The five-factor model of the Positive and Negative Syndrome Scale I: confirmatory factor analysis fails to confirm 25 published five-factor solutions

Objective The aim of this study was to test the goodness-of-fit of all previously published five-factor models of the Positive and Negative Syndrome Scale (PANSS). Methods We used confirmatory factor analysis (CFA) with a large data set (N = 5769). Results The different subsamples were tested for heterogeneity and were found to be homogeneous. This indicates that despite variability in age, sex, duration of illness, admission status, etc., in the different subsamples, the structure of symptoms is the same for all patients with schizophrenia. Although previous research has shown that a five-factor model fits the data better than models with three or four factors, no satisfactory fit for any of the 25 published five-factor models was found with CFA. Conclusions Variability in age, sex, admission status and duration of illness has no substantial effect on the structure of symptoms in schizophrenia. The lack of fit can be caused by ill-defined items that aim to measure several properties in a single rating. Another explanation is that well-defined symptoms can have two or more causes. Then a double or triple loading item should not be discarded, but included because the complexity of symptoms in schizophrenia is represented by these multiple loadings. Such a complex model not only needs confirmation by CFA, but also has to be proven stable. A 10-fold cross-validation is suggested to develop a complex and stable model.