IJPDS International Journal of Population Data Science IJPDS 2399-4908 Swansea University 10.23889/ijpds.v10i3.3172 10:3:143 Universal Credit trajectories among individuals who access secondary mental health services: a sequence analysis of linked data. Ledden Sarah 1 Stevelink Sharon 1 Bakolis Ioannis 1 2 Leal Ray 1 Madan Ira 1 3 Hotopf Matthew 1 2 Fear Nicola 1 Lorentzen Thomas 4 King's College London, London, United Kingdom South London and Maudsley NHS Trust, London, United Kingdom Guy's and St Thomas' Hospitals NHS Trust, London, United Kingdom University of Bergen, Bergen, Norway 01 06 2025 2025 8 4 3172 This work is licenced under a Creative Commons Attribution 4.0 International License. This article is available from the IJPDS website at: https://ijpds.org/article/view/3172 Objectives

Universal Credit (UC) was introduced in 2013 as part of welfare benefit reforms in the UK. It replaced six previous benefits, including jobseeker’s allowance, income support, and housing benefit. We aimed to examine UC trajectories, and transitions between UC conditionality regimes, among secondary mental health service users between 2016-2020.

 Methods

We used a linked dataset established by combining electronic secondary mental health records from South London and Department for Work and Pensions (DWP) administrative benefits data. 4,876 individuals who received UC for the first time in 2016 were included as our entry cohort, and followed up for approximately 4.5 years. We used sequence analysis to analyse transitions between UC regime states, followed by cluster analysis to identify typical UC trajectories. We used multinominal logistic regression to test associations between sociodemographic and diagnostic characteristics with UC trajectory membership; presenting these results as average marginal effects.

 Results

Our analysis identified six distinct UC trajectory clusters. These clusters indicated: short-term UC searching for work (18.7%), medium-term UC searching for work (19.1%), long-term UC searching for work (21.4%), no work requirements (11.9%), UC working cluster (6.1%), and no work searching and caring responsibilities cluster (22.8%). Distinct characteristic profiles were associated with each of these clusters. Women were overrepresented in the ‘no work searching and caring responsibilities’ cluster and a cluster indicating more low-paid or part-time work. Older people were more likely to be in the ‘long-term searching for work’ and ‘no work requirements’ clusters. Those with diagnosis of severe mental illness were over-represented in the no work requirements group.

 Conclusion

Using a novel analysis method, we identified six distinct UC trajectories among users of secondary mental health services and identified characteristics of patients represented within these groups. Findings can be used to inform and tailor support to groups vulnerable to conditionality or longer-term UC receipt.