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Zuckerman–Kuhlman–Aluja Personality Questionnaire as a predictor of MCMI‐III personality disorder scales: The role of facets
Author(s) -
Aluja Anton,
Blanch Angel,
García Luis F.,
García Oscar,
Escorial Sergio
Publication year - 2012
Publication title -
personality and mental health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.193
H-Index - 22
eISSN - 1932-863X
pISSN - 1932-8621
DOI - 10.1002/pmh.1185
Subject(s) - psychology , neuroticism , sensation seeking , millon clinical multiaxial inventory , extraversion and introversion , personality , personality assessment inventory , clinical psychology , big five personality traits , population , social psychology , personality disorders , demography , sociology
This research was planned to assess the predictive power of dimensions and facets of the Zuckerman–Kuhlman–Aluja Personality Questionnaire in relation to the Millon Clinical Multiaxial Inventory III 10 personality disorder (PD) scales in healthy subjects. The sample was composed of 529 subjects from the general population. The average age was 44.51 (standard deviation: 18.27; range 18–85) for men and 43.94 (standard deviation: 18.01; range 18–83) for women. Five factors emerged from principal component analyses. Alpha reliabilities were acceptable for the two questionnaires. Neuroticism correlated with most PD scales. Aggressiveness and sensation seeking correlated with antisocial PD; extraversion (negative) and neuroticism (positive) correlated with several PDs such as avoidant and dependent. The facets presented a similar pattern of correlations with the PD dimensions with different values and statistical power. Sensation seeking and aggression facets were strongly related with antisocial and obsessive–compulsive PDs (in negative). The personality contribution to explain the PD scales was studied by a multiple linear stepwise regression analysis. The facets explained the PD proportion of variance a little better than the dimensions. The relevance of Zuckerman–Kuhlman–Aluja Personality Questionnaire facets in the predictions of PDs is further discussed. Copyright © 2012 John Wiley & Sons, Ltd.