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

doi:10.1080/20008198.2020.1759279

	An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network
	Li, Gen 1,2; Wang, Li1,2 ; Cao, Chengqi 1,3; Fang, Ruojiao 1,2; Bi, Yajie 1,2; Liu, Ping 4; Luo, Shu 4; Hall, Brian J.5,6; Elhai, Jon D.7
通讯作者	Wang, Li(wangli1@psych.ac.cn)
摘要	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.
关键词	Latent factor symptom network posttraumatic stress disorder
	2020
语种	英语
DOI	10.1080/20008198.2020.1759279
发表期刊	EUROPEAN JOURNAL OF PSYCHOTRAUMATOLOGY
ISSN	2000-8198
卷号	11 期号:1 页码:11
收录类别	SCI
资助项目	External Cooperation Program of Chinese Academy of Sciences[153111KYSB20160036] ; National Natural Science Foundation of China[31271099] ; National Natural Science Foundation of China[31471004] ; Key Project of Research Base of Humanities and Social Sciences of Ministry of Education[16JJD190006] ; Beijing Municipal Science and Technology Commission[Z171100000117014]
出版者	TAYLOR & FRANCIS LTD
WOS研究方向	Psychology ; Psychiatry
WOS类目	Psychology, Clinical ; Psychiatry
WOS记录号	WOS:000615599100001
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.psych.ac.cn/handle/311026/38390
专题	中国科学院心理健康重点实验室
通讯作者	Wang, Li
作者单位	1.Chinese Acad Sci, Inst Psychol, Lab Traumat Stress Studies, CAS Key Lab Mental Hlth, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Dept Psychol, Beijing, Peoples R China 3.Shenzhen Univ, Shenzhen Key Lab Affect & Social Cognit Sci, Shenzhen, Peoples R China 4.Peoples Hosp Deyang City, Dept Psychosomat, Deyang, Shichuan, Peoples R China 5.Univ Macau, Fac Social Sci, Dept Psychol, Global & Community Mental Hlth Res Grp, Ave Univ, Taipa, Macao, Peoples R China 6.Johns Hopkins Bloomberg Sch Publ Hlth, Dept Hlth Behav & Soc, Baltimore, MD USA 7.Univ Toledo, Dept Psychol, Toledo, OH 43606 USA
第一作者单位	中国科学院心理健康重点实验室
通讯作者单位	中国科学院心理健康重点实验室
推荐引用方式 GB/T 7714	Li, Gen,Wang, Li,Cao, Chengqi,et al. An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network[J]. EUROPEAN JOURNAL OF PSYCHOTRAUMATOLOGY,2020,11(1):11.
APA	Li, Gen.,Wang, Li.,Cao, Chengqi.,Fang, Ruojiao.,Bi, Yajie.,...&Elhai, Jon D..(2020).An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network.EUROPEAN JOURNAL OF PSYCHOTRAUMATOLOGY,11(1),11.
MLA	Li, Gen,et al."An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network".EUROPEAN JOURNAL OF PSYCHOTRAUMATOLOGY 11.1(2020):11.