Date of Award
Doctor of Philosophy (College of Medicine)
Schools and Centres
Professor Lucie Rychetnik
Professor Paul Kelly
Associate Professor Jo-An Atkinson
Introduction: Achieving evidence-based public health policy is challenging. There is increasing recognition that more sophisticated, system-science, analytic methods, such as dynamic simulation modelling (DSM), are needed to better understand the dynamic, interacting and interrelated elements within complex public health systems. This thesis explored the implementation, feasibility and value of a novel participatory DSM approach as a tool for knowledge mobilisation and decision support in Australian health policy settings. An indepth case study of participatory modelling of Diabetes in Pregnancy (DIP) in the Australian Capital Territory (2016-2018) was conducted. Two additional modelling case studies focusing on prevention of childhood overweight and obesity and alcohol-related harms in New South Wales provided supplementary data across different settings.
Methods: A multidisciplinary stakeholder group, including researchers, clinicians, public health practitioners, policy makers, and simulation modelling experts, was convened to coproduce a pioneering, multi-method DSM to inform DIP health service policy and planning. Using participatory action research methods, interviews with participants, recordings from model development workshops and meetings, participatory research field notes and other documents were analysed to determine the feasibiliy and value of the participatory model development process. The analysis explored the deliberations, challenges, opportunities and decisions involved. Interviews with end-user participants for the primary and additional case studies explored their perceptions of the utility and value of this approach in applied settings.
Results: Participatory DSM builds on elements of best practice in knowledge mobilisation, including embedding deliberative methods to build shared understanding. The methods enabled a collaborative, co-production approach to evidence-informed practice that moved beyond evidence synthesis to provide dynamic decision support. The participatory process was iterative, with key decisions re-visited and refined throughout the process. It facilitated a significant, interdisciplinary knowledge base, built understanding of the modelling process, and established trust in the model to inform policy decisions. Key insights relating to the prevention and management of DIP were gained. The importance of implementing and maintaining population interventions promoting healthy weight for children and young adults was demonstrated. The unique benefits of simulation modelling most valued by health sector decision makers were its capacity to explore risk factor interactions, compare the outcomes of alternative intervention combinations, and consider the impacts of scaling-up. Participants also valued simulating new interventions prior to implementation, and mapping evidence gaps to prioritise future research.
Discussion: Using a participatory approach to DSM for health policy is feasible and enhances the value of models as knowledge mobilisation and health policy decision support tools. The detailed analysis in this thesis revealed the socio-technical opportunities and challenges of implementing these interdisciplinary methods at the intersection of systems science, knowledge mobilisation and public health policy, and the key elements required for successful implementation in applied health policy settings.
2019_Freebairn_Study_Chapter1.pdf (446 kB)
2019_Freebairn_Study_Chapter2.pdf (586 kB)
2019_Freebairn_Study_Chapter3.pdf (896 kB)
2019_Freebairn_Study_Chapter4.pdf (2881 kB)
2019_Freebairn_Study_Chapter5.pdf (2963 kB)
2019_Freebairn_Study_Chapter6.pdf (763 kB)
2019_Freebairn_Study_Chapter7.pdf (2605 kB)
2019_Freebairn_Study_Chapter8.pdf (529 kB)
2019_Freebairn_Study_Appendices_1-5.pdf (4063 kB)
2019_Freebairn_Study_Appendices_6-10.pdf (5580 kB)
Freebairn, L. (2019). “Turning mirrors into windows”: A study of participatory dynamic simulation modelling to inform health policy decisions (Doctor of Philosophy (College of Medicine)). University of Notre Dame Australia. https://researchonline.nd.edu.au/theses/239