Artificial Intelligence-enhanced mobile Behavioural Activation therapy for Dementia and Mild cognitive impairment (AI-BADeM). MRC GW4 BioMed DTP PhD studentship 2025/26 Entry,

About the Project

About the GW4 BioMed2 Doctoral Training Partnership

The partnership brings together the Universities of Bath, Bristol, Cardiff (lead) and Exeter to develop the next generation of biomedical researchers. Students will have access to the combined research strengths, training expertise and resources of the four research-intensive universities, with opportunities to participate in interdisciplinary and ‘team science’. The DTP already has over 90 studentships over 6 cohorts in its first phase, along with 58 students over 3 cohorts in its second phase.

Project Information

Research Theme:

Neuroscience & Mental Health

Summary:

Dementia affects around 55 million people globally, often leading to depression and unhealthy behaviours like physical inactivity and social isolation. These issues can worsen cognitive decline and reduce quality of life for both patients and their caregivers. Behavioural Activation therapy can help alleviate depression by encouraging engagement in enjoyable and meaningful activities. However, implementing behavioural activation faces several challenges and is not straightforward. Our study will test whether artificial intelligence-assisted mobile behavioural activation can overcome these barriers and improve accessibility and effectiveness for people living with dementia or mild cognitive impairment and their caregivers, ultimately enhancing their quality of life.

Main Description:

In the UK, approximately 944,000 people live with dementia and struggle with everyday activities, depression and social isolation. Behavioural Activation (BA) interventions focus on purposeful activity scheduling tailored to individual needs, are associated with improvements in activities of daily living and quality of life for people living with dementia(PLWD) and those with mild cognitive impairment (MCI).

A meta-analysis of BA approaches found significant benefits, including higher levels of daily functioning and improved caregiver-rated quality of life(doi: 10.1002/14651858.CD009125.pub3). Emerging evidence suggests similar benefits for general older population, with better independence and quality of life.

Despite promising early evidence, research on dementia prevention has been limited by implementation failures, unrepresentative samples, small effect sizes, lack of tailored interventions and ineffective technology integration.

This PhD project addresses these gaps by exploring the use of an AI-assisted mobile platform (Iona Mind) adapted for PLWD and MCI, utilizing BA. The AI will categorize BA activities into themes: Routine, Enjoyable, and Necessary, targeting key risk factors for dementia and MCI progression. This innovative approach aims to improve accessibility, effectiveness, and overall quality of life for PLWD and MCI and their informal caregivers.

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