[Tailored Treatment: Opportunities for Algorithm-Based Modular Psychotherapy in Hungarian Mental Health Care]

Area of Science:

• Psychiatry and Behavioral Sciences
• Clinical Psychology
• Psychotherapy Research

Background:

• Limited efficacy of traditional psychotherapies for complex mental disorders, especially with comorbidities and trauma.
• Failure of diagnosis-specific protocols to address underlying transdiagnostic mechanisms hindering treatment success.
• Need for personalized and mechanism-focused therapeutic models.

Purpose of the Study:

• To review the theoretical framework of Algorithm-Based Modular Psychotherapy (MoBa).
• To present key international findings and the structure of the MoBa approach.
• To explore the potential implementation of MoBa within the Hungarian mental health system.

Main Methods:

• Review of theoretical background and international findings on MoBa.
• Description of the modular structure and core transdiagnostic targets (e.g., rejection sensitivity, emotion dysregulation).
• Analysis of clinical and institutional challenges for MoBa implementation in Hungary.

Main Results:

• MoBa is a personalized, mechanism-focused treatment model utilizing a decision-making algorithm to select therapeutic modules.
• Core transdiagnostic targets include rejection sensitivity, emotion dysregulation, and impaired social cognition.
• Identified clinical and institutional challenges for adapting MoBa in Hungary.

Conclusions:

• MoBa represents a promising transdiagnostic, personalized treatment approach for various mental disorders.
• Adaptation of MoBa in Hungary requires addressing specific clinical and institutional challenges.
• Further research and practical recommendations are needed for successful MoBa implementation.