Digital Decisions: Enhancing Chronic Disease Self-Care Through Digital Health and AI-Enhanced Decision-Making

Area of Science:

• Digital Health
• Health Behavior
• Artificial Intelligence

Background:

• Digital health technologies (e.g., apps, wearables) are transforming patient engagement beyond clinical visits.
• Patients increasingly use digital tools for daily self-care decisions.

Purpose of the Study:

• To discuss the effectiveness of digital health interventions based on a systematic review.
• To analyze findings through the lens of dual-process theory.
• To propose future directions for digital health to enhance patient self-care and behavior change.

Main Methods:

• Systematic review and meta-analysis of digital health interventions.
• Application of dual-process theory to interpret intervention effectiveness.
• Discussion of emerging AI capabilities and implementation considerations.

Main Results:

• Digital health interventions showed modest improvements in self-care monitoring.
• Limited effects were observed on self-care maintenance and management behaviors.
• Technologies excel at supporting intuitive (fast) processes but struggle with deliberative (slow) ones.

Conclusions:

• Digital health should evolve to support reflective decision-making for sustained behavior change.
• AI can bridge cognitive processes, translating health information into actionable insights.
• Successful implementation requires human-centered design, patient engagement, and attention to bias, privacy, and transparency.