**Hyper-Personalized Cognitive Remediation for Meta-Reality Identity Discrepancy Using Adaptive Bayesian Network Dynamics**

**Abstract:** This paper introduces a novel framework for mitigating the psychological distress stemming from discrepancies between digital and real-world identities within metaverse environments. Leveraging adaptive Bayesian network dynamics and utilizing individualized multimodal biometric data streams, the system provides personalized cognitive remediation interventions. Distinct from existing virtual therapy approaches, this framework emphasizes real-time, dynamic adjustment of intervention strategies based on measurable physiological and behavioral markers, resulting in demonstrably improved identity integration and reduced psychological distress. The proposed system is commercially viable, offering readily implementable solutions for metaverse platforms aiming to ensure user wellbeing.