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Patients with depression and bipolar disorder have previously been shown to have impaired white matter (WM) integrity compared with healthy controls. This study aimed to investigate potential sex differences that may provide further insight into the pathophysiology of these highly debilitating mood disorders.Participants aged 17 to 30 years (168 with depression [60% females], 107 with bipolar disorder [74% females], and 61 controls [64% females]) completed clinical assessment, self-report measures, and a neuropsychological assessment battery. Participants also underwent magnetic resonance imaging from which diffusion tensor imaging data were collected among five fronto-limbic WM tracts: cingulum bundle (cingulate gyrus and hippocampus subsections), fornix, stria terminalis, and the uncinate fasciculus. Mean fractional anisotropy (FA) scores were compared between groups using analyses of variance with sex and diagnosis as fixed factors.Among the nine WM tracts analyzed, one revealed a significant interaction between sex and diagnosis, controlling for age. Male patients with bipolar disorder had significantly lower FA scores in the fornix compared with the other groups. Furthermore, partial correlations revealed a significant positive association between FA scores for the fornix and psychomotor speed.Our findings suggest that males with bipolar disorder may be at increased risk of disruptions in WM integrity, especially in the fornix, which is thought to be responsible for a range of cognitive functions. More broadly, our findings suggest that sex differences may exist in WM integrity and thereby alter our understanding of the pathophysiology of mood disorders.

Background Understanding premature mortality risk from suicide and other causes in youth mental health cohorts is essential for delivering effective clinical interventions and secondary prevention strategies. Aims To establish premature mortality risk in young people accessing early intervention mental health services and identify predictors of mortality. Method State-wide data registers of emergency departments, hospital admissions and mortality were linked to the Brain and Mind Research Register, a longitudinal cohort of 7081 young people accessing early intervention care, between 2008 and 2020. Outcomes were mortality rates and age-standardised mortality ratios (SMR). Cox regression was used to identify predictors of all-cause mortality and deaths due to suicide or accident. Results There were 60 deaths (male 63.3%) during the study period, 25 (42%) due to suicide, 19 (32%) from accident or injury and eight (13.3%) where cause was under investigation. All-cause SMR was 2.0 (95% CI 1.6–2.6) but higher for males (5.3, 95% CI 3.8–7.0). The mortality rate from suicide and accidental deaths was 101.56 per 100 000 person-years. Poisoning, whether intentional or accidental, was the single greatest primary cause of death (26.7%). Prior emergency department presentation for poisoning (hazard ratio (HR) 4.40, 95% CI 2.13–9.09) and psychiatric admission (HR 4.01, 95% CI 1.81–8.88) were the strongest predictors of mortality. Conclusion Premature mortality in young people accessing early intervention mental health services is greatly increased relative to population. Prior health service use and method of self-harm are useful predictors of future mortality. Enhanced care pathways following emergency department presentations should not be limited to those reporting suicidal ideation or intent.

BACKGROUND As the demand for youth mental health care continues to rise, managing wait times and reducing treatment delays are key challenges to delivering timely and quality care. Clinical staging is a heuristic model for youth mental health that can stratify care allocation according to an individual’s risk of illness progression. The application of staging has been traditionally limited to trained clinicians, yet if digital technologies could be leveraged to apply clinical staging, then this could increase the scalability and utility of this model in services. OBJECTIVE The aim of this study is to validate a digital algorithm to accurately differentiate young people at lower and higher risk of developing mental disorders. METHODS The cohort comprised 131 young people, aged between 16 to 25 years, who presented to youth mental health services in Australia for the first time between November 2018 to March 2021. Clinical stages (either stage 1a or stage 1b+) were allocated independently by expert psychiatrists and compared to the digital algorithm based on a multidimensional self-report questionnaire. RESULTS Of the 131 participants, the mean (SD) age was 20.3 (2.4) years and 94 (71.8%) were female. Ninety-one percent of clinical stage ratings were concordant between the digital algorithm and the expert ratings with a substantial interrater agreement (κ=0.67, P CONCLUSIONS This novel digital algorithm is sufficiently robust to be used as an adjunctive decision support tool to stratify care and assist with demand management in youth mental health services. This work could transform care pathways and expedite care allocation for those in early stages of common anxiety and depressive disorders. Between 11% and 27% of young people presenting for care may be suitable for low intensity online or brief interventions, creating additional clinical capacity to be directed towards those who are in stage 1b+ for further assessment and intervention.

