Latent structure of self-report negative symptoms in patients with schizophrenia: A preliminary study

Autor: Jessica O. Y. Wong, Wang Ling-ling, Raymond C.K. Chan, Eric F.C. Cheung, Koi-man Cheng, Michelle H.W. Tam, Simon S.Y. Lui
Rok vydání: 2021
Předmět:
Zdroj: Asian journal of psychiatry. 61
ISSN: 1876-2026
Popis: Negative symptoms are associated with poor outcomes and functioning. Latent structure of negative symptoms is important for identifying potential intervention targets for novel treatments. Self-report instruments have been developed to measure negative symptoms. Previous findings on latent structure of negative symptoms are inconsistently and mainly rely on clinician-rated instruments.We aimed to explore the latent structure of the Self-Evaluation of Negative Symptoms Scale (SNS) in 204 clinically-stable outpatients with schizophrenia. Confirmatory factor analysis (CFA) was used to compare the competing models (i.e., one-factor, two-factor and five-factor models), and estimated goodness-of-fit indexes. Other clinician-rated scales for psychopathology and medication side-effects were also collected.The CFA found the five-factor model performing best, with a comparative fit index (CFI) of0.95, a Tucker Lewis Index (TLI) of0.95, and a root mean square error of approximation (RMSEA) of0.06. The robust chi-square difference test for the weighted least squares with mean and variance adjusted estimation (WLSMV) also indicated a significant better fit for the five-factor model.Our preliminary findings support a five-factor latent structure of self-report negative symptoms in schizophrenia patients. Further research in this area should utilize multiple clinician-rated and self-report measures, and recruit large and homogeneous samples with schizophrenia.
Databáze: OpenAIRE
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