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

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Absence from work due to ill-health is one of the biggest causes of productivity loss across the UK. This PhD proposal aims to compare statistical methods to model common patterns (trajectories) of work absence using a large national electronic health record database; and determine health and sociodemographic characteristic associated with the resultant trajectories. Simple statistical approaches such as cumulative duration of absence will be compared to more complex methods such as latent class growth analysis and growth mixture modelling. Understanding patterns of absence would allow clinicians (and potentially workplaces) to identify those employees who may need further support, earlier than would otherwise be possible. By understanding the profiles of the patients/employees within these trajectories this support can be tailored to their specific needs, therefore making interventions more likely to succeed and hence preventing the potential for adverse economic and social outcomes for the individual, the economy and the wider society.