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Factor analyzing the Norwegian MATRICS Consensus Cognitive Battery.

Christine Mohn1, June U Lystad2, Torill Ueland2,3

  • 1Research Department, Vestre Viken Hospital Trust, Drammen, Norway.

Psychiatry and Clinical Neurosciences
|February 10, 2017
PubMed
Summary
This summary is machine-generated.

The Norwegian MATRICS Consensus Cognitive Battery (MCCB) structure differs from the original model. Specific subtests like Symbol Coding and Working Memory are key indicators of neurocognitive performance in schizophrenia spectrum disorders.

Keywords:
MATRICS Consensus Cognitive Batterycognitionfactor analysisneuropsychologyschizophrenia

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Area of Science:

  • Neuroscience
  • Psychology
  • Psychiatry

Background:

  • The MATRICS Consensus Cognitive Battery (MCCB) is designed to assess seven cognitive domains using 10 subtests.
  • The proposed domain structure of the MCCB has not been empirically validated.
  • Previous studies in US samples suggested a three-factor structure.

Purpose of the Study:

  • To examine the dimensional structure of the Norwegian version of the MCCB.
  • To investigate the contribution of individual subtests to the overall MCCB sum score.

Main Methods:

  • Exploratory and confirmatory factor analysis were applied to the Norwegian MCCB scores.
  • Regression analysis was used to determine subtest contributions.
  • The study included 131 patients with schizophrenia spectrum disorders and 300 healthy controls.

Main Results:

  • The theoretical MCCB factor structure was not supported in the Norwegian sample.
  • Three-factor and two-factor models demonstrated acceptable fit in the patient group.
  • Symbol Coding, Spatial Span, Letter-Number Span, and Visual Learning subtests were significant contributors to the sum score.

Conclusions:

  • The theoretical domain structure of the MCCB was not replicated in Norwegian participants.
  • Factor analysis in both Norwegian and US samples yielded similar, albeit different from the original, cognitive domains.
  • Subtests such as Symbol Coding, Working Memory, and Learning appear most sensitive to general neurocognitive performance.