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

Asian J Psychiatr. 2021 Jul:61:102680. doi: 10.1016/j.ajp.2021.102680. Epub 2021 May 11.

Abstract

Introduction: 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.

Method: 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.

Results: The CFA found the five-factor model performing best, with a comparative fit index (CFI) of > 0.95, a Tucker Lewis Index (TLI) of > 0.95, and a root mean square error of approximation (RMSEA) of < 0.06. 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.

Discussion: 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.

Keywords: Latent structure; Negative symptoms; Prominent negative symptoms; Schizophrenia; Self-report scales.

MeSH terms

  • Factor Analysis, Statistical
  • Humans
  • Psychometrics
  • Reproducibility of Results
  • Schizophrenia* / diagnosis
  • Schizophrenia* / drug therapy
  • Self Report