TY - JOUR
T1 - Temperament and character traits predict future burden of depression
AU - Rosenström, Tom
AU - Jylhä, Pekka
AU - Robert Cloninger, C.
AU - Hintsanen, Mirka
AU - Elovainio, Marko
AU - Mantere, Outi
AU - Pulkki-Råback, Laura
AU - Riihimäki, Kirsi
AU - Vuorilehto, Maria
AU - Keltikangas-Järvinen, Liisa
AU - Isometsä, Erkki
N1 - Funding Information:
This work was financially supported by the Academy of Finland (L.K.J., Grant no. 258711 ; M.H. , Grant no. 258578 ; and Grants for JoBS and PC-VDS); the Department of Psychiatry at Helsinki University Central Hospital (JoBS and PC-VDS) ; Signe and Ane Gyllenberg Foundation (L.K.J. and M.H.) ; Alli Paasikivi Foundation (M.H.) ; Emil Aaltonen Foundation (M.H.) ; and the Juho Vainio Foundation (L.P.R.) .
PY - 2014/4
Y1 - 2014/4
N2 - Background Personality traits are associated with depressive symptoms and psychiatric disorders. Evidence for their value in predicting accumulation of future dysphoric episodes or clinical depression in long-term follow-up is limited, however. Methods Within a 15-year longitudinal study of a general-population cohort (N=751), depressive symptoms were measured at four time points using Beck's Depression Inventory. In addition, 93 primary care patients with DSM-IV depressive disorders and 151 with bipolar disorder, diagnosed with SCID-I/P interviews, were followed for five and 1.5 years with life-chart methodology, respectively. Generalized linear regression models were used to predict future number of dysphoric episodes and total duration of major depressive episodes. Baseline personality was measured by the Temperament and Character Inventory (TCI). Results In the general-population sample, one s.d. lower Self-directedness predicted 7.6-fold number of future dysphoric episodes; for comparison, one s.d. higher baseline depressive symptoms increased the episode rate 4.5-fold. High Harm-avoidance and low Cooperativeness also implied elevated dysphoria rates. Generally, personality traits were poor predictors of depression for specific time points, and in clinical populations. Low Persistence predicted 7.5% of the variance in the future accumulated depression in bipolar patients, however. Limitations Degree of recall bias in life charts, limitations of statistical power in the clinical samples, and 21-79% sample attrition (corrective imputations were performed). Conclusion TCI predicts future burden of dysphoric episodes in the general population, but is a weak predictor of depression outcome in heterogeneous clinical samples. Measures of personality appear more useful in detecting risk for depression than in clinical prediction.
AB - Background Personality traits are associated with depressive symptoms and psychiatric disorders. Evidence for their value in predicting accumulation of future dysphoric episodes or clinical depression in long-term follow-up is limited, however. Methods Within a 15-year longitudinal study of a general-population cohort (N=751), depressive symptoms were measured at four time points using Beck's Depression Inventory. In addition, 93 primary care patients with DSM-IV depressive disorders and 151 with bipolar disorder, diagnosed with SCID-I/P interviews, were followed for five and 1.5 years with life-chart methodology, respectively. Generalized linear regression models were used to predict future number of dysphoric episodes and total duration of major depressive episodes. Baseline personality was measured by the Temperament and Character Inventory (TCI). Results In the general-population sample, one s.d. lower Self-directedness predicted 7.6-fold number of future dysphoric episodes; for comparison, one s.d. higher baseline depressive symptoms increased the episode rate 4.5-fold. High Harm-avoidance and low Cooperativeness also implied elevated dysphoria rates. Generally, personality traits were poor predictors of depression for specific time points, and in clinical populations. Low Persistence predicted 7.5% of the variance in the future accumulated depression in bipolar patients, however. Limitations Degree of recall bias in life charts, limitations of statistical power in the clinical samples, and 21-79% sample attrition (corrective imputations were performed). Conclusion TCI predicts future burden of dysphoric episodes in the general population, but is a weak predictor of depression outcome in heterogeneous clinical samples. Measures of personality appear more useful in detecting risk for depression than in clinical prediction.
KW - Bipolar disorder
KW - Longitudinal data
KW - Major depressive disorder
KW - Mood disorders
KW - Personality
KW - Prevention
UR - http://www.scopus.com/inward/record.url?scp=84896689308&partnerID=8YFLogxK
U2 - 10.1016/j.jad.2014.01.017
DO - 10.1016/j.jad.2014.01.017
M3 - Article
C2 - 24655778
AN - SCOPUS:84896689308
VL - 158
SP - 139
EP - 147
JO - Journal of Affective Disorders
JF - Journal of Affective Disorders
SN - 0165-0327
ER -