Ontology-Based Personalized Cognitive Behavioural Plans for Patients with Mild Depression

Area of Science:

• Psychology
• Computer Science
• Knowledge Management

Background:

• Cognitive Behavioural Therapy (CBT) is a leading psychotherapy for depression.
• Computerized CBT (CCBT) aims to improve therapy accessibility.
• A standardized domain understanding is needed for CCBT knowledge management.

Purpose of the Study:

• To develop a CBT ontology for aggregating and operationalizing CCBT knowledge.
• To enable the generation of personalized action plans for mild depression treatment.
• To ensure transparency in evidence-based interventions within CCBT systems.

Main Methods:

• A Knowledge Management approach was used to synthesize CBT knowledge.
• The CBT ontology was developed using Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL).
• Formative evaluation assessed the ontology's completeness, consistency, and conciseness.

Main Results:

• A comprehensive CBT ontology was created.
• The ontology facilitates the generation of personalized action plans for mild depression.
• Ontology-enabled systems offer traceable, evidence-based treatment recommendations.

Conclusions:

• The developed CBT ontology effectively structures knowledge for computerized applications.
• This approach enhances the personalization and transparency of CCBT interventions.
• The ontology serves as a foundation for advancing digital mental health tools.