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Refining the latent structure of neuropsychological performance in schizophrenia

Published online by Cambridge University Press:  22 May 2014

M. Lam ,
S. L. Collinson ,
G. K. Eng ,
A. Rapisarda ,
M. Kraus ,
J. Lee ,
S. A. Chong  and
R. S. E. Keefe
M. Lam
Affiliation:
Research Division, Institute of Mental Health, Singapore
S. L. Collinson
Affiliation:
Department of Psychology, National University of Singapore, Singapore
G. K. Eng
Affiliation:
Research Division, Institute of Mental Health, Singapore Division of Psychology, School of Humanities and Social Sciences, Nanyang Technological University, Singapore
A. Rapisarda
Affiliation:
Research Division, Institute of Mental Health, Singapore Neuroscience and Behavioral Disorders, Duke-NUS Graduate Medical School, Singapore
M. Kraus
Affiliation:
Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
J. Lee
Affiliation:
Research Division, Institute of Mental Health, Singapore Department of General Psychiatry 1, Institute of Mental Health, Singapore Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore
S. A. Chong
Affiliation:
Research Division, Institute of Mental Health, Singapore
R. S. E. Keefe*
Affiliation:
Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
*
*Address for correspondence: R. S. E. Keefe, Ph.D., Department of Psychiatry, Box 3270, Duke University Medical Center, Durham, NC 27710, USA. (Email: [email protected])
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Abstract

Background.

Elucidating the cognitive architecture of schizophrenia promises to advance understanding of the clinical and biological substrates of the illness. Traditional cross-sectional neuropsychological approaches differentiate impaired from normal cognitive abilities but are limited in their ability to determine latent substructure. The current study examined the latent architecture of abnormal cognition in schizophrenia via a systematic approach.

Method.

Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were carried out on a large neuropsychological dataset including the Brief Assessment of Cognition in Schizophrenia, Continuous Performance Test, Wisconsin Card Sorting Test, Benton Judgment of Line Orientation Test, and Wechsler Abbreviated Scale of Intelligence matrix reasoning derived from 1012 English-speaking ethnic Chinese healthy controls and 707 schizophrenia cases recruited from in- and out-patient clinics.

Results.

An initial six-factor model fit cognitive data in healthy and schizophrenia subjects. Further modeling, which accounted for methodological variance between tests, resulted in a three-factor model of executive functioning, vigilance/speed of processing and memory that appeared to best discriminate schizophrenia cases from controls. Factor analytic-derived g estimands and conventionally calculated g showed similar case–control discrimination. However, agreement analysis suggested systematic differences between both g indices.

Conclusions.

Factor structures derived in the current study were broadly similar to those reported previously. However, factor structures between schizophrenia subjects and healthy controls were different. Roles of factor analytic-derived g estimands and conventional composite score g were further discussed. Cognitive structures underlying cognitive deficits in schizophrenia may prove useful for interrogating biological substrates and enriching effect sizes for subsequent work.

Keywords

Bland–Altman analysisconfirmatory factor analysisendophenotypesexploratory factor analysisg
Type
Original Articles
Information
Psychological Medicine , Volume 44 , Issue 16 , December 2014 , pp. 3557 - 3570
Copyright
Copyright © Cambridge University Press 2014 

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