Work Package 1
WP1 is based at the University of Manchester and University of Southampton and is interested in how we characterise and identify high impact chronic pain (HICP). Particularly, we are interested in how we can identify HICP in populations where people have not been directly asked about the impact of their pain, and we can identify new, typically ‘unmeasured’ aspects of the impact of chronic pain. WP1 uses advanced computational methods (e.g machine learning) to identify and test definitions of pain impact, and to describe what HICP looks like in different populations.
The research team are currently exploring:
- How we can identify HICP in studies where people have not been asked directly about their pain impact
- Whether ‘clustering’ methods will allow us to identify novel patterns of pain impact, by separating people into groups with similar traits
- Intersectional differences between males and females in the prevalence and risk of experiencing chronic pain and HICP
Work Package 1 team:
- Professor John McBeth – Work-Package Lead
- Dr Charlotte Woolley – Research Fellow
Outputs:
Charlotte S C Woolley, John Mcbeth, on behalf of the CHIPP team. Identifying High Impact Pain in the UK Biobank 2019 Experience of Pain Survey. Poster presented at the IASP World Congress on Pain, Amsterdam, Netherlands, August 5 – 9, 2024.
Charlotte S C Woolley, John Mcbeth, on behalf of the CHIPP team. Measuring the impact of chronic pain in the UK Biobank: the Chronic High Impact Pain Project (CHIPP). Poster presented at the Advanced Pain Discovery Platform Annual Conference, Nottingham, UK, June 7, 2024.
Vitali D, Woolley CSC, Ly A, et al. How Well Can We Measure Chronic Pain Impact in Existing Longitudinal Cohort Studies? Lessons Learned. J Pain. 2025;26:104679. doi:10.1016/j.jpain.2024.104679. https://pubmed.ncbi.nlm.nih.gov/39299445/
