Injury hospitalisations for children and young people: a 20-year review.

BACKGROUND: Childhood injuries can have significant lifelong consequences. Quantifying and understanding patterns in injury severity can inform targeted prevention strategies and policies. This study examines the characteristics of child injury hospitalisations in the Australian Capital Territory over 20 years. METHODS: This study is a retrospective analysis of Admitted Patient Care Collection data for persons aged 0-24 years who were hospitalised for an injury between July 2000 and June 2020. Injury severity was assessed using International Classification of Injury Severity Scores based on survival risk ratios. RESULTS: The age standardised rate for injury hospitalisations increased significantly from 10.2 per 1000 in 2000/2001 to 21.0 per 1000 in 2019/2020, representing an average annual per cent change of 3.6%. Almost two-thirds of injuries were for men, however the rate of injury hospitalisations increased more rapidly in women. The majority of injuries (81.8%) were classified as minor. The proportion of injuries classified as serious increased with age. For moderate and serious injuries, injuries to the head were the most common type of injury, while falls were the leading cause. Self-harm injuries emerged as a leading contributor to the increase in injuries in young people aged 13-24 years old. CONCLUSION: This study emphasises the concerning upward trend in injury hospitalisations among children and young people over the past two decades. Given Australia is yet to formalise a national injury prevention strategy, understanding the patterns and characteristics of injuries is vital to developing effective prevention interventions to reduce harm and improve child safety.

Strengthening mental health research outcomes through genuine partnerships with young people with lived or living experience: A pilot evaluation study.

BACKGROUND: Despite increasing support for stakeholder inclusion in research, there is limited evaluative research to guide safe (i.e., youth-friendly) and meaningful (i.e., non-tokenistic) partnerships with young people with lived experience of mental ill-health in research. This paper describes a pilot evaluation and iterative design of a Youth Lived Experience Working Group (LEWG) protocol that was established by the Youth Mental Health and Technology team at The University of Sydney's Brain and Mind Centre, based on the results of two studies. METHODS: Study one consisted of a pilot evaluation of the extent to which youth partners felt empowered to contribute, to qualitatively explore how LEWG processes could be improved. Youth partners completed online surveys, and results were shared over two LEWG meetings in 2021 to empower youth partners to collectively identify actions of positive change regarding LEWG processes. These meetings were audio-recorded and transcripts were subsequently coded using thematic analysis. Study two assessed whether LEWG processes and proposed improvements were acceptable and feasible from the perspective of academic researchers via an online survey in 2022. RESULTS: Quantitative and qualitative data collected from nine youth partners and 42 academic researchers uncovered initial learnings regarding facilitators, motivators, and barriers to partnering with young people with lived experience in research. Implementing clear processes for youth partners and academic researchers on effective partnership strategies, providing training opportunities for youth partners to develop research skills, and providing regular updates on how youth partner contributions led to research outcomes were identified as key facilitators. CONCLUSIONS: This pilot study provides insight into a growing international field on how to optimise participatory processes so that researchers and young people with lived experience can be better supported and engaged to make meaningful contributions to mental health research. We argue that more transparency is needed around participatory research processes so that partnerships with young people with lived experience are not merely tokenistic. CONSUMER CONTRIBUTIONS: Our study has also been approved by and reflects the concepts and priorities of our youth lived experience partners and lived experience researchers, all of whom are authors of this paper.

Conceptualising the value of simulation modelling for public engagement with policy: a critical literature review.

As we face complex and dynamically changing public health and environmental challenges, simulation modelling has come to occupy an increasingly central role in public engagements with policy. Shifts are occurring not only in terms of wider public understandings of modelling, but also in how the value of modelling is conceptualised within scientific modelling communities. We undertook a critical literature review to synthesise the underlying epistemic, theoretical and methodological assumptions about the role and value of simulation modelling within the literature across a range of fields (e.g., health, social science and environmental management) that engage with participatory modelling approaches. We identified four cross-cutting narrative conceptualisations of the value of modelling across different research traditions: (1) models simulate and help solve complex problems; (2) models as tools for community engagement; (3) models as tools for consensus building; (4) models as volatile technologies that generate social effects. Exploring how these ideas of 'value' overlap and what they offer one another has implications for how participatory simulation modelling approaches are designed, evaluated and communicated to diverse audiences. Deeper appreciation of the conditions under which simulation modelling can catalyse multiple social effects is recommended.

Applying systems thinking to knowledge mobilisation in public health.

