Dynamic learning of individual-level suicidal ideation trajectories to enhance mental health care.

There has recently been an increase in ongoing patient-report routine outcome monitoring for individuals within clinical care, which has corresponded to increased longitudinal information about an individual. However, many models that are aimed at clinical practice have difficulty fully incorporating this information. This is in part due to the difficulty in dealing with the irregularly time-spaced observations that are common in clinical data. Consequently, we built individual-level continuous-time trajectory models of suicidal ideation for a clinical population (N = 585) with data collected via a digital platform. We demonstrate how such models predict an individual's level and variability of future suicide ideation, with implications for the frequency that individuals may need to be observed. These individual-level predictions provide a more personalised understanding than other predictive methods and have implications for enhanced measurement-based care.

The influence of economic policies on social environments and mental health.

Despite increased advocacy and investments in mental health systems globally, there has been limited progress in reducing mental disorder prevalence. In this paper, we argue that meaningful advancements in population mental health necessitate addressing the fundamental sources of shared distress. Using a systems perspective, economic structures and policies are identified as the potential cause of causes of mental ill-health. Neoliberal ideologies, prioritizing economic optimization and continuous growth, contribute to the promotion of individualism, job insecurity, increasing demands on workers, parental stress, social disconnection and a broad range of manifestations well-recognized to erode mental health. We emphasize the need for mental health researchers and advocates to increasingly engage with the economic policy discourse to draw attention to mental health and well-being implications. We call for a shift towards a well-being economy to better align commercial interests with collective well-being and social prosperity. The involvement of individuals with lived mental ill-health experiences, practitioners and researchers is needed to mobilize communities for change and influence economic policies to safeguard well-being. Additionally, we call for the establishment of national mental wealth observatories to inform coordinated health, social and economic policies and realize the transition to a more sustainable well-being economy that offers promise for progress on population mental health outcomes.

Malgré une meilleure sensibilisation et des investissements accrus dans les systèmes de santé mentale à travers le monde, les progrès en matière de réduction du degré de prévalence des troubles mentaux demeurent très limités. Dans le présent document, nous estimons que, pour réaliser des avancées au niveau de la santé mentale des populations, il est impératif de s'attaquer aux sources de cette détresse collective. En adoptant une perspective systémique, force est de constater que les politiques et structures économiques constituent les causes potentielles d'une mauvaise santé mentale. Les idéologies néolibérales, qui privilégient l'optimisation économique et la croissance ininterrompue, contribuent à promouvoir l'individualisme, l'insécurité professionnelle, la pression pesant sur les travailleurs, le stress parental, l'isolement social et un large éventail de facteurs associés à une dégradation de la santé mentale. Nous insistons sur la nécessité de faire appel à des chercheurs et défenseurs actifs dans ce domaine, afin de jouer un rôle dans la politique économique en attirant l'attention sur les implications pour le bien-être et la santé mentale. Nous plaidons pour une transition vers une économie du bien-être visant à rapprocher les intérêts commerciaux de la prospérité sociale et collective. L'intervention de personnes ayant été confrontées à des troubles mentaux, de praticiens et de chercheurs est nécessaire pour mobiliser les communautés en faveur d'un changement et influencer les politiques économiques pour préserver le bien-être. Par ailleurs, nous militons pour la création d'observatoires nationaux de la santé mentale qui serviront à orienter des politiques économiques, sociales et sanitaires coordonnées, mais aussi à favoriser l'évolution vers une économie du bien-être plus durable, laissant entrevoir une amélioration de la santé mentale au sein de la population.

