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Body and Social Anhedonia of Depression: A Bifactor Model Analysis

The purpose of this study was to develop a statistical model of anhedonia of depression. The study included 748 healthy controls (350 women, 46.79%, age 21.27 ± 4.72) and 80 patients (32 women, 40%, age 38.36 ± 16.42). The Physical Anhedonia Scale (PhAS), the Social Anhedonia Scale (CSAS), the Posit...

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Detalles Bibliográficos
Autores principales: Feng, Bo, Jiang, Yuan, Li, Yijun, Liu, Xufeng, Wu, Shengjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ubiquity Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120899/
https://www.ncbi.nlm.nih.gov/pubmed/32269829
http://dx.doi.org/10.5334/pb.524
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author Feng, Bo
Jiang, Yuan
Li, Yijun
Liu, Xufeng
Wu, Shengjun
author_facet Feng, Bo
Jiang, Yuan
Li, Yijun
Liu, Xufeng
Wu, Shengjun
author_sort Feng, Bo
collection PubMed
description The purpose of this study was to develop a statistical model of anhedonia of depression. The study included 748 healthy controls (350 women, 46.79%, age 21.27 ± 4.72) and 80 patients (32 women, 40%, age 38.36 ± 16.42). The Physical Anhedonia Scale (PhAS), the Social Anhedonia Scale (CSAS), the Positive and Negative Affect Scale (PANAS) and the Beck Depression Inventory(BDI) were administered. Classical Measurement Theory (CTT) and Item Response Theory (IRT) were applied to the collected data. We observed that the general factor of depression status was significantly related with positive emotion (r = –0.37, P < 0.05), negative emotion (r = 0.62, P < 0.05) and BDI (r = 0.48, P < 0.01). A significant difference also was observed between controls and patients. The bifactor model of anhedonia of depression provided a better fit to the data than a unidimensional model. The bifactor model appears to be useful to describe anhedonia in depression.
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spelling pubmed-71208992020-04-08 Body and Social Anhedonia of Depression: A Bifactor Model Analysis Feng, Bo Jiang, Yuan Li, Yijun Liu, Xufeng Wu, Shengjun Psychol Belg Research Article The purpose of this study was to develop a statistical model of anhedonia of depression. The study included 748 healthy controls (350 women, 46.79%, age 21.27 ± 4.72) and 80 patients (32 women, 40%, age 38.36 ± 16.42). The Physical Anhedonia Scale (PhAS), the Social Anhedonia Scale (CSAS), the Positive and Negative Affect Scale (PANAS) and the Beck Depression Inventory(BDI) were administered. Classical Measurement Theory (CTT) and Item Response Theory (IRT) were applied to the collected data. We observed that the general factor of depression status was significantly related with positive emotion (r = –0.37, P < 0.05), negative emotion (r = 0.62, P < 0.05) and BDI (r = 0.48, P < 0.01). A significant difference also was observed between controls and patients. The bifactor model of anhedonia of depression provided a better fit to the data than a unidimensional model. The bifactor model appears to be useful to describe anhedonia in depression. Ubiquity Press 2020-04-02 /pmc/articles/PMC7120899/ /pubmed/32269829 http://dx.doi.org/10.5334/pb.524 Text en Copyright: © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Article
Feng, Bo
Jiang, Yuan
Li, Yijun
Liu, Xufeng
Wu, Shengjun
Body and Social Anhedonia of Depression: A Bifactor Model Analysis
title Body and Social Anhedonia of Depression: A Bifactor Model Analysis
title_full Body and Social Anhedonia of Depression: A Bifactor Model Analysis
title_fullStr Body and Social Anhedonia of Depression: A Bifactor Model Analysis
title_full_unstemmed Body and Social Anhedonia of Depression: A Bifactor Model Analysis
title_short Body and Social Anhedonia of Depression: A Bifactor Model Analysis
title_sort body and social anhedonia of depression: a bifactor model analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120899/
https://www.ncbi.nlm.nih.gov/pubmed/32269829
http://dx.doi.org/10.5334/pb.524
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