CONTEXT: Knowledge mobilisation (KM) is a vital strategy in efforts to improve public health policy and practice. Linear models describing knowledge transfer and translation have moved towards multi-directional and complexity-attuned approaches where knowledge is produced and becomes meaningful through social processes. There are calls for systems approaches to KM but little guidance on how this can be operationalised. This paper describes the contribution that systems thinking can make to KM and provides guidance about how to put it into action. METHODS: We apply a model of systems thinking (which focuses on leveraging change in complex systems) to eight KM practices empirically identified by others. We describe how these models interact and draw out some key learnings for applying systems thinking practically to KM in public health policy and practice. Examples of empirical studies, tools and targeted strategies are provided. FINDINGS: Systems thinking can enhance and fundamentally transform KM. It upholds a pluralistic view of knowledge as informed by multiple parts of the system and reconstituted through use. Mobilisation is conceived as a situated, non-prescriptive and potentially destabilising practice, no longer conceptualised as a discrete piece of work within wider efforts to strengthen public health but as integral to and in continual dialogue with those efforts. A systems approach to KM relies on contextual understanding, collaborative practices, addressing power imbalances and adaptive learning that responds to changing interactions between mobilisation activities and context. CONCLUSION: Systems thinking offers valuable perspectives, tools and strategies to better understand complex problems in their settings and for strengthening KM practice. We make four suggestions for further developing empirical evidence and debate about how systems thinking can enhance our capacity to mobilise knowledge for solving complex problems - (1) be specific about what is meant by 'systems thinking', (2) describe counterfactual KM scenarios so the added value of systems thinking is clearer, (3) widen conceptualisations of impact when evaluating KM, and (4) use methods that can track how and where knowledge is mobilised in complex systems.

Contribution of maternal overweight and obesity to the occurrence of adverse pregnancy outcomes.

AIMS: Maternal overweight and obesity in pregnancy are known to increase the risk of a range of complications and adverse pregnancy outcomes. This study estimates the population-level contribution of maternal overweight and obesity to adverse pregnancy outcomes. METHODS: Data derived from the Australian Capital Territory (ACT) Maternal and Perinatal Data Collection were analysed. A total of 24 161 women who had a singleton birth in 2009-2015, with maternal weight and height information available, were included. In this study, the association between risk factors and outcomes was investigated using multilevel regression modelling. Based on model predictions under various hypothetical maternal weight scenarios, the number and proportion of adverse perinatal outcomes that could be potentially prevented were estimated. RESULTS: Maternal overweight and obesity were associated with increased risks of gestational diabetes mellitus (GDM), pre-eclampsia, caesarean delivery, preterm birth (PTB), large for gestational age (LGA) and admission to the special care nursery or neonatal intensive care unit (SCN/NICU). The estimated proportions of adverse pregnancy outcomes attributable to overweight and obesity in pregnancy are 29.3% for GDM, 36.2% for pre-eclampsia, 15.5% for caesarean delivery, 21.6% for longer antenatal stay in hospital (≥2 days), 16.3% for extreme PTB, 25.2% for LGA and 6.5% for SCN/NICU admission. CONCLUSIONS: Maternal overweight and obesity contribute to a large proportion of obstetric complications and adverse outcomes in the ACT. Effective intervention strategies to reduce the prevalence of overweight and obesity in pregnant women could have significant beneficial effects on pregnancy outcomes.

Decision makers' experience of participatory dynamic simulation modelling: methods for public health policy.

BACKGROUND: Systems science methods such as dynamic simulation modelling are well suited to address questions about public health policy as they consider the complexity, context and dynamic nature of system-wide behaviours. Advances in technology have led to increased accessibility and interest in systems methods to address complex health policy issues. However, the involvement of policy decision makers in health-related simulation model development has been lacking. Where end-users have been included, there has been limited examination of their experience of the participatory modelling process and their views about the utility of the findings. This paper reports the experience of end-user decision makers, including senior public health policy makers and health service providers, who participated in three participatory simulation modelling for health policy case studies (alcohol related harm, childhood obesity prevention, diabetes in pregnancy), and their perceptions of the value and efficacy of this method in an applied health sector context. METHODS: Semi-structured interviews were conducted with end-user participants from three participatory simulation modelling case studies in Australian real-world policy settings. Interviewees were employees of government agencies with jurisdiction over policy and program decisions and were purposively selected to include perspectives at different stages of model development. RESULTS: The 'co-production' aspect of the participatory approach was highly valued. It was reported as an essential component of building understanding of the modelling process, and thus trust in the model and its outputs as a decision-support tool. The unique benefits of simulation modelling included its capacity to explore interactions of risk factors and combined interventions, and the impact of scaling up interventions. Participants also valued simulating new interventions prior to implementation in the real world, and the comprehensive mapping of evidence and its gaps to prioritise future research. The participatory aspect of simulation modelling was time and resource intensive and therefore most suited to high priority complex topics with contested options for intervening. CONCLUSION: These findings highlight the value of a participatory approach to dynamic simulation modelling to support its utility in applied health policy settings.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.

