Temperament and character traits predict future burden of depression

Tom Rosenström, Pekka Jylhä, C. Robert Cloninger, Mirka Hintsanen, Marko Elovainio, Outi Mantere, Laura Pulkki-Råback, Kirsi Riihimäki, Maria Vuorilehto, Liisa Keltikangas-Järvinen, Erkki Isometsä

    Research output: Contribution to journalArticlepeer-review

    39 Scopus citations


    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.

    Original languageEnglish
    Pages (from-to)139-147
    Number of pages9
    JournalJournal of affective disorders
    StatePublished - Apr 2014


    • Bipolar disorder
    • Longitudinal data
    • Major depressive disorder
    • Mood disorders
    • Personality
    • Prevention


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