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The Scientific World Journal
Volume 2014, Article ID 964210, 10 pages
Research Article

MMPI-2: Cluster Analysis of Personality Profiles in Perinatal Depression—Preliminary Evidence

1Department of Neurology and Psychiatry, Policlinico Umberto I, Sapienza University of Rome, Viale dell’Università 30, 00185 Rome, Italy
2Department of Social and Developmental Psychology, Sapienza University of Rome, Via dei Marsi 78, 00185 Rome, Italy

Received 28 July 2014; Accepted 10 November 2014; Published 9 December 2014

Academic Editor: Manuel F. Casanova

Copyright © 2014 Valentina Meuti et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. To assess personality characteristics of women who develop perinatal depression. Methods. The study started with a screening of a sample of 453 women in their third trimester of pregnancy, to which was administered a survey data form, the Edinburgh Postnatal Depression Scale (EPDS) and the Minnesota Multiphasic Personality Inventory 2 (MMPI-2). A clinical group of subjects with perinatal depression (PND, 55 subjects) was selected; clinical and validity scales of MMPI-2 were used as predictors in hierarchical cluster analysis carried out. Results. The analysis identified three clusters of personality profile: two “clinical” clusters (1 and 3) and an “apparently common” one (cluster 2). The first cluster (39.5%) collects structures of personality with prevalent obsessive or dependent functioning tending to develop a “psychasthenic” depression; the third cluster (13.95%) includes women with prevalent borderline functioning tending to develop “dysphoric” depression; the second cluster (46.5%) shows a normal profile with a “defensive” attitude, probably due to the presence of defense mechanisms or to the fear of stigma. Conclusion. Characteristics of personality have a key role in clinical manifestations of perinatal depression; it is important to detect them to identify mothers at risk and to plan targeted therapeutic interventions.