BACKGROUND: Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. OBJECTIVE: This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. CONCLUSION: Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

Missing in action: the right to the highest attainable standard of mental health care.

BACKGROUND: The right to the highest attainable standard of mental health remains a distant goal worldwide. The Report of the UN Special Rapporteur on the right of all people to enjoyment of the highest attainable standard of physical and mental health pleaded the urgent need for governments to act through appropriate laws and policies. We argue that Australia is in breach of international obligations, with inadequate access to mental health services, inconsistent mental health legislation across jurisdictions and ongoing structural (systematic) and individual discrimination. DISCUSSION: Inadequate access to mental health services is a worldwide phenomenon. Australia has committed to international law obligations under the Convention on the Rights of Persons with Disabilities (CRPD) to 'promote, protect and ensure the full and equal enjoyment of all human rights and fundamental freedoms by all persons with disability, with respect to their inherent dignity'. This includes people with mental health impairment and this convention includes the right to 'the highest attainable standard of mental health'. Under the Australian Constitution, ratification of this convention enables the national government to pass laws to implement the convention obligations, and such national laws would prevail over any inconsistent state (or territory) laws governing mental health service provision. The authors argue that enabling positive rights through legislation and legally binding mental health service standards may facilitate enhanced accountability and enforcement of such rights. These steps may support critical key stakeholders to improve the standards of mental health service provision supported by the implementation of international obligations, thereby accelerating mental health system reform. Improved legislation would encourage better governance and the evolution of better services, making mental health care more accessible, without structural or individual discrimination, enabling all people to enjoy the highest attainable standard of health.

A Dynamic Approach to Economic Priority Setting to Invest in Youth Mental Health and Guide Local Implementation: Economic Protocol for Eight System Dynamics Policy Models.

Background: Mental illness costs the world economy over US2.5 Bn each year, including premature mortality, morbidity, and productivity losses. Multisector approaches are required to address the systemic drivers of mental health and ensure adequate service provision. There is an important role for economics to support priority setting, identify best value investments and inform optimal implementation. Mental health can be defined as a complex dynamic system where decision makers are challenged to prospectively manage the system over time. This protocol describes the approach to equip eight system dynamics (SD) models across Australia to support priority setting and guide portfolio investment decisions, tailored to local implementation context. Methods: As part of a multidisciplinary team, three interlinked protocols are developed; (i) the participatory process to codesign the models with local stakeholders and identify interventions for implementation, (ii) the technical protocol to develop the SD models to simulate the dynamics of the local population, drivers of mental health, the service system and clinical outcomes, and (iii) the economic protocol to detail how the SD models will be equipped to undertake a suite of economic analysis, incorporating health and societal perspectives. Models will estimate the cost of mental illness, inclusive of service costs (health and other sectors, where necessary), quality-adjusted life years (QALYs) lost, productivity costs and carer costs. To assess the value of investing (disinvesting) in interventions, economic analysis will include return-on-investment, cost-utility, cost benefit, and budget impact to inform affordability. Economic metrics are expected to be dynamic, conditional upon changing population demographics, service system capacities and the mix of interventions when synergetic or antagonistic interactions. To support priority setting, a portfolio approach will identify best value combinations of interventions, relative to a defined budget(s). User friendly dashboards will guide decision makers to use the SD models to inform resource allocation and generate business cases for funding. Discussion: Equipping SD models to undertake economic analysis is intended to support local priority setting and help optimise implementation regarding the best value mix of investments, timing and scale. The objectives are to improve allocative efficiency, increase mental health and economic productivity.

Applying systems approaches to stakeholder and community engagement and knowledge mobilisation in youth mental health system modelling.

