Mehdi Rezaee - Department of Psychology, Lorestan University, Khoramabad, Lorestan
Mohammad Reza Ahmadi - Department of Psychiatrist, Behavioral Research Center, Loghman Hospital,
Samira Goodarzi - Department of Clinical Psychology, Shahed University,
Hossein Shahahmadi - Department of Clinical Psychology, Tehran University, Tehran, Iran

Objectives: Hierarchical personality models have potential efficiency to identify specific components of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM‑IV) personality disorders (PDs). The purpose of this study was to investigate to factor structure of personality pathologyas measured by the Diagnostic Assessment of Personality Pathology‑Basic Questionnaire (DAPP‑BQ), and to examine the capacity of the components of the DAP‑BQ hierarchy to predict PDs symptoms. Materials and Methods: Students of Allame Tabatabii and Lorestan University (189 male, 176 female)and psychiatric outpatients of Loghman and Emam Hossein Hospitals (116 male, 159 female) were selected via convenient and voluntary sampling methods. Then completed the DAP‑BQ and answer to Structured Clinical Interview for DSM‑IV Axis II and Composite International Diagnostic Interview.The data were analyzed using multiple regression analysis and principal components analyses with bass‑ackwards method used to investigate the hierarchical structure of the DAP‑BQ. Results: Results showed that Level 5 of the hierarchy enhanced the capacity of the DAP‑BQ for predicting DSM‑IV PD symptoms beyond a four‑factor structure, particularly for borderline PD. Conclusion: It canbe concluded Level 5 represents an important level of analysis for predicting personality pathology, with an additional factor (Need for Approval) adding important information about symptoms of PD. The results from the current study may contribute to the refinement of the psychiatric nosology and assessment of personality pathology.

Diagnostic Assessment of Personality Pathology‑Basic Questionnaire, personality disorders, principal components analyses