Factor structure and external validity of the PANSS revisited

Abstract

Considerable controversy exists concerning the positive and negative syndrome scale (PANSS), one of the most widely used instruments in schizophrenia research. In this article we revisited the factor structure and external validity of the PANSS in a sample of 500 participants with DSM IV diagnoses of schizophrenia. We found that a model with six latent factors provided a relatively good fit, considered adequate by two rules of thumb. Five factors corresponded closely to those typically derived in other studies: Negative, Positive, Excited/Activation, Anxious-Depressed/Dysphoric, and Disorganized/Autistic preoccupation. The sixth factor seemed to have face validity and was labeled Withdrawn. With the exception of Anxious-Depressed/Dysphoric, Cronbach's Alpha ranged from 0.70 to 0.85 suggesting an acceptable internal consistency. External validity was studied through correlations with socio-demographic variables, DSM IV (subtype) diagnoses, clinical characteristics, and drug use. The many significant correlations suggested that the six PANSS scales measure meaningful aspects of schizophrenia. Furthermore, the pattern of correlations varied, providing evidence that the scales assessed partly different aspects of the disease. Our analyses also suggested that some of the controversy about the PANSS can possibly be attributed to methodological factors where the substantial cross-loadings of some PANSS items may play an important role.

Introduction

As seems the case for other common disorders such as obesity (Rosmond, 2003), inflammatory bowel disease (Duerr, 2002), and asthma (Hoffjan and Ober, 2002), schizophrenia could be a group of related conditions sharing clinical features but that are the outcome of in part distinct underlying causes. These subtypes may be distinguishable from each other with respect to prognosis, course, or response to treatment. Their identification is therefore crucial from a clinical perspective.

One of the first diagnostic refinements involved the subdivision of schizophrenia into positive and negative syndromes (Crow, 1980, Strauss et al., 1974). Delusions, hallucinations, and bizarre behavior characterize Positive schizophrenia, while blunted affect, avolition, and attentional problems are typical features of negative schizophrenia. To investigate the positive–negative distinction empirically, measurement instruments such as the Scale for the Assessment of Negative Symptoms (SANS) and the Scale for the Assessment of Positive Symptoms (SAPS) were developed (Andreasen, 1983, Andreasen, 1984). However, empirical analyses of these scales showed that positive symptoms can be further subdivided into psychotic and disorganized symptoms (Andreasen et al., 1995), suggesting that the positive–negative distinction does not fully capture the complex structure of schizophrenic symptoms.

The SANS and SAPS were designed to measure Positive and Negative syndromes. Because of the a priori selection of symptoms, these instruments may be limited in their potential to identify schizophrenia subtypes. To allow a more extensive assessment of schizophrenia symptoms, Kay et al. (Kay et al., 1987) used the Brief Psychiatric Rating Scale (Overall and Gorham, 1962) and the Psychopathology Rating Schedule (Singh and Kay, 1979) to develop the Positive and Negative Syndrome Scale (PANSS, (Kay et al., 1987). Many of the 30 items of the PANSS are not directly related to the Positive and Negative syndromes. To unravel the structure of the PANSS items, a considerable number of factor analyses have been performed. In these studies, the number of underlying factors derived varied, as were the PANSS items included in scales presumably measuring the same subtype. In an attempt to reconcile the different research findings, White and colleagues (White et al., 1997) fitted 20 previously proposed models to data from a sample of 1233 schizophrenics. They concluded that none of these models fitted the data adequately. The authors then derived a new model by performing exploratory factor analysis in one half of the data and cross-validating the derived model in the other half of the data. The five factors from this “pentagonal” model were labeled: Positive, Negative, Dysphoric mood, Activation, and Autistic preoccupation. It is this five factor model that is presently proposed in the manual for the PANSS (Kay et al., 2000).

The study by White and colleagues did not, however, end the controversy surrounding the factor structure of the PANSS (Emsley et al., 2003, Lancon et al., 1999, Lancon et al., 2000, Fitzgerald et al., 2001, Lykouras et al., 2000, Mass et al., 2000, Wolthaus et al., 2000). Critics argued that five factors may not be enough to capture the structure of the PANSS items (Emsley et al., 2003), that the proposed pentagonal model gives an inadequate goodness of fit in other samples (Fitzgerald et al., 2001), and that the external validity of the proposed scales is modest (Lykouras et al., 2000). Particularly because the PANSS is widely used in psychiatric research, more research is required to ascertain the optimal method for measuring PANSS symptom dimensions in research and clinical settings (Fitzgerald et al., 2001).

The aim of the present study is to revisit the factor structure and external validity of the PANSS. Our approach deviates from some of the previous publications in three ways. First, instead of choosing either exploratory (EFA) or confirmatory factor analysis (CFA), we will use a mixture of both. For example, as in CFA, we use fit indices to evaluate the factor models. More akin to EFA, however, we avoided fitting very restrictive models based on previous studies that may produce poor fit indices because many non-zero (cross) loadings are not estimated. Second, in addition to the number of extracted factors and model fit, for selecting the best factor solution we also considered how well the items measured the factors. For example, if one or more scales derived from a factor solution have poor internal consistency, it may be better to select another factor solution that results in scales with better measurement properties. Third, instead of confining ourselves to studying the factor structure and measurement properties of the derived scales, we also explored the external validity. This was done by studying the relation of the PANSS scales with socio-demographic variables, DSM IV diagnoses, clinical characteristics, and drug use. These analyses are important to examine whether the scales measure clinically meaningful but partly different aspects of Schizophrenia.