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Methodological innovations

Just as we aim to make advances in theory, we also strive to develop better and more complete ways to enhance our understanding of care and caring.

We hold six Care Data and Methods Sessions every year to share our work and engage with external speakers. These sessions provide a forum for discussing and developing qualitative, quantitative and mixed methods, helping us to maintain a consistent focus on rigorous methods, and raise team members’ awareness of opportunities for data gathering, linkage and analysis. 

We have explored the state-of-the-art across a spectrum of topics, including participatory and ethnographic methods, mixed-method design, network analysis, intersectional multi-level modelling, systems analysis, causal inference and survey design; 

Case studies

New application of method to study the impact of life events like becoming an unpaid carer 

Unpaid carers provide the majority of support for people living with challenges related to older age, long-term illness, or disability. However, the care they provide often results in a significant income penalty. We have developed an innovative approach that allows us to examine the impact of becoming an unpaid carer on people’s finances and other life chances (such as health, happiness and social relationships). The Individual Synthetic Control approach:

  • creates “synthetic doppelgängers”— digital twins who didn’t become a carer
  • allows us to estimate the causal impact of unpaid caring on individual incomes, highlighting that when all other things are equal, caring always results in a lower income
  • provides long-term estimates for how this income penalty builds over many years (the cumulative impact)
  • allows us to explore how these costs differ for people from various backgrounds (the intersectional inequalities).
illustration depicting the same person caring for another person, and not caring for anyone

In line with Open Research principles, we have created packages that allow people to freely use our new methods for their work in other research areas.

Linking data to understand how the context  of care impacts on experiences and life chances

We have completed several longitudinal studies that make important theoretical and methodological contributions to our understanding of care by linking household members (to create dyads – pairs of caring and cared-for people), linking people to where they live, and following them over time. This enables us to:

  • understand how relationships between unpaid carers and the people they care for impact on health, happiness and unmet need in different ways over time
  • explore the role of structural factors, such as area deprivation and social care provision, on different types of support to learn how we might improve provision.