Longitudinal trajectories of work absence: bridging the gap between health and work

The ability to work is one of the biggest drivers of social inequalities. Poor health, particularly chronic conditions, has a significant impact on work ability. The overall aim of the PhD is to derive common longitudinal trajectories of work absence in a population consulting their
general practitioner with a musculoskeletal or mental health condition, and to identify significant events (turning points) and characterise patients within each of these trajectories to enable those at risk of more persistent and recurrent work absence to be identified earlier.
The student will examine whether distinct patterns of work absence are detectable in primary care electronic health records (EHR). This studentship will use the Clinical Practice Research Datalink (CPRD), a large UK longitudinal database of primary care EHR. The student will identify trends in rates of work absence over time using recorded fit notes. They will then assess if it is possible to determine common patterns (trajectories) of absence comparing different statistical approaches including simple measures such as cumulative duration of absence to longitudinal statistical approaches such as latent class growth analysis and growth mixture modelling. The student will then assess whether there are distinct health and sociodemographic (for example, age, sex, deprivation, geographic region) characteristics associated with trajectories defined by persistent or recurrent absence.

Please ensure that you reference the studentship number SPSC2020_01 throughout your application.