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Measurement of the psychosis continuum: Modelling the frequency and distress of subclinical psychotic experiences

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  • Mark Shevlin
  • David Boyda
  • James Houston
  • Jamie Murphy

Abstract

Objective: Dimensional models of psychosis symptom frequency at clinical levels are representative of symptom dimensionality that is inclusive of distress. However, factor models of psychotic-like experiences, or subclinical symptomatology, in the general population have only ever been estimated using information on the frequency of occurrence. To ascertain whether dimensional representations of psychosis at subclinical levels are reflective of clinical manifestations of psychosis, factor models must utilise data that permits the measurement of both frequency and distress of psychosis experiences.Method: Psychotic-like experiences were assessed in a nonclinical sample (N = 462) using the 20 positive items from the CAPE42, which is a self-report questionnaire of psychotic experiences. For each item of the CAPE the frequency and distress ratings were recoded to form composite scores. Seven factor analytic models were specified and tested using confirmatory factor analysis.Results: The five-factor model of Wigman et al. (hallucinations, paranoia, grandiosity, delusions and paranormal beliefs factors) represented the best fitting model for both frequency and composite data.Conclusions: The findings constitute further evidence for a continuum of psychosis within the general population. Future analyses, aimed at delineating the dimensionality of psychosis, must advance towards the inclusion of distress as a central and necessary adjunct to measurement.

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  • Mark Shevlin & David Boyda & James Houston & Jamie Murphy, 2015. "Measurement of the psychosis continuum: Modelling the frequency and distress of subclinical psychotic experiences," Psychosis, Taylor & Francis Journals, vol. 7(2), pages 108-118, April.
    • Handle: RePEc:taf:rpsyxx:v:7:y:2015:i:2:p:108-118
    DOI: 10.1080/17522439.2014.931451
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    References listed on IDEAS

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    1. Ledyard Tucker & Charles Lewis, 1973. "A reliability coefficient for maximum likelihood factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 38(1), pages 1-10, March.
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