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Schizophr Bull. 2010 Jul;36(4):811-29. doi: 10.1093/schbul/sbn181. Epub 2009 Jan 27.

Seeking verisimilitude in a class: a systematic review of evidence that the criterial clinical symptoms of schizophrenia are taxonic.

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1
Department of Psychology, University of Otago, PO Box 56, Dunedin 9054, New Zealand. linscott@psy.otago.ac.nz

Abstract

This review examines whether there is evidence that the criterion symptoms of Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) (DSM-IV) schizophrenia are taxonic--that schizophrenia is not part of a single distribution of normality. Two taxometric methods, coherent cut kinetics (CCK) and latent variable modeling (LVM), are demonstrated to be sensitive to latent classes and, therefore, were regarded as providing relevant statistical evidence. A systematic literature search identified 24 articles describing analyses of 28 participant cohorts in which CCK or LVM methods were used with one or more criterion symptoms of schizophrenia. Virtually all analyses yielded results that, on first impression, favored taxonic over dimensional interpretations of the latent structure of schizophrenia. However, threats to the internal and external validity of these studies--including biased or inadequate analyses, violation of statistical assumptions, inadequate indicator screening, and the introduction of systematic error through recruitment and sampling--critically undermine this body of work. Uncertainties about the potential effects of perceptual biases, unimodal assessment, and item parceling are also identified, as are limitations in seeking to validate classes with single or double dissociations of outcomes. We conclude that there is no reason to seriously doubt a single-distribution model of schizophrenia because there is no evidence that provides a serious test of this null hypothesis. A second fundamental question remains outstanding: is schizophrenia truly a group of schizophrenias, with taxonic divisions separating its types? We make design and analysis suggestions for future research addressing these questions.

PMID:
19176472
PMCID:
PMC2894590
DOI:
10.1093/schbul/sbn181
[Indexed for MEDLINE]
Free PMC Article
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