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

Advances in digital health have dramatically changed how patients engage with their health. Rather than relying solely on periodic clinical visits, patients now have access to smartphones, patient portals, wearable devices, and mobile apps that provide support for day-to-day self-care decisions. This commentary discusses the findings of Longhini et al's systematic review and meta-analysis on the effectiveness of digital health interventions, which found modest improvements in self-care monitoring but limited effects on self-care maintenance and management behaviors. Reflecting on these findings through the lens of dual-process theory, digital health technologies appear to be effective at supporting fast, intuitive processes, such as symptom monitoring, but are less effective at engaging slower, deliberative processes needed for complex decision-making and behavior change. Digital health technologies should evolve from primarily supporting routine self-care activities to enhancing patients' reflective decision-making processes for sustained behavior change. Emerging AI capabilities offer opportunities to strengthen and bridge these fast and slow cognitive processes by translating complex health information into actionable insights and facilitating patient-clinician communication. Realizing this potential requires careful attention to implementation, including integration into clinical workflows, patient and clinician education, and digital literacy. In addition, digital health teams should adopt standardized implementation frameworks and outcome measures to generate a more robust evidence base. Lastly, human-centered design, patient engagement, and safeguards addressing bias, privacy, and transparency are foundational to ensure that the rapid pace of digital health technology will continue to enhance patient self-care and health outcomes.