Experiencing illness often involved complex and demanding work. Some tasks were assigned by health and social care professionals, creating negotiated obligations, such as managing symptoms, following diets, using medication or devices, navigating websites, and coordinating services. People also took on assumed obligations voluntary efforts by patients, families, and caregivers to support care beyond formal agreements.
The ability to manage this work depended on personal and social resources like income, education, ethnicity, gender, and age. These demands shifted over time based on the type and progression of illness, known as trajectories.
To better understand this "service user work" and the capacity to manage it, we planned a large review of published research on three illness trajectories: long-term disabling conditions, serious relapsing diseases, and rapidly progressing illnesses. First, we aimed to build a framework to organise the data. We then planned to extract insights using two methods: manual analysis and text mining software, which identifies patterns in language.
By combining both techniques, we hoped to create a detailed model of the challenges people faced, shaped by illness, service structures, and social inequality. Finally, we intended to work with patients, carers, and professionals to apply our findings and support strategies for reducing workload and improving care for those with complex health needs.