Improving Understanding and Acceptance of AI in Diabetic Eye Screening: Co-developing Educational Interventions for Patients Living with Diabetes and Healthcare Professionals Award Details Award Type:AcceleratorCommissioning Fund Theme:Integration of knowledge/advancing understanding of behaviour Lead Applicant:Dr Charlotte WahlichAmount Awarded:£50,091 FECAdministering Institution:City St George's, University of LondonStart Date:1st April 2026Duration:15 months Research Summary The NHS Diabetic Eye Screening Programme (DESP) reviews ~12 million eye images every year for presence and severity of diabetic retinopathy, an eye condition caused by diabetes. Currently, trained professionals review all these images. But as more people develop diabetes, this will have a profound impact on workload. Evidence has shown that systems using artificial intelligence (AI) can review eye images as well as humans and could speed up the process and save money. However, no AI-assisted system is currently approved for use in the NHS DESP in England. Introducing AI is not just about having efficient technology—it is also important to know how people feel about it. A recent study we conducted, involving over 1,800 people living with diabetes (PLD) and healthcare professionals (HCPs), found that many are unsure or worried about AI. PLD were concerned about how AI would affect their care. HCPs were concerned about job security and ongoing career progression/training. To make sure AI is accepted, adopted and used as intended, maintaining safety and efficacy, we plan to co-develop educational workshops and videos to explain how these AI systems work, why they’re being introduced, and how they will support, rather than replace, healthcare staff. Interviews with PLD from a broad range of sociodemographic backgrounds and HCP will inform the design of these workshops. Equitable co-design will build trust through knowledge transfer and retain PLD and HCPs engagement with the screening service. Expected Deliverables, Outputs and Outcomes This project will produce a novel educational programme of workshops and educational video for both HCP and PLD, which is based on theory (the Capability, Opportunity, Motivation – Behaviour model, COM-B model and encompasses various Behaviour Change Techniques. This educational programme will be translatable across different health conditions/ settings. This project advances methodological innovation by applying the COM-B model and Behaviour Change Techniques to inform the development of approaches for changing perception and behaviour related to AI in healthcare. Educational workshops will be assessed via pre- and post-surveys to measure changes in AI-related knowledge, perceptions, and acceptance within the DESP. Methods of assessing acceptability will be informed by the Theoretical Framework of Acceptability. Think-aloud interviews with PLD and HCP during video viewing will identify usability issues and inform final content. Research Team Name Organisation RoleCharlotte Wahlich City St George's, University of London Principal InvestigatorProfessor Michael Ussher City St George's, University of London Co-InvestigatorProfessor Alicja R Rudnicka City St George's, University of London Co-InvestigatorProfessor Christopher G Owen City St George's, University of London Co-InvestigatorDr Lakshmi Chandrasekaran City St George's, University of London Researcher Dr Umar Chaudhry City St George's, University of London Researcher Mrs Fiona Martin Person living with T1 diabetes and co- facilitator of the Hackney Diabetes Centre T1 peer support group Patient Collaborator Mr Adam Stott Person living with diabetes Patient Collaborator Gbenga Olasehinde Person living with diabetes Patient Collaborator This article was published on Wednesday 8 July 2026