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Details of Grant 

EPSRC Reference: EP/X000788/1
Title: Unpacking the black box of interventions such as peer support designed to optimize mental health outcomes of family caregivers
Principal Investigator: Rose, Professor L
Other Investigators:
Casson, Professor A Rooksby, Dr J Ang, Dr C
Condell, Professor JV Matcham, Dr F
Researcher Co-Investigators:
Project Partners:
Department: Applied Technologies in Clinical Care
Organisation: Kings College London
Scheme: Standard Research - NR1
Starts: 01 September 2022 Ends: 31 May 2025 Value (£): 484,380
EPSRC Research Topic Classifications:
Bioelectronic Devices Mental Health
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
28 Oct 2021 Digital Health Sandpit Oct 2021 Announced
Summary on Grant Application Form
In the UK, 1 in 8 adults (around 6.5 million people) are family carers. Although people prefer to receive care from a family member in the home, saving the NHS millions each year, caregiving can cause significant mental health issues and caregiver burden. These mental health issues also can cause physical illness in family caregivers, further burdening the NHS. For example, family caregiver of intensive care survivors after hospital discharge have levels of anxiety, depression, and PTSD well above UK population norms.

In recent years, peer support programmes have become widely available but have differences in structure, delivery, and duration. Programmes are most commonly aimed at supporting people with a disease/disorder - few are specifically directed at family caregivers. However, although theory based, the effective ingredient of peer support remains unknown. This means we do not understand the optimal way to design and deliver peer support to effectively improve mental health and wellbeing and to reduce family caregiver burden.

We propose to use novel methods including a strategy that delivers very brief questionnaires at very frequent intervals in the moment for assessment of experience. This method is called Ecological Momentary Assessment. We will use continuous data from how these questionnaires are answered as well as sensed wearable data (such as sweating, temperature, heart rate) measured in the home to adapt questionnaire delivery i.e. to turn off when not appropriate such as driving or sleeping.

We will use these methods in family caregivers participating in peer support programmes and those not receiving any peer support.

All data collection methods will be co-designed with family caregivers through interviews and workshops at the commencement of our work.

In addition, we will explore development of an easy-to-use fluid biosensor that can measure cortisol levels in the home. Cortisol is a marker of stress but is currently measured by sending a specimen to a laboratory and not measured as a point-of-care test in the home. A COVID-19 lateral flow test is an example of a point-of-care test for use in the home.

Combining home cortisol measurement with adaptive rapid fire questionnaire delivery and other sensed wearable data may provide the key to unpacking the black box of peer support thereby identifying its effective ingredient. These data will help to provide the tools to better optimise mental health outcomes of family caregivers.

Key Findings
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Potential use in non-academic contexts
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