Temperament and character influence on depression treatment outcome.
Bipolar disorder
Major depressive disorder
Treatment outcomes
Treatment resistance depression
Journal
Journal of affective disorders
ISSN: 1573-2517
Titre abrégé: J Affect Disord
Pays: Netherlands
ID NLM: 7906073
Informations de publication
Date de publication:
01 06 2019
01 06 2019
Historique:
received:
14
08
2018
revised:
07
03
2019
accepted:
07
04
2019
pubmed:
22
4
2019
medline:
6
2
2020
entrez:
22
4
2019
Statut:
ppublish
Résumé
personality features have been repeatedly associated with depression treatment outcome in Major Depressive Disorder (MDD), however conclusive results are still lacking. Moreover, as for Bipolar Disorder (BD), results are only few and preliminary. the aim of the present study was to perform an exploratory investigation of the influence of personality traits as assessed by the Temperament and Character Inventory (TCI), on principal depression treatment outcomes (non remission, non response and resistance). 743 mood disorders patients (455 MDD (61.24%) and 288 BD (38.76%)) were recruited in the context of 6 European studies. Generalized logit models were performed to test the effects of TCI dimensions on treatment outcomes, considering possible confounders such as age, gender and education. Positive results were controlled for comorbidities (anxiety and substance use disorders) as well. MDD Non-Remitters showed high Harm Avoidance (HA) and Self Transcendence (ST) (p = 0.0004, d = 0.40; p = 0.007, d = 0.36 respectively) and low Persistence (P) and Self Directedness (SD) (p = 0.05; d = 0.18; p = 0.002, d = 0.40, respectively); MDD Non-Responders showed a slightly different profile with high HA and low Reward Dependence (RD) and SD; finally, MDD Resistants showed low RD, P and Cooperativeness (C). In BD patients, only higher HA in non response was observed. the retrospective cross-sectional design, the TCI assessment regardless of the mood state and the small number of bipolar patients represent the main limitations. specific TCI personality traits are associated with depression treatment outcome in MDD patients. The inclusion of such personality traits, together with other socio-demographic and clinical predictors, could ameliorate the accuracy of the prediction models available to date.
Sections du résumé
BACKGROUND
personality features have been repeatedly associated with depression treatment outcome in Major Depressive Disorder (MDD), however conclusive results are still lacking. Moreover, as for Bipolar Disorder (BD), results are only few and preliminary.
AIM
the aim of the present study was to perform an exploratory investigation of the influence of personality traits as assessed by the Temperament and Character Inventory (TCI), on principal depression treatment outcomes (non remission, non response and resistance).
METHODS
743 mood disorders patients (455 MDD (61.24%) and 288 BD (38.76%)) were recruited in the context of 6 European studies. Generalized logit models were performed to test the effects of TCI dimensions on treatment outcomes, considering possible confounders such as age, gender and education. Positive results were controlled for comorbidities (anxiety and substance use disorders) as well.
RESULTS
MDD Non-Remitters showed high Harm Avoidance (HA) and Self Transcendence (ST) (p = 0.0004, d = 0.40; p = 0.007, d = 0.36 respectively) and low Persistence (P) and Self Directedness (SD) (p = 0.05; d = 0.18; p = 0.002, d = 0.40, respectively); MDD Non-Responders showed a slightly different profile with high HA and low Reward Dependence (RD) and SD; finally, MDD Resistants showed low RD, P and Cooperativeness (C). In BD patients, only higher HA in non response was observed.
LIMITATIONS
the retrospective cross-sectional design, the TCI assessment regardless of the mood state and the small number of bipolar patients represent the main limitations.
CONCLUSION
specific TCI personality traits are associated with depression treatment outcome in MDD patients. The inclusion of such personality traits, together with other socio-demographic and clinical predictors, could ameliorate the accuracy of the prediction models available to date.
Identifiants
pubmed: 31005789
pii: S0165-0327(18)31789-0
doi: 10.1016/j.jad.2019.04.031
pii:
doi:
Substances chimiques
Antidepressive Agents
0
Types de publication
Evaluation Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
464-474Informations de copyright
Copyright © 2019 Elsevier B.V. All rights reserved.