, Andrea M.
Gasson, Natalie
Thomas, Meghan G.
Timms, Caitlin F.
Olaithe, Michelle
Bucks, Romola S.
author_facet Pushpanathan, Maria E.
Loftus, Andrea M.
Gasson, Natalie
Thomas, Meghan G.
Timms, Caitlin F.
Olaithe, Michelle
Bucks, Romola S.
author_sort Pushpanathan, Maria E.
collection PubMed
description Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson’s disease (PD). The Parkinson’s Disease Sleep Scale (PDSS) and its variants (the Parkinson’s disease Sleep Scale-Revised; PDSS-R, and the Parkinson’s Disease Sleep Scale-2; PDSS-2) quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model) is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA) and REM sleep behaviour disorder (RBD) symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments.
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spelling pubmed-58090632018-02-28 Beyond factor analysis: Multidimensionality and the Parkinson’s Disease Sleep Scale-Revised Pushpanathan, Maria E. Loftus, Andrea M. Gasson, Natalie Thomas, Meghan G. Timms, Caitlin F. Olaithe, Michelle Bucks, Romola S. PLoS One Research Article Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson’s disease (PD). The Parkinson’s Disease Sleep Scale (PDSS) and its variants (the Parkinson’s disease Sleep Scale-Revised; PDSS-R, and the Parkinson’s Disease Sleep Scale-2; PDSS-2) quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model) is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA) and REM sleep behaviour disorder (RBD) symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments. Public Library of Science 2018-02-12 /pmc/articles/PMC5809063/ /pubmed/29432463 http://dx.doi.org/10.1371/journal.pone.0192394 Text en © 2018 Pushpanathan et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Pushpanathan, Maria E.
Loftus, Andrea M.
Gasson, Natalie
Thomas, Meghan G.
Timms, Caitlin F.
Olaithe, Michelle
Bucks, Romola S.
Beyond factor analysis: Multidimensionality and the Parkinson’s Disease Sleep Scale-Revised
title Beyond factor analysis: Multidimensionality and the Parkinson’s Disease Sleep Scale-Revised
title_full Beyond factor analysis: Multidimensionality and the Parkinson’s Disease Sleep Scale-Revised
title_fullStr Beyond factor analysis: Multidimensionality and the Parkinson’s Disease Sleep Scale-Revised
title_full_unstemmed Beyond factor analysis: Multidimensionality and the Parkinson’s Disease Sleep Scale-Revised
title_short Beyond factor analysis: Multidimensionality and the Parkinson’s Disease Sleep Scale-Revised
title_sort beyond factor analysis: multidimensionality and the parkinson’s disease sleep scale-revised
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5809063/
https://www.ncbi.nlm.nih.gov/pubmed/29432463
http://dx.doi.org/10.1371/journal.pone.0192394
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