The role of affective instability and impulsivity in predicting future BPD features.

Models of borderline personality disorder (BPD) suggest that extreme levels of affective instability/emotional dysregulation, impulsivity, or the combination of these two traits account for the symptoms characteristic of BPD. The present study utilized longitudinal data to evaluate the ability of Personality Assessment Inventory-Borderline Features (PAI-BOR; Morey, 1991) subscale scores to predict BPD features two years later as a test of these models of BPD. Participants were 156 male and 194 female young adults who completed the PAI-BOR at age 18 and again two years later. Three models were compared: (a) Wave 1 affective instability scores predicting Wave 2 BPD features (AI model); (b) Wave 1 self-harm/impulsivity scores predicting Wave 2 BPD features (IMP model); and (c) both Wave 1 affective instability and self-harm/impulsivity scores predicting Wave 2 BPD features (AI-IMP model), all controlling for stabilities and within-time covariances. Results indicated that the AI model provided the best fit to the data, and improved model fit over a baseline stabilities model and the other models tested. These results are consistent with Linehan's theory (1993) that emotional dysregulation drives the other BPD symptoms.