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A bifactor structural model of the Hungarian Pain Catastrophizing Scale and latent classes of a clinical sample

Pain catastrophizing is an exaggerated cognitive-affective response to actual or anticipated pain, usually measured by the Pain Catastrophizing Scale (PCS). Our study aimed to test the bifactor measurement model of the Hungarian PCS and to identify a catastrophizing risk group with a clinically mean...

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Autores principales: Galambos, Attila, Stoll, Dániel Péter, Bolczár, Szabolcs, Lazáry, Áron, Urbán, Róbert, Kökönyei, Gyöngyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473550/
https://www.ncbi.nlm.nih.gov/pubmed/34604562
http://dx.doi.org/10.1016/j.heliyon.2021.e08026
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author Galambos, Attila
Stoll, Dániel Péter
Bolczár, Szabolcs
Lazáry, Áron
Urbán, Róbert
Kökönyei, Gyöngyi
author_facet Galambos, Attila
Stoll, Dániel Péter
Bolczár, Szabolcs
Lazáry, Áron
Urbán, Róbert
Kökönyei, Gyöngyi
author_sort Galambos, Attila
collection PubMed
description Pain catastrophizing is an exaggerated cognitive-affective response to actual or anticipated pain, usually measured by the Pain Catastrophizing Scale (PCS). Our study aimed to test the bifactor measurement model of the Hungarian PCS and to identify a catastrophizing risk group with a clinically meaningful cut-off score. The data of 404 chronic spine-related (neck, back and low-back) pain patients (mean age: 58.61 (SD = 14.34)) were used in our cross-sectional study. Besides pain-related and demographic data, pain catastrophizing and depressive symptoms were measured with questionnaires. Confirmatory factor analyses confirmed that the bifactor model outperformed the other tested measurement models, and the general catastrophizing factor was responsible for 81.5% of the explained variance. Using latent class analysis, we found that even moderately elevated pain catastrophizing score was related to more depressive symptoms and higher perceived pain intensity, and 22 score could be used as a cut-off score. Our results support the concept of global pain catastrophizing and the validity of the Hungarian PCS. Further studies are needed to evaluate the bifactor structure of this scale and the predictive value of the proposed cut-off score.
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spelling pubmed-84735502021-10-01 A bifactor structural model of the Hungarian Pain Catastrophizing Scale and latent classes of a clinical sample Galambos, Attila Stoll, Dániel Péter Bolczár, Szabolcs Lazáry, Áron Urbán, Róbert Kökönyei, Gyöngyi Heliyon Research Article Pain catastrophizing is an exaggerated cognitive-affective response to actual or anticipated pain, usually measured by the Pain Catastrophizing Scale (PCS). Our study aimed to test the bifactor measurement model of the Hungarian PCS and to identify a catastrophizing risk group with a clinically meaningful cut-off score. The data of 404 chronic spine-related (neck, back and low-back) pain patients (mean age: 58.61 (SD = 14.34)) were used in our cross-sectional study. Besides pain-related and demographic data, pain catastrophizing and depressive symptoms were measured with questionnaires. Confirmatory factor analyses confirmed that the bifactor model outperformed the other tested measurement models, and the general catastrophizing factor was responsible for 81.5% of the explained variance. Using latent class analysis, we found that even moderately elevated pain catastrophizing score was related to more depressive symptoms and higher perceived pain intensity, and 22 score could be used as a cut-off score. Our results support the concept of global pain catastrophizing and the validity of the Hungarian PCS. Further studies are needed to evaluate the bifactor structure of this scale and the predictive value of the proposed cut-off score. Elsevier 2021-09-20 /pmc/articles/PMC8473550/ /pubmed/34604562 http://dx.doi.org/10.1016/j.heliyon.2021.e08026 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Galambos, Attila
Stoll, Dániel Péter
Bolczár, Szabolcs
Lazáry, Áron
Urbán, Róbert
Kökönyei, Gyöngyi
A bifactor structural model of the Hungarian Pain Catastrophizing Scale and latent classes of a clinical sample
title A bifactor structural model of the Hungarian Pain Catastrophizing Scale and latent classes of a clinical sample
title_full A bifactor structural model of the Hungarian Pain Catastrophizing Scale and latent classes of a clinical sample
title_fullStr A bifactor structural model of the Hungarian Pain Catastrophizing Scale and latent classes of a clinical sample
title_full_unstemmed A bifactor structural model of the Hungarian Pain Catastrophizing Scale and latent classes of a clinical sample
title_short A bifactor structural model of the Hungarian Pain Catastrophizing Scale and latent classes of a clinical sample
title_sort bifactor structural model of the hungarian pain catastrophizing scale and latent classes of a clinical sample
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473550/
https://www.ncbi.nlm.nih.gov/pubmed/34604562
http://dx.doi.org/10.1016/j.heliyon.2021.e08026
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