Overcoming Barriers to Labour Market Entry Amongst People with Disabilities and Long-term Health Conditions and their Unpaid Ca

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The PhD will address the research questions by using three existing high-quality large social survey datasets. One of the surveys has an existing linkage to administrative health and social care data, and all have substantial coverage of individuals experiencing DH/DH-C in Scotland. Each survey has its own particular strengths, allowing triangulation of findings with coverage of short, medium and long run employment dynamics for people with work-limiting conditions. The datasets are: The UK Labour Force Survey (UK LFS) has a rotating panel design, with each household interviewed five times over a one-year period. Detailed questions on employment characteristics, work-limiting disabilities and caring are included. It will support the analysis of short-run dynamics in employment and DH/DH-C circumstances of individuals, with particular strengths in comparing the type and quality of employment. Understanding Society (UKHLS) follows a large sample of households in annual waves, collecting a range of information about employment and health status. This dataset allows the comparison of medium to long-run dynamics of employment by DH/DH-C statusThe Scottish Health Survey (SHeS) (linked to administrative health records) provides detailed information on individuals' health status, combined with longitudinal information from administrative records of hospital admissions. Employment status is only measured at one time point, but this dataset will allow the analysis of health trajectories over time and their links to employment outcomes.In analysing the datasets, the PhD student will make use of a range of statistical methods including sequence analysis, logistic regression, panel data methods and multilevel modelling. The large scale of the data will allow analysis of the complex social heterogeneities that surround DH and DH-C experiences. A methodological contribution of the research will be to evaluate alternative measurement options when assessing heterogeneous employment circumstances and definitions of DH/DH-C.