Your browser doesn't support javascript.
loading
Bridge centrality network structure of negative symptoms in people with schizophrenia.
Wang, Ling-Ling; Tam, Michelle H W; Ho, Karen K Y; Hung, Karen S Y; Wong, Jessica O Y; Lui, Simon S Y; Chan, Raymond C K.
Afiliação
  • Wang LL; Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China.
  • Tam MHW; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
  • Ho KKY; Castle Peak Hospital, Hong Kong Special Administrative Region, China.
  • Hung KSY; Castle Peak Hospital, Hong Kong Special Administrative Region, China.
  • Wong JOY; Castle Peak Hospital, Hong Kong Special Administrative Region, China.
  • Lui SSY; Castle Peak Hospital, Hong Kong Special Administrative Region, China.
  • Chan RCK; Department of Psychiatry, School of Clinical Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China. lsy570@hku.hk.
Eur Arch Psychiatry Clin Neurosci ; 273(3): 589-600, 2023 Apr.
Article em En | MEDLINE | ID: mdl-35972557
ABSTRACT
Negative symptoms are complex psychopathology. Although evidence generally supported the NIMH five consensus domains, research seldom examined measurement invariance of this model, and domain-specific correspondence across multiple scales. This study aimed to examine the interrelationship between negative symptom domains captured by different rating scales, and to examine the domain-specific correspondence across multiple scales. We administered the Brief Negative Symptom Scale (BNSS), the Self-evaluation of Negative Symptoms (SNS), and the Scale for Assessment of Negative Symptoms (SANS) to 204 individuals with schizophrenia. We used network analysis to examine the interrelationship between negative symptom domains. Besides regularized partial correlation network, we estimated bridge centrality indices to investigate domain-specific correspondence, while taking each scale as an independent community. The regularized partial correlation network showed that the SNS nodes clustered together, whereas the SANS and the BNSS nodes intermingled together. The SANS attention domain lied at the periphery of the network according to the Fruchterman-Reingold algorithm. The SANS anhedonia-asociality (strength = 1.48; EI = 1.48) and the SANS affective flattening (strength = 1.06; EI = 1.06) had the highest node strength and EI. Moreover, the five nodes of the BNSS bridged the nodes of the SANS and the SNS. BNSS blunted affect (strength = 0.76; EI = 0.76) and SANS anhedonia-asociality (strength = 0.76; EI = 0.74) showed the highest bridge strength and bridge EI. The BNSS captures negative symptoms and bridges the symptom domains measured by the SANS and the SNS. The three scales showed domain-specific correspondence.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Esquizofrenia Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Eur Arch Psychiatry Clin Neurosci Assunto da revista: NEUROLOGIA / PSIQUIATRIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Esquizofrenia Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Eur Arch Psychiatry Clin Neurosci Assunto da revista: NEUROLOGIA / PSIQUIATRIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China