A pesar del aumento de la promoción y las inversiones en sistemas de salud mental en todo el mundo, los avances en la reducción de la prevalencia de los trastornos mentales han sido limitados. En este documento, sostenemos que para lograr avances significativos en la salud mental de la población es necesario abordar las fuentes fundamentales de la angustia compartida. Mediante una perspectiva sistémica, las estructuras y políticas económicas se identifican como la posible causa de los problemas de salud mental. Las ideologías neoliberales, que priorizan la optimización económica y el crecimiento continuo, contribuyen al fomento del individualismo, la inseguridad laboral, el aumento de las exigencias a los trabajadores, el estrés parental, la desconexión social y una gran variedad de manifestaciones bien reconocidas que perjudican la salud mental. Insistimos en la necesidad de que los investigadores y los defensores de la salud mental se impliquen cada vez más en el discurso de la política económica para atraer la atención sobre las implicaciones para la salud mental y el bienestar. Pedimos un cambio hacia una economía del bienestar para alinear mejor los intereses comerciales con el bienestar colectivo y la prosperidad social. Para movilizar a las comunidades en favor del cambio e influir en las políticas económicas con el fin de salvaguardar el bienestar, es necesaria la participación de personas que han padecido enfermedades mentales, profesionales e investigadores. Además, pedimos la creación de observatorios nacionales de bienestar mental que sirvan de base a las políticas sanitarias, sociales y económicas coordinadas y permitan la transición a una economía del bienestar más sostenible, que ofrezca perspectivas de progreso en los resultados de salud mental de la población.

Navigating a stable transition to the age of intelligence: A mental wealth perspective.

In the grand narrative of technological evolution, we are transitioning from the "Age of Information" to the "Age of Intelligence." Rapid advancements in generative artificial intelligence (AI) are set to reshape society, revolutionize industries, and change the nature of work, challenging our traditional understanding of the dynamics of the economy and its relationship with human productivity and societal prosperity. As we brace for this transformative shift, promising advancements in healthcare, education, productivity, and more, there are concerns of large-scale job loss, mental health repercussions, and risks to social stability and democracy. This paper proposes the concept of Mental Wealth as an action framework that supports nations to proactively position themselves for a smooth transition to the Age of Intelligence while fostering economic and societal prosperity.

Developing a Decision Aid for Clinical Obesity Services in the Real World: the DACOS Nationwide Pilot Study.

PURPOSE: The purpose of this study is to develop a decision aid tool using "real-world" data within the Australian health system to predict weight loss after bariatric surgery and non-surgical care. MATERIALS AND METHODS: We analyzed patient record data (aged 16+years) from initial review between 2015 and 2020 with 6-month (n=219) and 9-/12-month (n=153) follow-ups at eight clinical obesity services. Primary outcome was percentage total weight loss (%TWL) at 6 months and 9/12 months. Predictors were selected by statistical evidence (p<0.20), effect size (±2%), and clinical judgment. Multiple linear regression and bariatric surgery were used to create simple predictive models. Accuracy was measured using percentage of predictions within 5% of the observed value, and sensitivity and specificity for predicting target weight loss of 5% (non-surgical care) and 15% (bariatric surgery). RESULTS: Observed %TWL with bariatric surgery vs. non-surgical care was 19% vs. 5% at 6 months and 22% vs. 5% at 9/12 months. Predictors at 6 months with intercept (non-surgical care) of 6% include bariatric surgery (+11%), BMI>60 (-3%), depression (-2%), anxiety (-2%), and eating disorder (-2%). Accuracy, sensitivity, and specificity were 58%, 69%, and 56%. Predictors at 9/12 months with intercept of 5% include bariatric surgery (+15%), type 2 diabetes (+5%), eating disorder (+4%), fatty liver (+2%), atrial fibrillation (-4%), osteoarthritis (-3%), sleep/mental disorders (-2-3%), and ≥10 alcohol drinks/week (-2%). Accuracy, sensitivity, and specificity were 55%, 86%, and 53%. CONCLUSION: Clinicians may use DACOS to discuss potential weight loss predictors with patients after surgery or non-surgical care.

The temporal dependencies between social, emotional and physical health factors in young people receiving mental healthcare: a dynamic Bayesian network analysis.

