Klaas J Wardenaar 1 , Henk Jan Conradi , Elisabeth H Bos , Peter de Jonge Show Affiliations »
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OBJECTIVE: Effects of depression treatment are obscured by heterogeneity among patients. Personality types could be one source of heterogeneity that explains variability in treatment response. Clinically meaningful variations in personality patterns could be captured with data-driven subgroups. The aim of this study was to identify such personality types and to explore their predictive value for treatment efficacy. METHOD: Participants (N = 146) in the current exploratory study came from a randomized controlled trial in primary care depressed patients, conducted between January 1998 and June 2003 , comparing different treatments. All participants were diagnosed with a major depressive disorder (MDD) according to the DSM-IV . Primary (care as usual [CAU] or CAU plus a psychoeducational prevention program [PEP]) and specialized (CAU + PEP + psychiatric consultation or cognitive-behavioral therapy ) treatment were compared. Personality was assessed with the Neuroticism-Extraversion-Openness Five-Factor Inventory (NEO-FFI). Personality classes were identified with latent profile analysis (LPA). During 1 year, weekly depression ratings were obtained by trimonthly assessment with the Composite International Diagnostic Interview. Mixed models were used to analyze the effects of personality on treatment efficacy. RESULTS: A 2-class LPA solution fit best to the NEO-FFI data: Class 1 (vulnerable, n = 94) was characterized by high neuroticism, low extraversion, and low conscientiousness, and Class 2 (resilient, n = 52) by medium neuroticism and extraversion and higher agreeableness and conscientiousness. Recovery was quicker in the resilient class (class × time: P < .001). Importantly, specialized treatment had added value only in the vulnerable class, in which it was associated with quicker recovery than primary treatment (class × time × treatment: P < .001). CONCLUSIONS: Personality profile may predict whether specialized clinical efforts have added value, showing potential implications for planning of treatments. © Copyright 2014 Physicians Postgraduate Press, Inc.
RCT Entities: Population
Interventions
Outcomes
OBJECTIVE: Effects of depression treatment are obscured by heterogeneity among patients . Personality types could be one source of heterogeneity that explains variability in treatment response. Clinically meaningful variations in personality patterns could be captured with data-driven subgroups. The aim of this study was to identify such personality types and to explore their predictive value for treatment efficacy. METHOD: Participants (N = 146) in the current exploratory study came from a randomized controlled trial in primary care depressed patients , conducted between January 1998 and June 2003, comparing different treatments. All participants were diagnosed with a major depressive disorder (MDD ) according to the DSM-IV. Primary (care as usual [CAU] or CAU plus a psychoeducational prevention program [PEP]) and specialized (CAU + PEP + psychiatric consultation or cognitive-behavioral therapy) treatment were compared. Personality was assessed with the Neuroticism-Extraversion-Openness Five-Factor Inventory (NEO-FFI). Personality classes were identified with latent profile analysis (LPA ). During 1 year, weekly depression ratings were obtained by trimonthly assessment with the Composite International Diagnostic Interview. Mixed models were used to analyze the effects of personality on treatment efficacy. RESULTS: A 2-class LPA solution fit best to the NEO-FFI data: Class 1 (vulnerable, n = 94) was characterized by high neuroticism, low extraversion, and low conscientiousness, and Class 2 (resilient, n = 52) by medium neuroticism and extraversion and higher agreeableness and conscientiousness. Recovery was quicker in the resilient class (class × time: P < .001). Importantly, specialized treatment had added value only in the vulnerable class, in which it was associated with quicker recovery than primary treatment (class × time × treatment: P < .001). CONCLUSIONS: Personality profile may predict whether specialized clinical efforts have added value, showing potential implications for planning of treatments. © Copyright 2014 Physicians Postgraduate Press, Inc.
Entities: Chemical
Disease
Species
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Year: 2014
PMID： 25295434 DOI： 10.4088/JCP.13m08855
Source DB: PubMed Journal: J Clin Psychiatry ISSN： 0160-6689 Impact factor: 4.384