Digital twin technologies for supporting self-care in adults with diet-related chronic conditions: a systematic review

Of 3,685 records identified, four studies (N = 2,662) met the inclusion criteria, all focusing on type 2 diabetes. All four studies used continuous glucose monitoring (CGM), and three additionally used wearable devices and dietary logs integrated with AI-driven DT platforms to provide personalised feedback and recommendations, often alongside human coaching. Two retrospective studies found substantial reductions in antidiabetic medication use, with one reporting a 74% reduction over one year including discontinuation of insulin in 94% of baseline insulin users, and large class‑specific declines, such as sulfonylureas (-99%) and DPP‑4 inhibitors (-88%), with many participants maintaining HbA1c < 7% on no therapy or metformin monotherapy, and the other showing that 42.8% of participants eliminated all diabetes medications within 90 days while maintaining glycaemic control (via a staged medication‑reduction framework). One randomised controlled trial found that 94% of participants discontinued all T2D medications and 72.7% achieved diabetes remission after one year, accompanied by increased daily steps, improved sleep, and reduced sedentary time (with only 4.7% remaining on metformin alone at one year). Another study found that personalised insulin infusion guided by a DT over 14 days reduced insulin doses by 14-29% and increased time in the target glucose range to 86-97% (personal insulin pump data over a 14‑day collection period) CONCLUSIONS: DT-based interventions demonstrated potential to enhance multi-behavioural self-care and clinical outcomes in adults with type 2 diabetes. Evidence is currently limited to diabetes, highlighting the need for studies in other diet-related chronic conditions and standardised assessment of self-care behaviours.