Personality in patients with affective disorders and their relatives

Autor: D. van Calker, H. Hecht, D. von Zerssen, Mathias Berger
Rok vydání: 1998
Předmět:
Zdroj: Journal of Affective Disorders. 51:33-43
ISSN: 0165-0327
DOI: 10.1016/s0165-0327(98)00154-2
Popis: Background: In studies of both patients and high-risk subjects, particular patterns of personality have been found to be associated with affective disorders. Neuroticism and features of the melancholic type of personality seem to be risk factors for depression while premorbid features of the manic type of personality predominate in patients with more manic than depressive episodes. While neuroticism prevails in the majority of mental disorders, the `affective' personality variants appear to be more specifically associated with affective disorders. Methods: Personality features were investigated in 122 recovered patients with affective disorders, 58 first-degree relatives (high-risk subjects (HR)) and in the respective control groups (n=48; n=29). Patients were subdivided into: unipolar depression (melancholic subtype); bipolar II; bipolar I with more depressive episodes and bipolar I with more manic episodes. Personality measures were based on the Biographical Personality Interview (BPI) and the Munich Personality Test (MPT). Results: The melancholic personality type (BPI) decreased from the unipolar depressives to the mainly manic group, while features of the manic type increased. MPT scores failed to discriminate between subgroups of patients. HR were significantly more introverted and had a stronger orientation towards social norms than controls according to the MPT, and showed a tendency towards the melancholic type according to the BPI. Limitations: The sizes of some groups or subgroups are relatively small. Therefore, they have to be enlarged in the continuation of the study so as to increase the power of the statistical tests and thus to ascertain the robustness of the results. Conclusion: Features of the typus melancholicus seem to be a risk factor for depression. The identification of highly predictive risk factors provides an opportunity for the development of prevention programms.
Databáze: OpenAIRE