A systematic literature review for understanding the effectiveness of advanced techniques in diabetes self-care management

• Main Authors: Alsayed, Alhuseen Omar, Ismail, Nor Azman, Hasan, Layla, Syed, Asif Hassan, Embarak, Farhat, Da’u, Aminu
• Format: Article
• Language: English
• Published: Elsevier B.V. 2023
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/105007/1/NorAzmanIsmail2023_ASystematicLiteratureReviewforUnderstandingtheEffectiveness.pdf; http://eprints.utm.my/105007/; http://dx.doi.org/10.1016/j.aej.2023.08.026
• Institution: Universiti Teknologi Malaysia

This article includes a systematic review that identifies and summarizes the many behavioral change techniques (BCTs), behavioral health theories, and advanced techniques based on artificial intelligence (AI) currently used to manage diabetes. The review focuses on assessing the efficacy of diabetes self-care applications that leverage these cutting-edge techniques in their development and use. The study provides the latest comprehensive review and the findings of the report through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 reporting guidelines. After carefully reviewing and choosing pertinent studies from well-known bibliographic databases, the review finds that self-care treatments favor behavior change, blood glucose reduction, healthier habits, and substantial weight loss. According to the results, investigations that use these methodologies and ideas and AI-based ones are more likely to succeed. The evaluation ends by highlighting its shortcomings and outlining potential future research and application design areas. It also highlights the possibility of incorporating BCT methodologies, theories, and AI-based techniques in creating self-management interventions. The knowledge gained from this systematic review can help application developers create frameworks for effective diabetes self-care interventions based on the identified cutting-edge techniques.