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An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network

BACKGROUND: Both the latent variable model and the network model have been widely used to conceptualize mental disorders. However, it has been pointed out that there is no clear dichotomy between the two models, and a combination of these two model could enable a better understanding of psychopathol...

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Autores principales: Li, Gen, Wang, Li, Cao, Chengqi, Fang, Ruojiao, Bi, Yajie, Liu, Ping, Luo, Shu, Hall, Brian J., Elhai, Jon D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7448915/
https://www.ncbi.nlm.nih.gov/pubmed/32922682
http://dx.doi.org/10.1080/20008198.2020.1759279
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author Li, Gen
Wang, Li
Cao, Chengqi
Fang, Ruojiao
Bi, Yajie
Liu, Ping
Luo, Shu
Hall, Brian J.
Elhai, Jon D.
author_facet Li, Gen
Wang, Li
Cao, Chengqi
Fang, Ruojiao
Bi, Yajie
Liu, Ping
Luo, Shu
Hall, Brian J.
Elhai, Jon D.
author_sort Li, Gen
collection PubMed
description BACKGROUND: Both the latent variable model and the network model have been widely used to conceptualize mental disorders. However, it has been pointed out that there is no clear dichotomy between the two models, and a combination of these two model could enable a better understanding of psychopathology. The recently proposed latent network model (LNM) has provided a statistical framework to enable this combination. Evidence has shown that posttraumatic stress disorder (PTSD) could be a suitable candidate disorder to study the combined model. In the current study, we initiated the first investigation of the latent network of PTSD symptoms. METHODS: The latent network of DSM-5 PTSD symptoms was estimated in 1196 adult survivors of China’s 2008 Wenchuan earthquake. Validation testing of the latent network was conducted in a replication sample of children and adolescent who experienced various trauma types. PTSD symptoms were measured by the PTSD Checklist for DSM-5 (PCL-5). The latent network was estimated using the seven-factor hybrid model of DSM-5 PTSD symptoms, analysed using the R package lvnet. RESULTS: The latent network model demonstrated good fit in both samples. A strong weighted edge between the intrusion and avoidance dimensions was identified (regularized partial correlation = 0.75). The externalizing behaviour dimension demonstrated the highest centrality in the latent network. CONCLUSIONS: This study is the first to investigate the latent network of DSM-5 PTSD symptoms. Results suggest that both latent symptom dimension and associations between the dimensions should be considered in future PTSD studies and clinical practices.
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spelling pubmed-74489152020-09-10 An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network Li, Gen Wang, Li Cao, Chengqi Fang, Ruojiao Bi, Yajie Liu, Ping Luo, Shu Hall, Brian J. Elhai, Jon D. Eur J Psychotraumatol Basic Research Article BACKGROUND: Both the latent variable model and the network model have been widely used to conceptualize mental disorders. However, it has been pointed out that there is no clear dichotomy between the two models, and a combination of these two model could enable a better understanding of psychopathology. The recently proposed latent network model (LNM) has provided a statistical framework to enable this combination. Evidence has shown that posttraumatic stress disorder (PTSD) could be a suitable candidate disorder to study the combined model. In the current study, we initiated the first investigation of the latent network of PTSD symptoms. METHODS: The latent network of DSM-5 PTSD symptoms was estimated in 1196 adult survivors of China’s 2008 Wenchuan earthquake. Validation testing of the latent network was conducted in a replication sample of children and adolescent who experienced various trauma types. PTSD symptoms were measured by the PTSD Checklist for DSM-5 (PCL-5). The latent network was estimated using the seven-factor hybrid model of DSM-5 PTSD symptoms, analysed using the R package lvnet. RESULTS: The latent network model demonstrated good fit in both samples. A strong weighted edge between the intrusion and avoidance dimensions was identified (regularized partial correlation = 0.75). The externalizing behaviour dimension demonstrated the highest centrality in the latent network. CONCLUSIONS: This study is the first to investigate the latent network of DSM-5 PTSD symptoms. Results suggest that both latent symptom dimension and associations between the dimensions should be considered in future PTSD studies and clinical practices. Taylor & Francis 2020-06-08 /pmc/articles/PMC7448915/ /pubmed/32922682 http://dx.doi.org/10.1080/20008198.2020.1759279 Text en © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Basic Research Article
Li, Gen
Wang, Li
Cao, Chengqi
Fang, Ruojiao
Bi, Yajie
Liu, Ping
Luo, Shu
Hall, Brian J.
Elhai, Jon D.
An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network
title An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network
title_full An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network
title_fullStr An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network
title_full_unstemmed An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network
title_short An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network
title_sort exploration of the dsm-5 posttraumatic stress disorder symptom latent variable network
topic Basic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7448915/
https://www.ncbi.nlm.nih.gov/pubmed/32922682
http://dx.doi.org/10.1080/20008198.2020.1759279
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