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The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity
BACKGROUND: Using a personality typing approach, we investigated the relationship between personality profiles and the prediction of longterm illness severity in patients with bipolar disorder (BD). While previous research suggests associations between BD and traits from the NEO-FFI profiles, the cu...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8766615/ https://www.ncbi.nlm.nih.gov/pubmed/35041119 http://dx.doi.org/10.1186/s40345-021-00248-y |
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author | Ortelbach, Niklas Rote, Jonas Dingelstadt, Alice Mai Ly Stolzenburg, Anna Koenig, Cornelia O’Malley, Grace Quinlivan, Esther Fiebig, Jana Pfeiffer, Steffi König, Barbara Simhandl, Christian Bauer, Michael Pfennig, Andrea Stamm, Thomas J. |
author_facet | Ortelbach, Niklas Rote, Jonas Dingelstadt, Alice Mai Ly Stolzenburg, Anna Koenig, Cornelia O’Malley, Grace Quinlivan, Esther Fiebig, Jana Pfeiffer, Steffi König, Barbara Simhandl, Christian Bauer, Michael Pfennig, Andrea Stamm, Thomas J. |
author_sort | Ortelbach, Niklas |
collection | PubMed |
description | BACKGROUND: Using a personality typing approach, we investigated the relationship between personality profiles and the prediction of longterm illness severity in patients with bipolar disorder (BD). While previous research suggests associations between BD and traits from the NEO-FFI profiles, the current study firstly aimed to identify latent classes of NEO-FFI profiles, and, secondly, to examine their impact on the longterm prognosis of BD. METHODS: Based on the NEO-FFI profiles of 134 euthymic patients diagnosed with BD (64.2% female, mean age = 44.3 years), successive latent profile analyses were conducted. Subsequently, a subsample (n = 80) was examined prospectively by performing multiple regression analysis of the latent classes to evaluate the longitudinal course of the disease (mean: 54.7 weeks) measured using a modified Morbidity Index. RESULTS: The latent profile analyses suggested a 3-class model typifying in a resilient (n = 68, 51%), vulnerable (n = 55, 41%) and highly vulnerable (n = 11, 8%) class. In the regression analysis, higher vulnerability predicted a higher longterm Morbidity Index (R(2) = 0.28). CONCLUSIONS: Subgroups of patients with BD share a number of discrete personality features and their illness is characterized by a similar clinical course. This knowledge is valuable in a variety of clinical contexts including early detection, intervention planning and treatment process. |
format | Online Article Text |
id | pubmed-8766615 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-87666152022-02-02 The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity Ortelbach, Niklas Rote, Jonas Dingelstadt, Alice Mai Ly Stolzenburg, Anna Koenig, Cornelia O’Malley, Grace Quinlivan, Esther Fiebig, Jana Pfeiffer, Steffi König, Barbara Simhandl, Christian Bauer, Michael Pfennig, Andrea Stamm, Thomas J. Int J Bipolar Disord Research BACKGROUND: Using a personality typing approach, we investigated the relationship between personality profiles and the prediction of longterm illness severity in patients with bipolar disorder (BD). While previous research suggests associations between BD and traits from the NEO-FFI profiles, the current study firstly aimed to identify latent classes of NEO-FFI profiles, and, secondly, to examine their impact on the longterm prognosis of BD. METHODS: Based on the NEO-FFI profiles of 134 euthymic patients diagnosed with BD (64.2% female, mean age = 44.3 years), successive latent profile analyses were conducted. Subsequently, a subsample (n = 80) was examined prospectively by performing multiple regression analysis of the latent classes to evaluate the longitudinal course of the disease (mean: 54.7 weeks) measured using a modified Morbidity Index. RESULTS: The latent profile analyses suggested a 3-class model typifying in a resilient (n = 68, 51%), vulnerable (n = 55, 41%) and highly vulnerable (n = 11, 8%) class. In the regression analysis, higher vulnerability predicted a higher longterm Morbidity Index (R(2) = 0.28). CONCLUSIONS: Subgroups of patients with BD share a number of discrete personality features and their illness is characterized by a similar clinical course. This knowledge is valuable in a variety of clinical contexts including early detection, intervention planning and treatment process. Springer Berlin Heidelberg 2022-01-18 /pmc/articles/PMC8766615/ /pubmed/35041119 http://dx.doi.org/10.1186/s40345-021-00248-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Ortelbach, Niklas Rote, Jonas Dingelstadt, Alice Mai Ly Stolzenburg, Anna Koenig, Cornelia O’Malley, Grace Quinlivan, Esther Fiebig, Jana Pfeiffer, Steffi König, Barbara Simhandl, Christian Bauer, Michael Pfennig, Andrea Stamm, Thomas J. The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity |
title | The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity |
title_full | The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity |
title_fullStr | The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity |
title_full_unstemmed | The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity |
title_short | The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity |
title_sort | big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8766615/ https://www.ncbi.nlm.nih.gov/pubmed/35041119 http://dx.doi.org/10.1186/s40345-021-00248-y |
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