Advanced Care Research Centre

Understanding The Person In Context

The fourth work package of the Advanced Care Research Centre.

We will use innovative social science qualitative methodologies to understand how people manage the challenges posed by changes in physical and mental function in the context of their social support, personal financial circumstance, community resources and statutory services.

Dissemination Outputs and Impact:

An understanding of the circumstances, needs and priorities of people in later life in the context of families and communities is foundational for ACRC research. WP4 will ensure that we keep the person in later life at the heart of all research, as well as delivering new academic insights and contribution to social theory. There will be direct impact in relation to the focus of other research work-packages. The findings will be of direct value to many other stakeholders, for example by better understanding decision-making at times of transition.


We need to better understand how individuals and their families experience later life, with an emphasis on an approach to care that promotes continuing social participation and active citizenship, reflecting that we will almost all be carers and cared for at different times of our lives. Our ambition is to help maintain quality of life and sense of self for the individual as they experience different stages of later life, ensuring we understand the desired ‘ecology of care’ in context and the supportive physical, social and economic environments that are needed to provide this. ACRC funding provides a near-unique opportunity to generate a longitudinal understanding of the experience of transitions and care in later life.

Research Design:

The overall design of this WP is based in a set of linked and complementary studies described below. The research will apply social science qualitative methodologies and follow a carefully selected group of participants over five years. Using a variety of methods (according to each study’s focus and requirements), we will generate one data set for the whole WP to facilitate cross-study comparison and analysis. To ensure sensitivity to context, we will take a community case study approach, identifying 10 geographically and socioeconomically diverse communities in Scotland and England. Within each community, we will recruit participants with varying individual circumstances, and will work with WP1 (Stakeholder Engagement) to compare the experience and perceptions of younger age groups. Data collection will use co-creative and participatory approaches to ensure that we actively involve people in later life, their care partners and professionals.

The four underlying studies reflect different ways of focusing on experience of later life.

4.1 Personal Projects: By examining what people are seeking to achieve in their lives (big or small), we can better understand what contributes to meaningful quality of life and, by exploring how the wider environment helps or hinders these projects, we can understand how better to support people to maintain their sense of self and purpose.

4.2 Citizenship and Care: will discover how people in later life perceive citizenship and social participation and their own transitions as citizens framed through an understanding of how best to achieve ‘ageing in place’ or successful transitions to alternative living arrangements.

4.3 Understanding Care Transitions: will take a lifecourse approach to personal projects, to explore change over time, including: how societal mandates (e.g. protecting the vulnerable) enable and disable the individual, and the consequences of choices made for individual autonomy and sense of self; how mutual responsibilities are negotiated over time; and how participants might flourish, while managing risk in the face of an intrinsically uncertain environment.

4.4 Understanding Informal Care Networks: will develop rich understandings of how value in informal later life care is understood and constructed and how these could map into emerging personal socio-ecologies and to understand how data-driven technologies may support healthier, informal networks.