BACKGROUND: There is a significant push to change the trajectory of youth mental ill-health and suicide globally. Ensuring that young people have access to services that meet their individual needs and are easily accessible is a priority. Genuine stakeholder engagement in mental health system design is critical to ensure that system strengthening is likely to be successful within these complex environments. There is limited literature describing engagement processes undertaken by research teams in mental health program implementation and planning. This protocol describes the methods that will be used to engage local communities using systems science methods to mobilize knowledge and action to strengthen youth mental health services. METHODS: Using participatory action research principles, the research team will actively engage with local communities to ensure genuine user-led participatory systems modelling processes and enhance knowledge mobilisation within research sites. Ensuring that culturally diverse and Aboriginal and Torres Strait Islander community voices are included will support this process. A rigorous site selection process will be undertaken to ensure that the community is committed and has capacity to actively engage in the research activities. Stakeholder engagement commences from the site selection process with the aim to build trust between researchers and key stakeholders. The research team will establish a variety of engagement resources and make opportunities available to each site depending on their local context, needs and audiences they wish to target during the process. DISCUSSION: This protocol describes the inclusive community engagement and knowledge mobilization process for the Right care, first time, where you live research Program. This Program will use an iterative and adaptive approach that considers the social, economic, and political context of each community and attempts to maximise research engagement. A theoretical framework for applying systems approaches to knowledge mobilization that is flexible will enable the implementation of a participatory action research approach. This protocol commits to a rigorous and genuine stakeholder engagement process that can be applied in mental health research implementation.

Optimizing Strategies for Improving Mental Health in Victoria, Australia during the COVID-19 Era: A System Dynamics Modelling Study.

The ongoing COVID-19 pandemic has impacted the mental health of populations and highlighted the limitations of mental health care systems. As the trajectory of the pandemic and the economic recovery are still uncertain, decision tools are needed to help evaluate the best interventions to improve mental health outcomes. We developed a system dynamics model that captures causal relationships among population, demographics, post-secondary education, health services, COVID-19 impact, and mental health outcomes. The study was conducted in the Australian state of Victoria. The model was calibrated using historical data and was stratified by age group and by geographic remoteness. Findings demonstrate that the most effective intervention combination includes economic, social, and health sector initiatives. Assertive post-suicide attempt care is the most impactful health sector intervention, but delaying implementation reduces the potency of its impact. Some evidence-based interventions, such as population-wide community awareness campaigns, are projected to worsen mental health outcomes when implemented on their own. Systems modelling offers a powerful decision-support tool to test alternative strategies for improving mental health outcomes in the Victorian context.

Presenting a comprehensive multi-scale evaluation framework for participatory modelling programs: A scoping review.

INTRODUCTION: Systems modelling and simulation can improve understanding of complex systems to support decision making, better managing system challenges. Advances in technology have facilitated accessibility of modelling by diverse stakeholders, allowing them to engage with and contribute to the development of systems models (participatory modelling). However, despite its increasing applications across a range of disciplines, there is a growing need to improve evaluation efforts to effectively report on the quality, importance, and value of participatory modelling. This paper aims to identify and assess evaluation frameworks, criteria, and/or processes, as well as to synthesize the findings into a comprehensive multi-scale framework for participatory modelling programs. MATERIALS AND METHODS: A scoping review approach was utilized, which involved a systematic literature search via Scopus in consultation with experts to identify and appraise records that described an evaluation framework, criteria, and/or process in the context of participatory modelling. This scoping review is registered with the Open Science Framework. RESULTS: The review identified 11 studies, which varied in evaluation purposes, terminologies, levels of examination, and time points. The review of studies highlighted areas of overlap and opportunities for further development, which prompted the development of a comprehensive multi-scale evaluation framework to assess participatory modelling programs across disciplines and systems modelling methods. The framework consists of four categories (Feasibility, Value, Change/Action, Sustainability) with 30 evaluation criteria, broken down across project-, individual-, group- and system-level impacts. DISCUSSION & CONCLUSION: The presented novel framework brings together a significant knowledge base into a flexible, cross-sectoral evaluation effort that considers the whole participatory modelling process. Developed through the rigorous synthesis of multidisciplinary expertise from existing studies, the application of the framework can provide the opportunity to understand practical future implications such as which aspects are particularly important for policy decisions, community learning, and the ongoing improvement of participatory modelling methods.

Participatory Methods for Systems Modeling of Youth Mental Health: Implementation Protocol.

