ORCID
- Hobson-Merrett, Charley: 0000-0002-2990-2871
- Byng, Richard: 0000-0001-7411-9467
Abstract
Background This paper explores the extent to which the implementation and evaluation of a collaborative care model of face-to-face service delivery for people with severe mental illness was viable during the first UK lockdown associated with COVID-19. The PARTNERS2 cluster randomised controlled trial and process evaluation were co-designed with service users and carers. The aim of this paper is to explore whether digital adaptation of the PARTNERS model for people with severe mental illness during the COVID-19 lockdown was equitable, in terms of fostering collaboration and trust in a vulnerable population. Results We collected qualitative data from multiple sources during lockdown and subsequently constructed case-studies of participating secondary care workers. We adopted Bauman’s notions of liquid modernity to inform our analysis, and identified that digital adaptation during lockdown was only successful where organisational policies, care partner skills and service users’ existing resources were optimal. Conclusion PARTNERS2 can be delivered digitally by a care partner to support people with severe mental illness to identify and work towards their goals when existing resources are optimal. However, at a time of increased need, we identified that people who are very unwell and living with limited access to resources and opportunities, remained disenfranchised at great cost. Trial registration ISRCTN 95702682, registered 26.10.2017
DOI
10.1186/s44247-023-00028-x
Publication Date
2023-08-03
Publication Title
BMC Digital Health
Volume
1
Issue
1
Embargo Period
2023-12-06
Organisational Unit
Peninsula Medical School
Recommended Citation
Frost, J., Hobson-Merrett, C., Gask, L., Clark, M., Pinfold, V., Plappert, H., Reilly, S., Gibson, J., Richards, D., Denyer, R., & Byng, R. (2023) 'Liquidity and uncertainty: digital adaptation of a complex intervention for people with severe mental illness during the COVID-19 lockdown', BMC Digital Health, 1(1). Available at: https://doi.org/10.1186/s44247-023-00028-x