Comprehensive Summary
This study compared the Alternative Model for Personality Disorders (AMPD) and Object Relations Theory (ORT) using neural networks to see how well each identifies personality pathology. A total of 647 participants, including non-clinical students and psychiatric inpatients, completed standardized self-reports and clinical interviews that were analyzed with neural network models. Both systems reliably distinguished clinical from non-clinical groups, with borderline personality disorder patients scoring the highest across the measures. The models showed an overall accuracy above 65 percent, with AMPD performing slightly better than ORT. The findings highlighted a strong overlap between the two frameworks and that each contributed unique strengths to personality disorder assessment.
Outcomes and Implications
This research is important because it validates two complementary approaches to understanding personality disorders, which are both alternative models to the traditional DSM categories. The AMPD offered stronger predictive accuracy, while ORT provided deeper insights into identity and aggression, which are especially relevant for borderline personality disorder. Using the two together can support earlier detection, more personalized treatment planning, and better monitoring of therapeutic progress. Since this work was conducted in a non-Western setting, it demonstrates that these models have global clinical relevance.