BACKGROUND: Despite significant investment, mental health issues remain a leading cause of death among young people globally. Sophisticated decision analysis methods are needed to better understand the dynamic and multisector drivers of youth mental health. System modeling can help explore complex issues such as youth mental health and inform strategies to effectively respond to local needs and achieve lasting improvements. The advantages of engaging stakeholders in model development processes have long been recognized; however, the methods for doing so are often not well-described. OBJECTIVE: This paper aims to describe the participatory procedures that will be used to support systems modeling for national multisite implementation. The Right Care, First Time, Where You Live research program will focus on regional youth mental health applications of systems modeling in 8 different sites across Australia. METHODS: The participatory model development approach involves an iterative process of engaging with a range of participants, including people with lived experience of mental health issues. Their knowledge of the local systems, pathways, and drivers is combined with the academic literature and data to populate the models and validate their structure. The process centers around 3 workshops where participants interact and actively engage in group model-building activities to define, refine, and validate the systems models. This paper provides a detailed blueprint for the implementation of this process for mental health applications. RESULTS: The participatory modeling methods described in this paper will be implemented at 2 sites per year from 2022 to 2025. The 8 selected sites have been chosen to capture variations in important factors, including determinants of mental health issues and access to services. Site engagement commenced in August 2021, and the first modeling workshops are scheduled to commence in February 2022. CONCLUSIONS: Mental health system decision makers require tools to help navigate complex environments and leverage interdisciplinary problem-solving. Systems modeling can mobilize data from diverse sources to explore a range of scenarios, including the impact of interventions in different combinations and contexts. Involving stakeholders in the model development process ensures that the model findings are context-relevant and fit-for-purpose to inform decision-making. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/32988.

Sound Decision Making in Uncertain Times: Can Systems Modelling Be Useful for Informing Policy and Planning for Suicide Prevention?

The COVID-19 pandemic demonstrated the significant value of systems modelling in supporting proactive and effective public health decision making despite the complexities and uncertainties that characterise an evolving crisis. The same approach is possible in the field of mental health. However, a commonly levelled (but misguided) criticism prevents systems modelling from being more routinely adopted, namely, that the presence of uncertainty around key model input parameters renders a model useless. This study explored whether radically different simulated trajectories of suicide would result in different advice to decision makers regarding the optimal strategy to mitigate the impacts of the pandemic on mental health. Using an existing system dynamics model developed in August 2020 for a regional catchment of Western Australia, four scenarios were simulated to model the possible effect of the COVID-19 pandemic on levels of psychological distress. The scenarios produced a range of projected impacts on suicide deaths, ranging from a relatively small to a dramatic increase. Discordance in the sets of best-performing intervention scenarios across the divergent COVID-mental health trajectories was assessed by comparing differences in projected numbers of suicides between the baseline scenario and each of 286 possible intervention scenarios calculated for two time horizons; 2026 and 2041. The best performing intervention combinations over the period 2021-2041 (i.e., post-suicide attempt assertive aftercare, community support programs to increase community connectedness, and technology enabled care coordination) were highly consistent across all four COVID-19 mental health trajectories, reducing suicide deaths by between 23.9-24.6% against the baseline. However, the ranking of best performing intervention combinations does alter depending on the time horizon under consideration due to non-linear intervention impacts. These findings suggest that systems models can retain value in informing robust decision making despite uncertainty in the trajectories of population mental health outcomes. It is recommended that the time horizon under consideration be sufficiently long to capture the full effects of interventions, and efforts should be made to achieve more timely tracking and access to key population mental health indicators to inform model refinements over time and reduce uncertainty in mental health policy and planning decisions.

Participatory Systems Modelling for Youth Mental Health: An Evaluation Study Applying a Comprehensive Multi-Scale Framework.

The youth mental health sector is persistently challenged by issues such as service fragmentation and inefficient resource allocation. Systems modelling and simulation, particularly utilizing participatory approaches, is offering promise in supporting evidence-informed decision making with limited resources by testing alternative strategies in safe virtual environments before implementing them in the real world. However, improved evaluation efforts are needed to understand the critical elements involved in and to improve methods for implementing participatory modelling for youth mental health system and service delivery. An evaluation protocol is described to evaluate the feasibility, value, impact, and sustainability of participatory systems modelling in delivering advanced decision support capabilities for youth mental health. This study applies a comprehensive multi-scale evaluation framework, drawing on participatory action research principles as well as formative, summative, process, and outcome evaluation techniques. Novel data collection procedures are presented, including online surveys that incorporate gamification to enable social network analysis and patient journey mapping. The evaluation approach also explores the experiences of diverse stakeholders, including young people with lived (or living) experience of mental illness. Social and technical opportunities will be uncovered, as well as challenges implementing these interdisciplinary methods in complex settings to improve youth mental health policy, planning, and outcomes. This study protocol can also be adapted for broader international applications, disciplines, and contexts.

