Is there an optimal factor structure of the Positive and Negative Syndrome Scale in patients with first-episode psychosis?

Johannes Langeveld*, Ole A. Andreassen, Bjørn Auestad, Ann Færden, Lars Johan Hauge, Inge Joa, Jan Olav Johannessen, Ingrid Melle, Bjorn Rishovd Rund, Jan Ivar Røssberg, Erik Simonsen, Per Vaglum, Tor Ketil Larsen

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftArtikelForskningpeer review

Abstrakt

The Positive and Negative Syndrome Scale (PANSS) is the most widely used scale to assess a variety of symptoms in patients with schizophrenia and other psychoses. The factor structure of the PANSS has been examined with confirmatory factor analyses in several studies, but not in a well-defined first-episode psychosis sample. The aim of this paper is to examine the statistical fit of five different PANSS models in a first-episode, non-affective psychosis sample. Confirmatory factor analyses were performed on PANSS data (n=588). A main criterion for best fit was defined as the Expected Cross Validation Index (ECVI). No tested model revealed an optimally satisfactory model fit index. The Wallwork/Fortgang five-factor model demonstrated the most optimal psychometric properties. The corresponding subscales of all evaluated five-factor models were strongly intercorrelated. The Wallwork/Fortgang five-factor model was found to be statistically and clinically ideal among patients with first-episode psychosis. Therefore, we recommend this model in forthcoming studies among patients with first-episode psychosis. However, to prevent the loss of clinically valuable information on an item level, we do not recommend removing any items from the original form. Our study also implies that the specific choice of model will not have a substantial effect on outcome results in studies on the course and outcome in first-episode psychosis.

OriginalsprogEngelsk
Sider (fra-til)160-165
Antal sider6
TidsskriftScandinavian Journal of Psychology
Vol/bind54
Udgave nummer2
DOI
StatusUdgivet - 1 apr. 2013

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