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Principal-component analysis of PANSS and SANS - SAPS global ratings in schizophrenic patients

Published online by Cambridge University Press:  16 April 2020

S Dollfus ,
M Petit ,
P Lesieur  and
JF Menard
S Dollfus
Affiliation:
Department of Psychiatry, University of Rouen, CHS du Rouvray, Sotteville-les-Rouen, 76301
M Petit
Affiliation:
Department of Psychiatry, University of Rouen, CHS du Rouvray, Sotteville-les-Rouen, 76301
P Lesieur
Affiliation:
Department of Information and Research, CHS du Rouvray, Sotteville-les-Rouen, 76301
JF Menard
Affiliation:
Department of Biophysics, University of Rouen, Hospital Charles Nicolle, Rouen, France
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Summary

The aim of this study was to test whether a positive and a negative component could be found in broadly defined schizophrenic patients. Therefore, 70 patients either in an exacerbated or in a stabilized phase were selected according to the criteria of at least 1 of the 4 following diagnostic systems: DSM III-R, Schneider, Carpenter, Langfeldt; principal component analyses (PCA) were carried out with the 9 global ratings of the Scales for Assessment of Negative and Positive Symptoms (SANS and SAPS) and with the Positive and Negative Syndrome Scale (PANSS). The PCA of the SANS-SAPS global ratings yielded a 3-factor solution explaining 72.14% of the total variance, depicting a negative, a positive and a disorganization component. The PCA of the PANSS provided a 5-factor solution with a total explained variance of 55.98%. The first 3 factors were similar to those of the SANS-SAPS global rating analysis. The results showed that the positive and negative components described in a homogeneous schizophrenic population could be replicated in a larger and more heterogeneous group of schizophrenic patients. The question regarding the sufficiency of the positive-negative dichotomy was strengthened by the presence of a third disorganization component which explained as much of the variance as the positive component.

Keywords

schizophrenianegative symptomspositive symptomsdisorganizationscalesprincipal component analysis (PCA)
Type
Original article
Information
European Psychiatry , Volume 6 , Issue 5 , 1991 , pp. 251 - 259
Copyright
Copyright © Elsevier, Paris 1991

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