Active Diabetes, Hormones & Metabolism Computing & AI

Human Agency & Leveraging Technology (HALT) to prevent diabetes complications

Funder DiabetesUK Charity-funded
Recipient organisation PhD Studentship
Funding £99K
Period Jan 2025 — Jan 2028

In plain English

AI plain-English summary

Diabetes complications are often caught too late, after the damage is already done. Current screening methods detect microvascular changes only once they have developed, limiting how effectively treatments can prevent or delay further harm. This research tackles that gap by asking whether artificial intelligence can predict complication risks before symptoms appear—and, crucially, whether people with diabetes will trust and act on those predictions. Using questionnaires, voice notes, interviews, and focus groups, the team will assess how current screening affects individuals emotionally, how patients and clinicians perceive AI in healthcare, and what builds trust in AI-driven risk tools. The findings will feed into recommendations developed with a consensus panel of people with diabetes and healthcare professionals. If successful, this work could shift diabetes care from reactive to preventive: instead of waiting for retinal damage or kidney decline, patients could receive precise, actionable warnings early enough to change course. The impact would be felt in everyday clinic visits, in the design of health apps, and in how the NHS deploys AI—not as a black box, but as a tool people genuinely understand and use.

View original technical description
Preventing and delaying diabetes complications require tight glycaemic control, but current screening methods detect microvascular changes only after they have developed, limiting treatment effectiveness. Emerging Artificial Intelligence (AI) in healthcare holds promise for transforming diabetes care by enabling early detection of complication risks before symptoms appear. Effective management depends on providing precise, actionable information that empowers individuals with diabetes to make informed decisions. Therefore, bridging the gap between technology, human understanding, and emotional well-being is essential. This research program will assess the impact of current screening methods on individuals with diabetes, evaluate perceptions of AI in healthcare, and explore strategies to build trust and understanding in AI risk prediction. Using a mixed-methods approach, including questionnaires, voice notes, interviews, and focus groups, the study will gather comprehensive insights. The results will inform recommendations developed in collaboration with a consensus panel of people with diabetes and healthcare professionals. The ultimate goal is to optimise the use of AI technologies to benefit both individuals living with diabetes and the healthcare system.

View the original record at the funder ↗

Researchers

Rebecca Thomas (EPMC Awardee)

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Original classification

Studentship

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.