Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients.
cluster analyses
cognitive functioning
latent class cluster analysis
psychiatric inpatients
two-step cluster analysis
Journal
Frontiers in psychology
ISSN: 1664-1078
Titre abrégé: Front Psychol
Pays: Switzerland
ID NLM: 101550902
Informations de publication
Date de publication:
2020
2020
Historique:
received:
30
11
2019
accepted:
28
04
2020
entrez:
27
6
2020
pubmed:
27
6
2020
medline:
27
6
2020
Statut:
epublish
Résumé
The heterogeneity of cognitive profiles among psychiatric patients has been reported to carry significant clinical information. However, how to best characterize such cognitive heterogeneity is still a matter of debate. Despite being well suited for clinical data, cluster analysis techniques, like the Two-Step and the Latent Class, received little to no attention in the literature. The present study aimed to test the validity of the cluster solutions obtained with Two-Step and Latent Class cluster analysis on the cognitive profile of a cross-diagnostic sample of 387 psychiatric inpatients. Two-Step and Latent Class cluster analysis produced similar and reliable solutions. The overall results reported that it is possible to group all psychiatric inpatients into Low and High Cognitive Profiles, with a higher degree of cognitive heterogeneity in schizophrenia and bipolar disorder patients than in depressive disorders and personality disorder patients.
Identifiants
pubmed: 32587546
doi: 10.3389/fpsyg.2020.01085
pmc: PMC7299079
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1085Informations de copyright
Copyright © 2020 Benassi, Garofalo, Ambrosini, Sant’Angelo, Raggini, De Paoli, Ravani, Giovagnoli, Orsoni and Piraccini.
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