10054562Staying Well XRClosedCollaborative R&DISCFMillions of people in the UK are affected by mental health conditions such as bipolar disorder (BD), psychosis and depression. These conditions have significant impact on both those who experience them and their carers; particularly impacting their employment, leisure, and relationships. The annual cost to the NHS of managing BD alone is estimated to be £2 billion, while the wider societal costs associated with the condition in the UK have been estimated at over £6 billion annually. When service users are well and their condition is 'in remittance', a key NICE recommendation is 'relapse prevention' work, supported by various interventions including 'Staying Well Plans'. Guided by mental health professionals, service users learn about their symptoms, identifying patterns of symptoms associated with developing ill health called 'relapse signatures'. Effective coping strategies are identified to support staying well. One commonly used relapse prevention method is the Early Warning Signs (EWS) card-sort task. Therapists using card-sorting confirm that most service users find it engaging and useful. The COVID-19 restrictions prompted our team's lead researcher to digitise the task. This digital proof-of-concept enabled clinicians to effectively carry out the card-sort when delivering remote therapy. However, high quality administration of the card-sort is time-consuming, and developing a compelling and memorable Staying Well Plan is often led by the therapist rather than by the service user. These plans are often developed under significant time pressure due to service demands, and may not be optimally personal, memorable, or accessible to service users. In contrast, those that are service user-developed under light guidance of the therapist may be more individually meaningful and memorable, especially when delivered in a more immersive setting. StayingWell XR uses an immersive environment where service users can explore and learn to self-identify signs they may be experiencing a relapse of their mental health condition; be it BD, psychosis or depression. Our feasibility study will deliver a wearable Virtual Reality (VR) software allowing service users to explore their 'relapse signatures' and coping strategies with and without a therapist. They will be able to take appropriate action to avert a potentially damaging episode, and anonymously share their experiences with others in a similar situation. We will write a feasibility report evaluating the app's usability, situating it in the larger competitive landscape of mental health products adjacent to our approach. The report will recommend further development steps for our project, including an optimal route to market.