AIMS: The needs of young people attending mental healthcare can be complex and often span multiple domains (e.g., social, emotional and physical health factors). These factors often complicate treatment approaches and contribute to poorer outcomes in youth mental health. We aimed to identify how these factors interact over time by modelling the temporal dependencies between these transdiagnostic social, emotional and physical health factors among young people presenting for youth mental healthcare. METHODS: Dynamic Bayesian networks were used to examine the relationship between mental health factors across multiple domains (social and occupational function, self-harm and suicidality, alcohol and substance use, physical health and psychiatric syndromes) in a longitudinal cohort of 2663 young people accessing youth mental health services. Two networks were developed: (1) 'initial network', that shows the conditional dependencies between factors at first presentation, and a (2) 'transition network', how factors are dependent longitudinally. RESULTS: The 'initial network' identified that childhood disorders tend to precede adolescent depression which itself was associated with three distinct pathways or illness trajectories; (1) anxiety disorder; (2) bipolar disorder, manic-like experiences, circadian disturbances and psychosis-like experiences; (3) self-harm and suicidality to alcohol and substance use or functioning. The 'transition network' identified that over time social and occupational function had the largest effect on self-harm and suicidality, with direct effects on ideation (relative risk [RR], 1.79; CI, 1.59-1.99) and self-harm (RR, 1.32; CI, 1.22-1.41), and an indirect effect on attempts (RR, 2.10; CI, 1.69-2.50). Suicide ideation had a direct effect on future suicide attempts (RR, 4.37; CI, 3.28-5.43) and self-harm (RR, 2.78; CI, 2.55-3.01). Alcohol and substance use, physical health and psychiatric syndromes (e.g., depression and anxiety, at-risk mental states) were independent domains whereby all direct effects remained within each domain over time. CONCLUSIONS: This study identified probable temporal dependencies between domains, which has causal interpretations, and therefore can provide insight into their differential role over the course of illness. This work identified social, emotional and physical health factors that may be important early intervention and prevention targets. Improving social and occupational function may be a critical target due to its impacts longitudinally on self-harm and suicidality. The conditional independence of alcohol and substance use supports the need for specific interventions to target these comorbidities.

Patterns of emergency department presentations for a youth mental health cohort: data-linkage cohort study.

BACKGROUND: Primary youth mental health services in Australia have increased access to care for young people, yet the longer-term outcomes and utilisation of other health services among these populations is unclear. AIMS: To describe the emergency department presentation patterns of a help-seeking youth mental health cohort. METHOD: Data linkage was performed to extract Emergency Department Data Collection registry data (i.e. emergency department presentations, pattern of re-presentations) for a transdiagnostic cohort of 7024 youths (aged 12-30 years) who presented to mental health services. Outcome measures were pattern of presentations and reason for presentations (i.e. mental illness; suicidal behaviours and self-harm; alcohol and substance use; accident and injury; physical illness; and other). RESULTS: During the follow-up period, 5372 (76.5%) had at least one emergency department presentation. The presentation rate was lower for males (IRR = 0.87, 95% CI 0.86-0.89) and highest among those aged 18 to 24 (IRR = 1.117, 95% CI 1.086-1.148). Almost one-third (31.12%) had an emergency department presentation that was directly associated with mental illness or substance use, and the most common reasons for presentation were for physical illness and accident or injury. Index visits for mental illness or substance use were associated with a higher rate of re-presentation. CONCLUSIONS: Most young people presenting to primary mental health services also utilised emergency services. The preventable and repeated nature of many presentations suggests that reducing the ongoing secondary risks of mental disorders (i.e. substance misuse, suicidality, physical illness) could substantially improve the mental and physical health outcomes of young people.

A multidimensional approach for differentiating the clinical needs of young people presenting for primary mental health care.

OBJECTIVES: There is an ongoing necessity to match clinical interventions with the multidimensional needs of young people. A key step toward better service planning and the design of optimal models of care is to use multidimensional assessment to understand the clinical needs of those presenting to primary mental health care. METHODS: 1284 people aged 12-25 years presenting to primary youth mental health services completed an online assessment at service entry. Latent class analysis was conducted for seven scales assessing anxiety, depression, psychosis, mania, functioning (indexed by Work and Social Adjustment Scale), and suicidality. RESULTS: A three-class solution was identified as the optimal solution. Class 1 (n = 305, 23.75%), an early illness stage group, had low and mixed symptomatology with limited functional impairment, class 2 (n = 353, 27.49%) was made up of older persons with established depression and functional impairment, and class 3 (n = 626, 48.75%) had very high and complex needs, with functional impairment, suicidality, and at-risk mental states (psychosis or mania). Additional differentiating characteristics included psychological distress, circadian disturbances, social support, mental health history, eating disorder behaviours, and symptoms of post-traumatic stress disorder. CONCLUSIONS: A large proportion of help-seeking young people present with symptoms and functional impairment that may exceed the levels of care available from basic primary care or brief intervention services. These subgroups highlight the importance of multidimensional assessments to determine appropriate service pathways and care options.

