The distribution of positive psychosis-like symptoms in the population: A latent class analysis of the National Comorbidity Survey

M Shevlin, Jamie Murphy, Martin J. Dorahy, Gary Adamson

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88 Citations (Scopus)

Abstract

Objective: Previous research has suggested that psychosis is better described as a continuum rather than a dichotomous entity. This study aimed to describe the distribution of positive psychosis-like symptoms in the general population by means of latent class analysis. Method: Latent class analysis was used to identify homogeneous sub-types of psychosis-like experiences. Multinomial logistic regression models were used to interpret the nature of the latent classes, or groups, by estimating the associations with demographic factors, clinical variables, and experiences of traumatic events. Results: The best fitting latent class model was a four-class solution: a psychosis class, a hallucinatory class, an intermediate class, and a normative class. The associations between the latent classes and the demographic risk factors, clinical variables, and experiences of traumatic events showed significantly higher risks for the psychosis class, the hallucinatory class, and the intermediate class compared to the normative class. Furthermore there appeared to be a grading in the magnitude of the odds ratios: the odds ratios for the psychosis group were generally higher than those for the hallucinatory class, and the odds ratios for the hallucinatory class were generally higher than those for the intermediate class. Conclusions: The latent class analysis showed that psychosis-like symptoms at the population level could be best explained by four groups that appeared to represent an underlying continuum. (c) 2006 Elsevier B.V. All rights reserved.
LanguageEnglish
Pages101-109
JournalSchizophrenia Research
Volume89
Issue number1-3
DOIs
Publication statusPublished - Jan 2007

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psychosis
comorbidity
experience
Group
event
demographic situation
grading
demographic factors
logistics
regression

Cite this

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title = "The distribution of positive psychosis-like symptoms in the population: A latent class analysis of the National Comorbidity Survey",
abstract = "Objective: Previous research has suggested that psychosis is better described as a continuum rather than a dichotomous entity. This study aimed to describe the distribution of positive psychosis-like symptoms in the general population by means of latent class analysis. Method: Latent class analysis was used to identify homogeneous sub-types of psychosis-like experiences. Multinomial logistic regression models were used to interpret the nature of the latent classes, or groups, by estimating the associations with demographic factors, clinical variables, and experiences of traumatic events. Results: The best fitting latent class model was a four-class solution: a psychosis class, a hallucinatory class, an intermediate class, and a normative class. The associations between the latent classes and the demographic risk factors, clinical variables, and experiences of traumatic events showed significantly higher risks for the psychosis class, the hallucinatory class, and the intermediate class compared to the normative class. Furthermore there appeared to be a grading in the magnitude of the odds ratios: the odds ratios for the psychosis group were generally higher than those for the hallucinatory class, and the odds ratios for the hallucinatory class were generally higher than those for the intermediate class. Conclusions: The latent class analysis showed that psychosis-like symptoms at the population level could be best explained by four groups that appeared to represent an underlying continuum. (c) 2006 Elsevier B.V. All rights reserved.",
author = "M Shevlin and Jamie Murphy and Dorahy, {Martin J.} and Gary Adamson",
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AB - Objective: Previous research has suggested that psychosis is better described as a continuum rather than a dichotomous entity. This study aimed to describe the distribution of positive psychosis-like symptoms in the general population by means of latent class analysis. Method: Latent class analysis was used to identify homogeneous sub-types of psychosis-like experiences. Multinomial logistic regression models were used to interpret the nature of the latent classes, or groups, by estimating the associations with demographic factors, clinical variables, and experiences of traumatic events. Results: The best fitting latent class model was a four-class solution: a psychosis class, a hallucinatory class, an intermediate class, and a normative class. The associations between the latent classes and the demographic risk factors, clinical variables, and experiences of traumatic events showed significantly higher risks for the psychosis class, the hallucinatory class, and the intermediate class compared to the normative class. Furthermore there appeared to be a grading in the magnitude of the odds ratios: the odds ratios for the psychosis group were generally higher than those for the hallucinatory class, and the odds ratios for the hallucinatory class were generally higher than those for the intermediate class. Conclusions: The latent class analysis showed that psychosis-like symptoms at the population level could be best explained by four groups that appeared to represent an underlying continuum. (c) 2006 Elsevier B.V. All rights reserved.

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