Affective temperaments as clinical indicators in major depressive disorder: Associations with psychiatric state and...

Major depressive disorder (MDD) is a heterogeneous illness. Affective temperaments, stable traits underlying mood disorders, may contribute to this variability. However, prior studies were limited by small samples, non-standardized assessments, and cutoff scores for dominant affective temperaments derived solely from patient samples. This study aimed to establish cutoff points for dominant affective temperaments in both patients and the general population, and to investigate their impact on clinical characteristics.

Outpatient data from individuals aged 18-49 years diagnosed with MDD was retrospectively reviewed. Participants completed questionnaires assessing affective temperaments, depressive and anxiety symptoms, seasonality, alcohol consumption, hypomanic symptoms, and suicidal ideation. To establish cutoff scores, 1000 adults from the general population additionally completed the affective temperaments survey. Multiple linear regression analyses were performed to investigate the influence of affective temperaments on clinical characteristics.

Dominant depressive and irritable temperaments were consistently associated with greater severity of depressive symptoms and suicidal ideation, whereas cyclothymic temperament was additionally related to depressive symptom severity. Dominant depressive, irritable, and cyclothymic temperaments were significantly associated with increased anxiety symptoms, whereas all temperaments except the depressive type were associated with greater seasonality. Furthermore, dominant depressive, hyperthymic, and anxious temperaments were associated with problematic alcohol consumption, whereas cyclothymic, hyperthymic, and irritable temperaments were associated with a greater likelihood of bipolar spectrum features.

Affective temperaments demonstrated significant associations with psychiatric state and trait characteristics. These findings suggest that temperament profiles may serve as clinical indicators for identifying MDD subtypes and guiding more personalized treatment approaches.