Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients

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 t...

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Autores principales: Benassi, Mariagrazia, Garofalo, Sara, Ambrosini, Federica, Sant’Angelo, Rosa Patrizia, Raggini, Roberta, De Paoli, Giovanni, Ravani, Claudio, Giovagnoli, Sara, Orsoni, Matteo, Piraccini, Giovanni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Psychology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7299079/
https://www.ncbi.nlm.nih.gov/pubmed/32587546
http://dx.doi.org/10.3389/fpsyg.2020.01085
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author Benassi, Mariagrazia
Garofalo, Sara
Ambrosini, Federica
Sant’Angelo, Rosa Patrizia
Raggini, Roberta
De Paoli, Giovanni
Ravani, Claudio
Giovagnoli, Sara
Orsoni, Matteo
Piraccini, Giovanni
author_facet Benassi, Mariagrazia
Garofalo, Sara
Ambrosini, Federica
Sant’Angelo, Rosa Patrizia
Raggini, Roberta
De Paoli, Giovanni
Ravani, Claudio
Giovagnoli, Sara
Orsoni, Matteo
Piraccini, Giovanni
author_sort Benassi, Mariagrazia
collection PubMed
description 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.
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spelling pubmed-72990792020-06-24 Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients Benassi, Mariagrazia Garofalo, Sara Ambrosini, Federica Sant’Angelo, Rosa Patrizia Raggini, Roberta De Paoli, Giovanni Ravani, Claudio Giovagnoli, Sara Orsoni, Matteo Piraccini, Giovanni Front Psychol Psychology 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. Frontiers Media S.A. 2020-06-10 /pmc/articles/PMC7299079/ /pubmed/32587546 http://dx.doi.org/10.3389/fpsyg.2020.01085 Text en Copyright © 2020 Benassi, Garofalo, Ambrosini, Sant’Angelo, Raggini, De Paoli, Ravani, Giovagnoli, Orsoni and Piraccini. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Benassi, Mariagrazia
Garofalo, Sara
Ambrosini, Federica
Sant’Angelo, Rosa Patrizia
Raggini, Roberta
De Paoli, Giovanni
Ravani, Claudio
Giovagnoli, Sara
Orsoni, Matteo
Piraccini, Giovanni
Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients
title Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients
title_full Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients
title_fullStr Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients
title_full_unstemmed Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients
title_short Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients
title_sort using two-step cluster analysis and latent class cluster analysis to classify the cognitive heterogeneity of cross-diagnostic psychiatric inpatients
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7299079/
https://www.ncbi.nlm.nih.gov/pubmed/32587546
http://dx.doi.org/10.3389/fpsyg.2020.01085
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