Dimensional personality traits and the prediction of DSM-IV personality disorder symptom counts in a nonclinical sample

The third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III; APA, 1980) set forth a categorical system of personality psychopathology that is composed of discrete personality disorders (PDs), each with a distinct set of diagnostic criteria. Although this system is widely accepted and highly influential, alternative dimensional approaches to capturing personality psychopathology have been proposed. Three dimensional models of personality have garnered particular attention-the Five-Factor Model (FFM; Costa & McCrae, 1992), the Seven-Factor Psychobiological Model of Temperament and Character (Seven-Factor Model; Cloninger, Svrakic, & Przybeck, 1993); and the 18-factor model of personality pathology (18-factor model; Livesley, 1986). Although the personality traits from each of these models has been examined in relation to the ten personality disorders in the DSM-IV, no study has examined the comparative and incremental validity of these models in predicting PD symptoms for these ten disorders. Using self-report instruments that measure these models and the ten DSM-IV PDs, correlation and linear regression analyses indicate that traits from all three models had statistically significant associations with PD symptom counts. Hierarchical regressions revealed that the 18-factor model had incremental predictive validity over the FFM and Seven-Fac-tor Model in predicting symptom counts for all ten DSM-IV PDs. The FFM had incremental predictive validity over the Seven-Factor Model model for all ten disorders and the Seven-Factor was able to add incremental predictive validity over the 18-factor model for five of the ten PDs and for eight of the ten disorders relative to the FFM.