AI-Based Profiling of Personality Disorder Traits Associated with Chronic Somatic Symptoms

Abstract

This study aimed to identify and model personality disorder–related trait profiles associated with the severity of chronic somatic symptoms using artificial intelligence–based analytical approaches. A cross-sectional observational design was employed with an adult sample recruited in Hungary. Participants completed standardized self-report measures assessing chronic somatic symptom severity, dimensional personality disorder traits, and psychological distress variables. Data were collected electronically following informed consent and ethical approval. Multiple supervised machine learning models, including regularized regression and ensemble-based algorithms, were trained to predict somatic symptom severity from personality trait dimensions while controlling for demographic and psychological covariates. Model performance was evaluated using cross-validation procedures, and explainable AI techniques were applied to determine the relative importance and direction of trait contributions. Ensemble machine learning models demonstrated superior predictive performance compared with linear approaches, indicating non-linear and interactive associations between personality traits and chronic somatic symptom severity. Negative affectivity emerged as the strongest predictor, followed by detachment, with both traits showing robust positive associations with symptom severity. Disinhibition and psychoticism contributed moderately, while antagonism exhibited a smaller but significant effect. Personality disorder traits provided substantial incremental explanatory value beyond anxiety and depressive symptoms, accounting for additional variance in somatic symptom severity. Explainability analyses confirmed the dominance of internalizing and emotion-related traits in the AI-derived personality profiles associated with higher symptom burden. The findings indicate that chronic somatic symptoms are strongly linked to specific configurations of maladaptive personality traits, particularly negative affectivity and detachment, and that AI-based modeling offers a powerful framework for capturing these complex relationships.