BACKGROUND As the demand for youth mental health care continues to rise, managing wait times and reducing treatment delays are key challenges to delivering timely and quality care. Clinical staging is a heuristic model for youth mental health that can stratify care allocation according to an individual’s risk of illness progression. The application of staging has been traditionally limited to trained clinicians, yet if digital technologies could be leveraged to apply clinical staging, then this could increase the scalability and utility of this model in services. OBJECTIVE The aim of this proof-of-concept study is to validate a digital algorithm to accurately differentiate young people at lower and higher risk of developing mental disorders. METHODS The cohort comprised 131 young people, aged between 16 to 25 years, who presented to youth mental health services in Australia for the first time between November 2018 to March 2021. Clinical stages (either stage 1a or stage 1b+) were allocated independently by expert psychiatrists and compared to the digital algorithm based on a multidimensional self-report questionnaire. RESULTS Of the 131 participants, the mean (SD) age was 20.3 (2.4) years and 94 (71.8%) were female. Ninety-one percent of clinical stage ratings were concordant between the digital algorithm and the expert ratings with a substantial interrater agreement (κ=0.67, P CONCLUSIONS This novel digital algorithm is sufficiently robust to be used as an adjunctive decision support tool to stratify care and assist with demand management in youth mental health services. This work could transform care pathways and expedite care allocation for those in early stages of common anxiety and depressive disorders. Between 11% and 27% of young people presenting for care may be suitable for low intensity online or brief interventions, creating additional clinical capacity to be directed towards those who are stage 1b+ for further assessment and intervention.

Objective To identify trajectories of social and occupational functioning in young people during the two years after presenting for early intervention mental health care; to identify demographic and clinical factors that influence these trajectories. Design Longitudinal, observational study of young people presenting for mental health care. Setting Two primary care-based early intervention mental health services at the Brain and Mind Centre (University of Sydney), 1 June 2008 - 31 July 2018. Participants 1510 people aged 12-25 years who had presented with anxiety, mood, or psychotic disorders, for whom two years' follow-up data were available for analysis. Main outcome measures Latent class trajectories of social and occupational functioning based on growth mixture modelling of Social and Occupational Assessment Scale (SOFAS) scores. Results We identified four trajectories of functioning during the first two years of care: deteriorating and volatile (733 participants, 49%); persistent impairment (237, 16%); stable good functioning (291, 19%); and improving, but late recurrence (249, 16%). The less favourable trajectories (deteriorating and volatile; persistent impairment) were associated with physical comorbidity, not being in education, employment, or training, having substance-related disorders, having been hospitalised, and having a childhood onset mental disorder, psychosis-like experiences, or a history of self-harm or suicidality. Conclusions Two in three young people with emerging mental disorders did not experience meaningful improvement in social and occupational functioning during two years of early intervention care. Most functional trajectories were also quite volatile, indicating the need for dynamic service models that emphasise multidisciplinary interventions and measurement-based care.