Bi-stability and critical transitions in mental health care systems: a model-based analysis.

BACKGROUND: Delayed initiation and early discontinuation of treatment due to limited availability and accessibility of services may often result in people with mild or moderate mental disorders developing more severe disorders, leading to an increase in demand for specialised care that would be expected to further restrict service availability and accessibility (due to increased waiting times, higher out-of-pocket costs, etc.). METHODS: We developed a simple system dynamics model of the interaction of specialised services capacity and disease progression to examine the impact of service availability and accessibility on the effectiveness and efficiency of mental health care systems. RESULTS: Model analysis indicates that, under certain conditions, increasing services capacity can precipitate an abrupt, step-like transition from a state of persistently high unmet need for specialised services to an alternative, stable state in which people presenting for care receive immediate and effective treatment. This qualitative shift in services system functioning results from a 'virtuous cycle' in which increasing treatment-dependent recovery among patients with mild to moderate disorders reduces the number of severely ill patients requiring intensive and/or prolonged treatment, effectively 'releasing' services capacity that can be used to further reduce the disease progression rate. We present an empirical case study of tertiary-level child and adolescent mental health services in the Australian state of South Australia demonstrating that the conditions under which such critical transitions can occur apply in real-world services systems. CONCLUSIONS: Policy and planning decisions aimed at increasing specialised services capacity have the potential to dramatically increase the effectiveness and efficiency of mental health care systems, promoting long-term sustainability and resilience in the face of future threats to population mental health (e.g., economic crises, natural disasters, global pandemics).

Clinical staging and the differential risks for clinical and functional outcomes in young people presenting for youth mental health care.

BACKGROUND: Clinical staging proposes that youth-onset mental disorders develop progressively, and that active treatment of earlier stages should prevent progression to more severe disorders. This retrospective cohort study examined the longitudinal relationships between clinical stages and multiple clinical and functional outcomes within the first 12 months of care. METHODS: Demographic and clinical information of 2901 young people who accessed mental health care at age 12-25 years was collected at predetermined timepoints (baseline, 3 months, 6 months, 12 months). Initial clinical stage was used to define three fixed groups for analyses (stage 1a: 'non-specific anxious or depressive symptoms', 1b: 'attenuated mood or psychotic syndromes', 2+: 'full-threshold mood or psychotic syndromes'). Logistic regression models, which controlled for age and follow-up time, were used to compare clinical and functional outcomes (role and social function, suicidal ideation, alcohol and substance misuse, physical health comorbidity, circadian disturbances) between staging groups within the initial 12 months of care. RESULTS: Of the entire cohort, 2093 young people aged 12-25 years were followed up at least once over the first 12 months of care, with 60.4% female and a baseline mean age of 18.16 years. Longitudinally, young people at stage 2+ were more likely to develop circadian disturbances (odds ratio [OR]=2.58; CI 1.60-4.17), compared with individuals at stage 1b. Additionally, stage 1b individuals were more likely to become disengaged from education/employment (OR=2.11, CI 1.36-3.28), develop suicidal ideations (OR=1.92; CI 1.30-2.84) and circadian disturbances (OR=1.94, CI 1.31-2.86), compared to stage 1a. By contrast, we found no relationship between clinical stage and the emergence of alcohol or substance misuse and physical comorbidity. CONCLUSIONS: The differential rates of emergence of poor clinical and functional outcomes between early versus late clinical stages support the clinical staging model's assumptions about illness trajectories for mood and psychotic syndromes. The greater risk of progression to poor outcomes in those who present with more severe syndromes may be used to guide specific intervention packages.

