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Two-step Cluster Analysis Application to a Sample of Psychiatric Inpatients at Psychiatric Service of Diagnosis and Care

Published online by Cambridge University Press:  23 March 2020

F. Ambrosini
Affiliation:
Department of Psychology, University of Bologna, Bologna, Italy
M. Benassi
Affiliation:
Department of Psychology, University of Bologna, Bologna, Italy
R.P. Sant’Angelo
Affiliation:
U.O. Servizio Psichiatrico di Diagnosi e Cura, Istituto AUSL della Romagna - Cesena, Cesena, Italy
R. Raggini
Affiliation:
U.O. Servizio Psichiatrico di Diagnosi e Cura, Istituto AUSL della Romagna - Cesena, Cesena, Italy
L. Mandolesi
Affiliation:
Department of Psychology, University of Bologna, Bologna, Italy
G. Piraccini
Affiliation:
U.O. Servizio Psichiatrico di Diagnosi e Cura, Istituto AUSL della Romagna - Cesena, Cesena, Italy

Abstract

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Introduction

Recent findings demonstrated significant overlaps among major psychiatric disorders on multiple neurocognitive domains. However, it is not clear which are the cognitive functions that contribute to this phenomenon.

Objectives

To find the optimal clustering solution using the two-step cluster analysis on a sample of psychiatric patients.

Aims

To classify into subgroups a cross-diagnostic sample of psychiatric inpatients on the basis of their neurocognitive profiles.

Methods

Seventy-one patients with psychotic, bipolar, depressive and personality disorders hospitalised at Psychiatric Diagnosis and Care Service of Bufalini Hospital of Cesena participated in the study. The symptomatology was assessed using Health of the Nation Outcome Scales-Roma and Brief Psychiatric Rating Scale. Cognitive functions were evaluated using Tower of London, Modified Wisconsin Card Sorting Test, Judgment and Verbal Abstract Tasks test, Raven matrices, Attentional Matrices, Stroop Test and Mini Mental State Examination. Two-step cluster analysis was conducted using the standardized scores of each neurocognitive test.

Results

Two groups were obtained:– group 1, with good cognitive performances;– group 2, with almost all subjects having impaired cognitive performances.

Executive functions and attention are the major determinants of the cluster solution. The clusters did not differ on socio-demographic correlates. Different diagnoses were equally distributed amongst the clusters.

Conclusions

Two-step cluster analysis was useful in identifying subgroups of psychiatric inpatients with different cognitive functioning, overcoming other cluster techniques limitations. According to former literature, these results confirm a continuum of severity in cognitive impairment across different psychiatric disorders.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

Type
e-poster walk: Classification of mental disorders and cultural psychiatry
Copyright
Copyright © European Psychiatric Association 2017
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