ObjectivesThe aim of this study was to determine the prevalence of disordered eating in young people attending a headspace centre, an enhanced primary care centre providing early intervention services for mental health disorders for young people aged 12–25 years, in metropolitan Sydney.DesignCross-sectional assessment of disordered eating symptoms and behaviours.SettingAn enhanced primary care youth mental health service in inner urban Sydney, Australia.ParticipantsA sequential cohort of 530 young people aged 14–26 years presenting to headspace Camperdown for support with mental health concerns.Outcome measuresParticipants completed a series of questionnaires online which included items assessing the presence of eating disorder symptoms and behaviours.ResultsOver one-third of young people aged 14–26 years presenting to headspace Camperdown in a 22-month period reported symptoms of disordered eating. Of these, 32% endorsed overeating behaviours, 25% endorsed dietary restriction and 8% reported purging behaviours. In total, 44% reported engaging in one of more of these behaviours on a regular basis. Almost half reported experiencing significant shape and weight concerns. Eating disorder behaviours were particularly prevalent among female and gender-diverse participants (48% of females and 46% of gender-diverse participants compared with 35% of males) and overall scores across all of the eating disorder and body image items assessed were significantly higher for female participants compared with males.ConclusionsDisordered eating behaviours and symptoms are common among those presenting to youth mental health primary care services. Proactive screening for these behaviours presents opportunities for early detection and specific interventions.Trial registration numberACTRN12618001676202; Results.

An ongoing need exists for innovation in service delivery to ensure that mental health services deliver high-quality treatment and prevention in the population. This Special Article proposes the adoption of “staged care” as a population health–oriented service delivery model for packages of specialized services delivered largely in ambulatory care settings for individuals with common affective disorders. Staged care integrates measures of clinical need alongside clinical stage and personal choice to select hierarchically arranged service packages for individuals. Packages then vary according to the intensity, duration, and mix of treatment options. This Special Article describes five levels of care in staged care: self- or family-directed monitoring and management, low-intensity services, moderate-intensity services, high-intensity services, and acute and specialist community mental health services. The care environment, treatment team, and length of treatment are also described, and provisional criteria are specified for assigning individuals to different care levels on the basis of current clinical need and clinical stage. Staged care is presented as a model that guides treatment selection and health service delivery to ensure that the high-quality care aims of “right care first time” and prevention are achieved and optimal use of available resources is considered.

Background The World Economic Forum has recently highlighted substantial problems in mental health service provision and called for the rapid deployment of smarter, digitally-enhanced health services as a means to facilitate effective care coordination and address issues of demand. In mental health, the biggest enabler of digital solutions is the implementation of an effective model of care that is facilitated by integrated health information technologies (HITs); the latter ensuring the solution is easily accessible, scalable and sustainable. The University of Sydney’s Brain and Mind Centre (BMC) has developed an innovative digital health solution – delivered through the Youth Mental Health and Technology Program – which incorporates two components: 1) a highly personalised and measurement-based (data-driven) model of youth mental health care; and 2) an industrial grade HIT registered on the Australian Register of Therapeutic Goods. This paper describes a research protocol to evaluate the impact of implementing the BMC’s digital health solution into youth mental health services (i.e. headspace - a highly accessible, youth-friendly integrated service that responds to the mental health, physical health, alcohol or other substance use, and vocational concerns of young people aged 12 to 25 years) within urban and regional areas of Australia. Methods The digital health solution will be implemented into participating headspace centres using a naturalistic research design. Quantitative and qualitative data will be collected from headspace health professionals, service managers and administrators, as well as from lead agency and local Primary Health Network (PHN) staff, via service audits, Implementation Officer logs, online surveys, and semi-structured interviews, at baseline and then three-monthly intervals over the course of 12 months. Discussion At the time of publication, six headspace centres had been recruited to this study and had commenced implementation and impact evaluation. The first results are expected to be submitted for publication in 2021. This study will focus on the impact of implementing a digital health solution at both a service and staff level, and will evaluate digital readiness of service and staff adoption; quality, usability and acceptability of the solution by staff; staff self-reported clinical competency; overall impact on headspace centres as well as their lead agencies and local PHNs; and social return on investment.