Measuring, Modeling, and Forecasting the Mental Wealth of Nations.

The COVID-19 pandemic has exposed the deep links and fragility of economic, health and social systems. Discussions of reconstruction include renewed interest in moving beyond GDP and recognizing "human capital", "brain capital", "mental capital", and "wellbeing" as assets fundamental to economic reimagining, productivity, and prosperity. This paper describes how the conceptualization of Mental Wealth provides an important framing for measuring and shaping social and economic renewal to underpin healthy, productive, resilient, and thriving communities. We propose a transdisciplinary application of systems modeling to forecast a nation's Mental Wealth and understand the extent to which policy-mediated changes in economic, social, and health sectors could enhance collective mental health and wellbeing, social cohesion, and national prosperity. Specifically, simulation will allow comparison of the projected impacts of a range of cross-sector strategies (education sector, mental health system, labor market, and macroeconomic reforms) on GDP and national Mental Wealth, and provide decision support capability for future investments and actions to foster Mental Wealth. Finally, this paper introduces the Mental Wealth Initiative that is harnessing complex systems science to examine the interrelationships between social, commercial, and structural determinants of mental health and wellbeing, and working to empirically challenge the notion that fostering universal social prosperity is at odds with economic and commercial interests.

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.

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.

The Impact of Technology-Enabled Care Coordination in a Complex Mental Health System: A Local System Dynamics Model.

BACKGROUND: Prior to the COVID-19 pandemic, major shortcomings in the way mental health care systems were organized were impairing the delivery of effective care. The mental health impacts of the pandemic, the recession, and the resulting social dislocation will depend on the extent to which care systems will become overwhelmed and on the strategic investments made across the system to effectively respond. OBJECTIVE: This study aimed to explore the impact of strengthening the mental health system through technology-enabled care coordination on mental health and suicide outcomes. METHODS: A system dynamics model for the regional population catchment of North Coast New South Wales, Australia, was developed that incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and suicidal behavior. The model reproduced historic time series data across a range of outcomes and was used to evaluate the relative impact of a set of scenarios on attempted suicide (ie, self-harm hospitalizations), suicide deaths, mental health-related emergency department (ED) presentations, and psychological distress over the period from 2021 to 2030. These scenarios include (1) business as usual, (2) increase in service capacity growth rate by 20%, (3) standard telehealth, and (4) technology-enabled care coordination. Each scenario was tested using both pre- and post-COVID-19 social and economic conditions. RESULTS: Technology-enabled care coordination was forecast to deliver a reduction in self-harm hospitalizations and suicide deaths by 6.71% (95% interval 5.63%-7.87%), mental health-related ED presentations by 10.33% (95% interval 8.58%-12.19%), and the prevalence of high psychological distress by 1.76 percentage points (95% interval 1.35-2.32 percentage points). Scenario testing demonstrated that increasing service capacity growth rate by 20% or standard telehealth had substantially lower impacts. This pattern of results was replicated under post-COVID-19 conditions with technology-enabled care coordination being the only tested scenario, which was forecast to reduce the negative impact of the pandemic on mental health and suicide. CONCLUSIONS: The use of technology-enabled care coordination is likely to improve mental health and suicide outcomes. The substantially lower effectiveness of targeting individual components of the mental health system (ie, increasing service capacity growth rate by 20% or standard telehealth) reiterates that strengthening the whole system has the greatest impact on patient outcomes. Investments into more of the same types of programs and services alone will not be enough to improve outcomes; instead, new models of care and the digital infrastructure to support them and their integration are needed.

Using Digital Technologies to Facilitate Care Coordination Between Youth Mental Health Services: A Guide for Implementation.