Partnering with Aboriginal and Torres Strait Islander Peoples: An Evaluation Study Protocol to Strengthen a Comprehensive Multi-Scale Evaluation Framework for Participatory Systems Modelling through Indigenous Paradigms and Methodologies.

The social and emotional wellbeing of young Aboriginal and Torres Strait Islander peoples should be supported through an Indigenous-led and community empowering approach. Applying systems thinking via participatory approaches is aligned with Aboriginal and Torres Strait Islander research paradigms and can be an effective method to deliver a decision support tool for mental health systems planning for Indigenous communities. Evaluations are necessary to understand the effectiveness and value of such methods, uncover protective and healing factors of social and emotional wellbeing, as well as to promote Aboriginal and Torres Strait Islander self-determination over allocation of funding and resources. This paper presents modifications to a published evaluation protocol for participatory systems modelling to align with critical Aboriginal and Torres Strait Islander guidelines and recommendations to support the social and emotional wellbeing of young people. This paper also presents a culturally relevant participatory systems modelling evaluation framework. Recognizing the reciprocity, strengths, and expertise Aboriginal and Torres Strait Islander methodologies can offer to broader research and evaluation practices, the amended framework presented in this paper facilitates empowering evaluation practices that should be adopted when working with Aboriginal and Torres Strait Islander peoples as well as when working with other diverse, non-Indigenous communities.

Positive impact of a long-running urban Aboriginal medical service midwifery program.

BACKGROUND: The Winnunga Nimmityjah Aboriginal Health Service Aboriginal Midwifery Access Program (AMAP) was established in 2001 to provide antenatal care, birth support and postnatal care to clients in the Australian Capital Territory (ACT). AIM: To describe the uptake and impact of AMAP services on access to antenatal care, behavioural risk factors and pregnancy outcomes and to compare the characteristics of AMAP clients with other women giving birth in the ACT. METHODS: A descriptive study of medical records for AMAP clients who gave birth in 2004-2008. OUTCOME MEASURES: maternal and baby characteristics, antenatal visits, behavioural risk factors and complications. Characteristics of AMAP clients were compared with the ACT Maternal and Perinatal Collection. RESULTS: Of 187 women, 11.2% were aged <20 years, 50.3% presented in the first trimester and 94.7% attended five or more antenatal visits. Of 193 babies, 17.1% were born preterm and 18.1% had low birthweight. Compared with the ACT Maternal and Perinatal Collection, Aboriginal and Torres Strait Islander AMAP clients had a higher smoking rate (63.8 vs 49.0%), a lower caesarean delivery rate (20.0 vs 27.6%), a slightly lower proportion of preterm babies (18.8 vs 21.6%) and a slightly lower proportion of low-birthweight babies (18.8 vs 21.0%). CONCLUSIONS: Aboriginal Midwifery Access Program provides high-quality antenatal care in a trusted environment. The high rate of smoking in pregnancy needs to be addressed.

Which Social, Economic, and Health Sector Strategies Will Deliver the Greatest Impacts for Youth Mental Health and Suicide Prevention? Protocol for an Advanced, Systems Modelling Approach.

Background: Current global challenges are generating extensive social disruption and uncertainty that have the potential to undermine the mental health, wellbeing, and futures of young people. The scale and complexity of challenges call for engagement with systems science-based decision analytic tools that can capture the dynamics and interrelationships between physical, social, economic, and health systems, and support effective national and regional responses. At the outset of the pandemic mental health-related systems models were developed for the Australian context, however, the extent to which findings are generalisable across diverse regions remains unknown. This study aims to explore the context dependency of systems modelling insights. Methods: This study will employ a comparative case study design, applying participatory system dynamics modelling across eight diverse regions of Australia to answer three primary research questions: (i) Will current regional differences in key youth mental health outcomes be exacerbated in forward projections due to the social and economic impacts of COVID-19?; (ii) What combination of social policies and health system strengthening initiatives will deliver the greatest impacts within each region?; (iii) To what extent are optimal strategic responses consistent across the diverse regions? We provide a detailed technical blueprint as a potential springboard for more timely construction and deployment of systems models in international contexts to facilitate a broader examination of the question of generalisability and inform investments in the mental health and wellbeing of young people in the post COVID-19 recovery. Discussion: Computer simulation is known as the third pillar of science (after theory and experiment). Simulation allows researchers and decision makers to move beyond what can be manipulated within the scale, time, and ethical limits of the experimental approach. Such learning when achieved collectively, has the potential to enhance regional self-determination, help move beyond incremental adjustments to the status quo, and catalyze transformational change. This research seeks to advance efforts to establish regional decision support infrastructure and empower communities to effectively respond. In addition, this research seeks to move towards an understanding of the extent to which systems modelling insights may be relevant to the global mental health response by encouraging researchers to use, challenge, and advance the existing work for scientific and societal progress.

