Volunteering for the Commonwealth Games: what can realist synthesis contribute to health policy making?

The aim of this thesis was to investigate, using the real-time test case of the 2014 Commonwealth Games, whether the realist synthesis methodology could contribute to the making of health policy in a meaningful way. This was done by looking at two distinct research questions: first, whether realist synthesis could contribute new insights to the health policymaking process, and second, whether the 2014 Commonwealth Games volunteer programme was likely to have any significant, measurable, impact on health inequalities experienced by large sections of the host population. The 2014 Commonwealth Games legacy laid out ambitious plans for the event, in which it was anticipated that it would provide explicit opportunities to impact positively on health inequalities. By using realist synthesis to unpick the theories underpinning the volunteer programme, the review identifies the population subgroups for whom the programme was likely to be successful, how this could be achieved and in what contexts. In answer to the first research question, the review found that while realist methods were able to provide a more nuanced exposition of the impacts of the Games volunteer programme on health inequalities than previous traditional reviews had been able to provide, there were several drawbacks to using the method. It was found to be resource-intensive and complex, encouraging the exploration of a much wider set of literatures at the expense of an in-depth grasp of the complexities of those literatures. In answer to the second research question, the review found that the Games were, if anything, likely to exacerbate health inequalities because the programme was designed in such a way that individuals recruited to it were most likely to be those in least need of the additional mental and physical health benefits that Games volunteering was designed to provide. The following thesis details the approach taken to investigate both the realist approach to evidence synthesis and the likelihood that the 2014 Games volunteer programme would yield the expected results.

Methods matter: computational modelling in public health policy and planning

This work is aimed at understanding and unifying information on epidemiological modelling methods and how those methods relate to public policy addressing human health, specifically in the context of infectious disease prevention, pandemic planning, and health behaviour change. This thesis employs multiple qualitative and quantitative methods, and presents as a manuscript of several individual, data-driven projects that are combined in a narrative arc. The first chapter introduces the scope and complexity of this interdisciplinary undertaking, describing several topical intersections of importance. The second chapter begins the presentation of original data, and describes in detail two exercises in computational epidemiological modelling pertinent to pandemic influenza planning and policy, and progresses in the next chapter to present additional original data on how the confidence of the public in modelling methodology may have an effect on their planned health behaviour change as recommended in public health policy. The thesis narrative continues in the final data-driven chapter to describe how health policymakers use modelling methods and scientific evidence to inform and construct health policies for the prevention of infectious diseases, and concludes with a narrative chapter that evaluates the breadth of this data and recommends strategies for the optimal use of modelling methodologies when informing public health policy in applied public health scenarios.