The Structure and Individual Patterns of Trait Impulsivity Across Addiction Disorders: a Network Analysis.
Addiction is associated with high impulsivity. Behavioral impulsivity sets the vulnerability in addiction formation, facilitates drug use, and acts as one most important risk factors for relapse. However, the pattern of individual heterogeneity across addictive disorders for precision medicine is st...
| Publicado en: | International Journal of Mental Health & Addiction Vol. 22; no. 5; pp. 2844 - 2861 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Oct2024
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=181830960&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 181830960 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 15571874 46AW jtl: International Journal of Mental Health & Addiction issn: 15571874 maglogo: N pubinfo: dt: Oct2024 vid: 22 iid: 5 pid: 237 pub: Springer Nature artinfo: ui: 181830960 10.1007/s11469-023-01022-0 ppf: 2844 ppct: 17 formats: fmt: – @attributes: type: T – @attributes: type: P size: 3.1MB tig: atl: The Structure and Individual Patterns of Trait Impulsivity Across Addiction Disorders: a Network Analysis. aug: au: Guo, Lei Chen, Tianzhen Zheng, Hui Zhong, Na Wu, Qianying Su, Hang Jiang, Haifeng Du, Jiang Dong, Guangheng Yuan, Ti-Fei Zhao, Min affil: https://ror.org/05bd2wa15 Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 600 Wan Ping Nan Road, Shanghai, China https://ror.org/01bkvqx83 Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Zhejiang Province, Hangzhou, China https://ror.org/05bd2wa15 Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai, China https://ror.org/02afcvw97 Co-Innovation Center of Neuroregeneration, Nantong University, Nantong, China https://ror.org/034t30j35 CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Sciences, Shanghai, China su: Gaming disorder Impulsive personality Addictions Individualized medicine Heroin sug: subj: Gaming disorder Impulsive personality Addictions Individualized medicine Heroin keyword: Addiction Clustering Impulsivity Internet gaming disorder Network analysis Addiction Clustering Impulsivity Internet gaming disorder Network analysis ab: Addiction is associated with high impulsivity. Behavioral impulsivity sets the vulnerability in addiction formation, facilitates drug use, and acts as one most important risk factors for relapse. However, the pattern of individual heterogeneity across addictive disorders for precision medicine is still unclear. We performed network-based analysis using the clinical data of trait impulsivity from 1687 subjects with stimulant and heroin use disorders, as well as Internet gaming disorder (IGD). Based on Barratt Impulsivity Scale (BIS) measurements, the trait impulsivity networks and individual differential impulsivity networks (IDINs) were constructed. The three types of addiction respectively accompany different core impulsivity traits. The global network strength in stimulant use disorder was significantly higher than that in other addiction types, and non-planning impulsivity connections in heroin subjects differed from the rest groups. Based on the individual differential impulsivity networks, these subjects were clustered into three types, as deviated from control subjects. The three deviation patterns were related to addiction type, age, education, and addiction duration. These findings indicated different core impulsivity traits across addictions and heterogeneity of individual trait impulsivity patterns, which supports individualized medicine in managing impulsivity. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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