A scoping review of AI-powered/ data-driven interventions in Type-2 diabetic care in low -and middle-income countries for patient-provider health communication.

Artificial intelligence (AI) -powered and data-driven tools can offer personalised, engaging, and on-demand health communications interventions for patients and healthcare providers. This scoping review aims to analyse existing scientific evidence on the use of AI-powered and data-driven visual, auditory, and text-based web-based tools for patient-provider health communication and to identify which guidelines and studies enhanced the quality of patient-provider health communication in self-care and lifestyle outcomes of type-2 diabetic patients. Addressing the knowledge gap allows informed advancements in AI-powered and data-driven health interventions for type-2 diabetic patients. The review question is: What is the existing evidence for AI-powered and data-driven visual, auditory, and text-based storytelling health intervention for patient-provider health communication to improve self-care and lifestyle management in patients with type-2 diabetes (T2DM) in LMICs and HICs? Findings from this scoping review will inform two systematic reviews. One will explore the acceptability and the other the effectiveness of the identified AI-powered / data-driven visual, auditory, and text-based messaging systems for storytelling health interventions to improve self-care and lifestyle management in patients with type-2 diabetes in LMICs and HICs. Methodology: The scoping review will follow the JBI Scoping Review methodology outlined in the 2015 Joanna Briggs Institute Reviewers' Manual and the PRISMA-ScR guideline.