Towards Adaptability of Just-in-Time Adaptive Interventions

Area of Science:

• Digital Health
• Behavioral Science
• Computer Science

Background:

• Just-in-time adaptive interventions (JITAIs) show promise for promoting patient behavior change.
• Current JITAIs often lack adaptability for diverse applications and individual needs.
• Centralized maintenance and data analysis across multiple JITAI deployments are challenging.

Purpose of the Study:

• To develop a concept for adaptable just-in-time adaptive interventions (JITAIs).
• To enable JITAIs to be configured for different purposes and personalized for individual participants.
• To facilitate central maintenance and integrated data analysis across various JITAI deployments and user groups.

Main Methods:

• A design science research approach was employed to create the JITAI concept.
• The concept utilizes multi-level conceptual modeling.
• Knowledge graphs are integrated into the JITAI framework.

Main Results:

• A novel concept for adaptable JITAIs has been developed.
• The proposed framework supports configuration, personalization, and centralized management.
• The concept is designed for evaluation in upcoming user studies.

Conclusions:

• Adaptable JITAIs can enhance the flexibility and scalability of digital health interventions.
• Multi-level conceptual modeling and knowledge graphs provide a robust foundation for adaptable JITAIs.
• Further research through user studies is necessary to validate the practical utility of this approach.