Journal of Medicine and Health Research

Non-communicable diseases (NCDs) remain a critical global health challenge, requiring innovative, scalable, and personalized solutions. Mobile health (mHealth) interventions have shown promise in managing NCDs by promoting medication adherence, behaviour modification, and self-management. The integration of artificial intelligence (AI) into mHealth platforms amplifies these benefits through enhanced personalization, predictive analytics, and dynamic patient engagement. This study systematically evaluates the effectiveness of AI-enabled mHealth interventions in improving NCD outcomes, offering a theoretical framework and evidence-based insights. The conceptual framework highlights the characteristics of AI-enabled mHealth interventions and their alignment with behaviour change theories, such as social cognitive theory and self-efficacy models. Core mechanisms explored include AI-driven personalized medicine, health coaching, virtual assistants, and predictive analytics for early disease detection. Evidence reveals significant benefits, including improved health outcomes and enhanced patient engagement, showcasing the transformative potential of these tools. However, challenges such as data privacy concerns, inequitable access, and algorithmic biases hinder widespread adoption. Addressing these barriers requires robust policy frameworks, ethical considerations, and collaboration among healthcare stakeholders, policymakers, and technologists. Future research must prioritize human-centred design and inclusivity to maximize the impact of AI-enabled mHealth solutions. This study offers a comprehensive examination of the role of AI in mHealth interventions, contributing to the theoretical understanding and practical application of these technologies. The findings hold significant implications for advancing effective and sustainable solutions for NCD management, supporting global efforts to combat the growing burden of chronic diseases.