The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Niklas Ortelbach - , Freie Universität (FU) Berlin (Autor:in)
  • Jonas Rote - , Charité – Universitätsmedizin Berlin, Klinik und Poliklinik für Psychiatrie und Psychotherapie (Autor:in)
  • Alice Mai Ly Dingelstadt - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Anna Stolzenburg - , Universitätsklinikum Ruppin-Brandenburg (Autor:in)
  • Cornelia Koenig - , Universitätsklinikum Ruppin-Brandenburg (Autor:in)
  • Grace O'Malley - , Universitätsklinikum Ruppin-Brandenburg (Autor:in)
  • Esther Quinlivan - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Jana Fiebig - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Steffi Pfeiffer - , Klinik und Poliklinik für Psychiatrie und Psychotherapie, Poliklinik für Zahnärztliche Prothetik (Autor:in)
  • Barbara König - , BIPOLAR Zentrum Wiener Neustadt (Autor:in)
  • Christian Simhandl - , BIPOLAR Zentrum Wiener Neustadt (Autor:in)
  • Michael Bauer - , Klinik und Poliklinik für Psychiatrie und Psychotherapie, Poliklinik für Zahnärztliche Prothetik (Autor:in)
  • Andrea Pfennig - , Klinik und Poliklinik für Psychiatrie und Psychotherapie, Poliklinik für Zahnärztliche Prothetik (Autor:in)
  • Thomas J Stamm - , Universitätsklinikum Ruppin-Brandenburg (Autor:in)

Abstract

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 (R2 = 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.

Details

OriginalspracheEnglisch
Aufsatznummer1
FachzeitschriftInternational journal of bipolar disorders
Jahrgang10
Ausgabenummer1
PublikationsstatusVeröffentlicht - 18 Jan. 2022
Peer-Review-StatusJa

Externe IDs

PubMedCentral PMC8766615
Scopus 85123014904
ORCID /0000-0002-3415-5583/work/150329746
ORCID /0000-0002-2666-859X/work/150329165

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