Enhanced care coordination is essential to improving access to and navigation between youth mental health services. By facilitating better communication and coordination within and between youth mental health services, the goal is to guide young people quickly to the level of care they need and reduce instances of those receiving inappropriate care (too much or too little), or no care at all. Yet, it is often unclear how this goal can be achieved in a scalable way in local regions. We recommend using technology-enabled care coordination to facilitate streamlined transitions for young people across primary, secondary, more specialised or hospital-based care. First, we describe how technology-enabled care coordination could be achieved through two fundamental shifts in current service provisions; a model of care which puts the person at the centre of their care; and a technology infrastructure that facilitates this model. Second, we detail how dynamic simulation modelling can be used to rapidly test the operational features of implementation and the likely impacts of technology-enabled care coordination in a local service environment. Combined with traditional implementation research, dynamic simulation modelling can facilitate the transformation of real-world services. This work demonstrates the benefits of creating a smart health service infrastructure with embedded dynamic simulation modelling to improve operational efficiency and clinical outcomes through participatory and data driven health service planning.

A Pilot Case-Control Study of the Social Media Activity Following Cluster and Non-Cluster Suicides in Australia.

Social media may play a role in the "contagion" mechanism thought to underpin suicide clusters. Our pilot case-control study presented a novel methodological approach to examining whether Facebook activity following cluster and non-cluster suicides differed. We used a scan statistic to identify suicide cluster cases occurring in spatiotemporal clusters and matched each case to 10 non-cluster control suicides. We identified the Facebook accounts of 3/48 cluster cases and 20/480 non-cluster controls and their respective friends-lists and retrieved 48 posthumous posts and replies (text segments) referring to the deceased for the former and 606 for the latter. We examined text segments for "putatively harmful" and "putatively protective" content (e.g., discussion of the suicide method vs. messages discouraging suicidal acts). We also used concept mapping, word-emotion association, and sentiment analysis and gauged user reactions to posts using the reactions-to-posts ratio. We found no "putatively harmful" or "putatively protective" content following any suicides. However, "family" and "son" concepts were more common for cluster cases and "xx", "sorry" and "loss" concepts were more common for non-cluster controls, and there were twice as many surprise- and disgust-associated words for cluster cases. Posts pertaining to non-cluster controls were four times as receptive as those about cluster cases. We hope that the approach we have presented may help to guide future research to explain suicide clusters and social-media contagion.

Policy options for endgame planning in tobacco control: a simulation modelling study.

OBJECTIVE: To investigate the potential impacts of several tobacco control interventions on adult daily smoking prevalence in the Australian state of Queensland, using a system dynamics model codeveloped with local and national stakeholders. METHODS: Eight intervention scenarios were simulated and compared with a reference scenario (business as usual), in which all tobacco control measures currently in place are maintained unchanged until the end of the simulation period (31 December 2037). FINDINGS: Under the business as usual scenario, adult daily smoking prevalence is projected to decline from 11.8% in 2017 to 5.58% in 2037. A sustained 50% increase in antismoking advertising exposure from 2018 reduces projected prevalence in 2037 by 0.80 percentage points. Similar reductions are projected with the introduction of tobacco wholesaler and retailer licensing schemes that either permit or prohibit tobacco sales by alcohol-licensed venues (0.65 and 1.73 percentage points, respectively). Increasing the minimum age of legal supply of tobacco products substantially reduces adolescent initiation, but has minimal impact on smoking prevalence in the adult population over the simulation period. Sustained reductions in antismoking advertising exposure of 50% and 100% from 2018 increase projected adult daily smoking prevalence in 2037 by 0.88 and 1.98 percentage points, respectively. CONCLUSIONS: These results suggest that any prudent approach to endgame planning should seek to build on rather than replace existing tobacco control measures that have proved effective to date. Additional interventions that can promote cessation are expected to be more successful in reducing smoking prevalence than interventions focussing exclusively on preventing initiation.

'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.

The Impact of Reducing Psychiatric Beds on Suicide Rates.

There has been ongoing debate regarding the impact of reductions in psychiatric beds on suicide rates, and the potential effect of reallocation of acute hospital funding to community-based mental health programs and services. Computer simulation offers significant value in advancing such debate by providing a robust platform for exploring strategic resource allocation scenarios before they are implemented in the real world. We report an application that demonstrates a threshold effect of cuts to psychiatric beds on suicide rates and the role of context specific variations in population, behavioral, and service use dynamics in determining where that threshold lies. Findings have important implications for regional decision-making regarding resource allocation for suicide prevention.