The Impact of Physical Distancing Policies During the COVID-19 Pandemic on Health and Well-Being Among Australian Adolescents.

PURPOSE: Physical distancing policies in the state of New South Wales (Australia) were implemented on March 23, 2020, because of the COVID-19 pandemic. This study investigated changes in physical activity, dietary behaviors, and well-being during the early period of this policy. METHODS: A cohort of young people aged 13-19 years from Sydney (N = 582) were prospectively followed for 22 weeks (November 18, 2019, to April 19, 2020). Daily, weekly, and monthly trajectories of diet, physical activity, sedentary behavior, well-being, and psychological distress were collected via smartphone, using a series of ecological momentary assessments and smartphone sensors. Differences in health and well-being outcomes were compared pre- and post-implementation of physical distancing guidelines. RESULTS: After the implementation of physical distancing measures in NSW, there were significant decreases in physical activity (odds ratio [OR] = .53, 95% confidence interval [CI] = .34-.83), increases in social media and Internet use (OR = 1.86, 95% CI = 1.15-3.00), and increased screen time based on participants' smartphone screen state. Physical distancing measures were also associated with being alone in the previous hour (OR = 2.09, 95% CI: 1.33-3.28), decreases in happiness (OR = .38, 95% CI = .18-.82), and fast food consumption (OR = .46, 95% CI = .29-.73). CONCLUSIONS: Physical distancing and social restrictions had a contemporaneous impact on health and well-being outcomes associated with chronic disease among young people. As the pandemic evolves, it will be important to consider how to mitigate against any longer term health impacts of physical distancing restrictions.

'Turning the tide' on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling.

INTRODUCTION: Hyperglycemia in pregnancy (HIP, including gestational diabetes and pre-existing type 1 and type 2 diabetes) is increasing, with associated risks to the health of women and their babies. Strategies to manage and prevent this condition are contested. Dynamic simulation models (DSM) can test policy and program scenarios before implementation in the real world. This paper reports the development and use of an advanced DSM exploring the impact of maternal weight status interventions on incidence of HIP. METHODS: A consortium of experts collaboratively developed a hybrid DSM of HIP, comprising system dynamics, agent-based and discrete event model components. The structure and parameterization drew on a range of evidence and data sources. Scenarios comparing population-level and targeted prevention interventions were simulated from 2018 to identify the intervention combination that would deliver the greatest impact. RESULTS: Population interventions promoting weight loss in early adulthood were found to be effective, reducing the population incidence of HIP by 17.3% by 2030 (baseline ('business as usual' scenario)=16.1%, 95% CI 15.8 to 16.4; population intervention=13.3%, 95% CI 13.0 to 13.6), more than targeted prepregnancy (5.2% reduction; incidence=15.3%, 95% CI 15.0 to 15.6) and interpregnancy (4.2% reduction; incidence=15.5%, 95% CI 15.2 to 15.8) interventions. Combining targeted interventions for high-risk groups with population interventions promoting healthy weight was most effective in reducing HIP incidence (28.8% reduction by 2030; incidence=11.5, 95% CI 11.2 to 11.8). Scenarios exploring the effect of childhood weight status on entry to adulthood demonstrated significant impact in the selected outcome measure for glycemic regulation, insulin sensitivity in the short term and HIP in the long term. DISCUSSION: Population-level weight reduction interventions will be necessary to 'turn the tide' on HIP. Weight reduction interventions targeting high-risk individuals, while beneficial for those individuals, did not significantly impact forecasted HIP incidence rates. The importance of maintaining interventions promoting healthy weight in childhood was demonstrated.