DECODE

  • Research type

    Research Study

  • Full title

    Data-driven machine-learning aided stratification and management of multiple long-term conditions in adults with intellectual disabilities

  • IRAS ID

    315569

  • Contact name

    Gyuchan Thomas Jun

  • Contact email

    g.jun@lboro.ac.uk

  • Sponsor organisation

    Loughborough University

  • Duration of Study in the UK

    1 years, 10 months, 0 days

  • Research summary

    People with Intellectual Disabilities (PID) represent 1 in 100 of the UK population; of them, two-thirds have two or more long-term health problems, known as Multiple Long-Term Conditions (MLTCs). Some of these conditions can be delayed or prevented through lifestyle changes, such as diabetes and heart problems; for other conditions like epilepsy, better management can improve the quality of life.

    The aim of this research is to apply machine learning approaches to identify clusters and trajectories of MLTCs in people with ID and to utilise that information to develop actionable insights and practical Artificial Intelligence usage scenarios for effective care coordination to improve the health and wellbeing of people with ID.

    To ensure we hear the needs and views of the different actors involved in delivering care, this research will engage PID and their carers (experts by experience), health and social care professionals, tech innovators, charity members and policymakers (professional experts). We will use a combination of methods throughout the research as follows:
    • Interviews to talk about barriers and enablers to delivering good care coordination.
    • Focus groups to collect feedback and recommendations on the graphs and dashboards specially designed for people who will use them, including those with learning disabilities.
    • Participatory workshops to explore how technology (i.e., Artificial Intelligence) can help to improve care and support for people with intellectual disabilities and MLTCs and develop actionable suggestions (usage scenarios).
    • World Cafes (large group discussion sessions) to present our scenarios and evaluate their feasibility and risk.

    The outputs of this research will include a proposal (usage scenarios) for the joined-up model of care, with the ultimate purpose of improving the lives of people with intellectual disabilities to manage and prevent MLTCs.

  • REC name

    South West - Frenchay Research Ethics Committee

  • REC reference

    22/SW/0174

  • Date of REC Opinion

    17 Feb 2023

  • REC opinion

    Further Information Favourable Opinion