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 two large community samples using an item response mixture model. METHOD: An item response mixture model was used to explain the pattern of psychosis-like symptom endorsement. This model incorporated two elements. First, a continuous non-normal latent variable to explain the observed pattern of data. Second, a categorical latent variable to explain the variation in the continuous non-normal latent variable. RESULTS: For both samples, representing broadly and narrowly defined psychosis, the best fitting model was a four-class solution. In both cases, the classes differed quantitatively rather than qualitatively. CONCLUSIONS: The analysis showed that psychosis-like symptoms at the population level could be best explained by four classes that appeared to represent an underlying continuum.
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 two large community samples using an item response mixture model. METHOD: An item response mixture model was used to explain the pattern of psychosis-like symptom endorsement. This model incorporated two elements. First, a continuous non-normal latent variable to explain the observed pattern of data. Second, a categorical latent variable to explain the variation in the continuous non-normal latent variable. RESULTS: For both samples, representing broadly and narrowly defined psychosis, the best fitting model was a four-class solution. In both cases, the classes differed quantitatively rather than qualitatively. CONCLUSIONS: The analysis showed that psychosis-like symptoms at the population level could be best explained by four classes that appeared to represent an underlying continuum.
Authors: N C Stefanis; M Hanssen; N K Smirnis; D A Avramopoulos; I K Evdokimidis; C N Stefanis; H Verdoux; J Van Os Journal: Psychol Med Date: 2002-02 Impact factor: 7.723
Authors: Judith Rietdijk; Marjolein Fokkema; Daniel Stahl; Lucia Valmaggia; Helga K Ising; Sara Dragt; Rianne M C Klaassen; Dorien H Nieman; Rachel Loewy; Pim Cuijpers; Philippe Delespaul; Don H Linszen; Mark van der Gaag Journal: Soc Psychiatry Psychiatr Epidemiol Date: 2013-10-15 Impact factor: 4.328
Authors: E Daneluzzo; P Stratta; S Di Tommaso; R Pacifico; I Riccardi; A Rossi Journal: Soc Psychiatry Psychiatr Epidemiol Date: 2009-03-21 Impact factor: 4.328