System science approaches are increasingly used to explore complex public health problems. Quantitative methods, such as participatory dynamic simulation modelling, can mobilise knowledge to inform health policy decisions. However, the analytic and practical steps required to turn collaboratively developed, qualitative system maps into rigorous and policy-relevant quantified dynamic simulation models are not well described. This paper reports on the processes, interactions and decisions that occurred at the interface between modellers and end-user participants in an applied health sector case study focusing on diabetes in pregnancy.An analysis was conducted using qualitative data from a participatory dynamic simulation modelling case study in an Australian health policy setting. Recordings of participatory model development workshops and subsequent meetings were analysed and triangulated with field notes and other written records of discussions and decisions. Case study vignettes were collated to illustrate the deliberations and decisions made throughout the model development process.The key analytic objectives and decision-making processes included: defining the model scope; analysing and refining the model structure to maximise local relevance and utility; reviewing and incorporating evidence to inform model parameters and assumptions; focusing the model on priority policy questions; communicating results and applying the models to policy processes. These stages did not occur sequentially; the model development was cyclical and iterative with decisions being re-visited and refined throughout the process. Storytelling was an effective strategy to both communicate and resolve concerns about the model logic and structure, and to communicate the outputs of the model to a broader audience.The in-depth analysis reported here examined the application of participatory modelling methods to move beyond qualitative conceptual mapping to the development of a rigorously quantified and policy relevant, complex dynamic simulation model. The analytic objectives and decision-making themes identified provide guidance for interpreting, understanding and reporting future participatory modelling projects and methods.
Background Prostate-specific antigen (PSA) testing for prostate cancer is controversial. There are unresolved tensions and disagreements amongst experts, and clinical guidelines conflict. This both reflects and generates significant uncertainty about the appropriateness of screening. Little is known about general practitioners' (GPs') perspectives and experiences in relation to PSA testing of asymptomatic men. In this paper we asked the following questions: (1) What are the primary sources of uncertainty as described by GPs in the context of PSA testing? (2) How do GPs experience and respond to different sources of uncertainty? Methods This was a qualitative study that explored general practitioners' current approaches to, and reasoning about, PSA testing of asymptomatic men. We draw on accounts generated from interviews with 69 general practitioners located in Australia (n = 40) and the United Kingdom (n = 29). The interviews were conducted in 2013–2014. Data were analysed using grounded theory methods. Uncertainty in PSA testing was identified as a core issue. Findings Australian GPs reported experiencing substantially more uncertainty than UK GPs. This seemed partly explainable by notable differences in conditions of practice between the two countries. Using Han et al's taxonomy of uncertainty as an initial framework, we first outline the different sources of uncertainty GPs (mostly Australian) described encountering in relation to prostate cancer screening and what the uncertainty was about. We then suggest an extension to Han et al's taxonomy based on our analysis of data relating to the varied ways that GPs manage uncertainties in the context of PSA testing. We outline three broad strategies: (1) taking charge of uncertainty; (2) engaging others in managing uncertainty; and (3) transferring the responsibility for reducing or managing some uncertainties to other parties. Conclusion Our analysis suggests some GPs experienced uncertainties associated with ambiguous guidance and the complexities of their situation as professionals with responsibilities to patients as considerably burdensome. This raises important questions about responsibility for uncertainty. In Australia in particular they feel insufficiently supported by the health care system to practice in ways that are recognisably consistent with 'evidence based' professional standards and appropriate for patients. More work is needed to clarify under what circumstances and how uncertainty should be communicated. Closer attention to different types and aspects of the uncertainty construct could be useful.
Healthy Environments And Lives (HEAL) is the Australian national research network established to support improvements to health, the Australian health system, and the environment in response to the unfolding climate crisis. The HEAL Network comprises researchers, community members and organisations, policymakers, practitioners, service providers, and other stakeholders from diverse backgrounds and sectors. HEAL seeks to protect and improve public health, reduce health inequities and inequalities, and strengthen health system sustainability and resilience in the face of environmental and climate change, all with a commitment to building on the strengths, knowledge, wisdom, and experience of Aboriginal and Torres Strait Islander people, culture, and communities. Supporting applied research that can inform policy and practice, and effective research translation, implementation, and impact are important goals across the HEAL Network and essential to achieve its intended outcomes. To aid translation approaches, a research translation, implementation, and impact strategy for the HEAL Network was developed. The strategy has been created to inform and guide research translation across HEAL, emphasising communication, trust, partnerships, and co-design with communities and community organisations as well as the decision-makers responsible for public policies and programs. Development of the strategy was guided by research translation theory and practice and the Health in All Policies and Environment in All Policies frameworks. As described in this paper, the strategy is underpinned by a set of principles and outlines preliminary actions which will be further expanded over the course of the HEAL Network’s activities. Through these actions, the HEAL Network is well-positioned to ensure successful research translation and implementation across its program of work.
Systems thinking has emerged in recent years as a promising approach to understanding and acting on the prevention and amelioration of non-communicable disease. However, the evidence on inequities in non-communicable diseases and their risks factors, particularly diet, has not been examined from a systems perspective. We report on an approach to developing a system oriented policy actor perspective on the multiple causes of inequities in healthy eating.
Few Australians consume diets consistent with the Australian Dietary Guidelines. A major problem is high intake of discretionary food and drinks (those not needed for health and high in saturated fat, added sugar, salt and/or alcohol). Low socioeconomic groups (SEGs) suffer particularly poor diet-related health. Surprisingly, detailed quantitative dietary data across SEGs was lacking. Analysis of the most recent national nutrition survey data produced habitual intakes of a reference household (two adults and two children) in SEG quintiles of household income. Cost and affordability of habitual and recommended diets for the reference household were determined using methods based on the Healthy Diets Australian Standardised Affordability and Pricing protocol. Low SEGs reported significantly lower intakes of healthy food and drinks yet similarly high intakes of discretionary choices to high SEGs (435 serves/fortnight). Total habitual diets of low SEGs cost significantly less than those of high SEGs (AU$751/fortnight to AU$853/fortnight). Results confirmed low SEGs cannot afford a healthy diet. Lower intakes of healthy choices in low SEGs may help explain their higher rates of diet-related disease compared to higher SEGs. The findings can inform potential policy actions to improve affordability of healthy foods and help drive healthier diets for all Australians.
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