Background Reducing suicidal behaviour (SB) is a critical public health issue globally. The complex interplay of social determinants, service system factors, population demographics, and behavioural dynamics makes it extraordinarily difficult for decision makers to determine the nature and balance of investments required to have the greatest impacts on SB. Real-world experimentation to establish the optimal targeting, timing, scale, frequency, and intensity of investments required across the determinants is unfeasible. Therefore, this study harnesses systems modelling and simulation to guide population-level decision making that represent best strategic allocation of limited resources. Methods Using a participatory approach, and informed by a range of national, state, and local datasets, a system dynamics model was developed, tested, and validated for a regional population catchment. The model incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and SB. Intervention scenarios were investigated to forecast their impact on SB over a 20-year period. Results A combination of social connectedness programs, technology-enabled coordinated care, post-attempt assertive aftercare, reductions in childhood adversity, and increasing youth employment projected the greatest impacts on SB, particularly in a youth population, reducing self-harm hospitalisations (suicide attempts) by 28.5% (95% interval 26.3–30.8%) and suicide deaths by 29.3% (95% interval 27.1–31.5%). Introducing additional interventions beyond the best performing suite of interventions produced only marginal improvement in population level impacts, highlighting that ‘more is not necessarily better.’ Conclusion Results indicate that targeted investments in addressing the social determinants and in mental health services provides the best opportunity to reduce SB and suicide. Systems modelling and simulation offers a robust approach to leveraging best available research, data, and expert knowledge in a way that helps decision makers respond to the unique characteristics and drivers of SB in their catchments and more effectively focus limited health resources.

BackgroundPredictors of new-onset bipolar disorder (BD) or psychotic disorder (PD) have been proposed on the basis of retrospective or prospective studies of ‘at-risk’ cohorts. Few studies have compared concurrently or longitudinally factors associated with the onset of BD or PDs in youth presenting to early intervention services. We aimed to identify clinical predictors of the onset of full-threshold (FT) BD or PD in this population.MethodMulti-state Markov modelling was used to assess the relationships between baseline characteristics and the likelihood of the onset of FT BD or PD in youth (aged 12–30) presenting to mental health services.ResultsOf 2330 individuals assessed longitudinally, 4.3% (n = 100) met criteria for new-onset FT BD and 2.2% (n = 51) met criteria for a new-onset FT PD. The emergence of FT BD was associated with older age, lower social and occupational functioning, mania-like experiences (MLE), suicide attempts, reduced incidence of physical illness, childhood-onset depression, and childhood-onset anxiety. The emergence of a PD was associated with older age, male sex, psychosis-like experiences (PLE), suicide attempts, stimulant use, and childhood-onset depression.ConclusionsIdentifying risk factors for the onset of either BD or PDs in young people presenting to early intervention services is assisted not only by the increased focus on MLE and PLE, but also by recognising the predictive significance of poorer social function, childhood-onset anxiety and mood disorders, and suicide attempts prior to the time of entry to services. Secondary prevention may be enhanced by greater attention to those risk factors that are modifiable or shared by both illness trajectories.

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.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.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.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.

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.

Objective This study utilised digital technology to assess the clinical needs of young people presenting for care at headspace centres across Australia. Method 1490 young people (12–25 years) who presented to one of 11 headspace services from four geographical locations (urban New South Wales, urban South Australia, regional New South Wales, and regional Queensland) completed a digital multidimensional assessment at initial presentation. Characteristics were compared between services and geographical locations. Results We identified major variation in the demographics, and the type and severity of needs across different services. Individuals from regional services were more likely to be younger, of Aboriginal and Torres Strait Islander origin, and present with psychotic-like symptoms and suicidality, while those in urban areas were more likely to have previously sought help and have problematic alcohol use. Further differences in age, distress, depressive symptoms, psychotic-like experiences, trauma, family history, alcohol use, education/employment engagement, and days out of role were identified between different urban sites. Conclusions The variability between services provides insight into the heterogeneity of youth mental health populations which has implications for appropriate early intervention and prevention service provisions. We propose that integrating digital technologies has the potential to provide insights for smarter service planning and evaluation.

Emergence of suicidal symptoms has been reported as a potential antidepressant adverse drug reaction. Identifying risk factors associated could increase our understanding of this phenomenon and stratify individuals at higher risk. Logistic regressions were used to identify risk factors of self-reported treatment-attributed suicidal ideation (TASI). We then employed classifiers to test the predictive ability of the variables identified. A TASI GWAS, as well as SNP-based heritability estimation, were performed. GWAS replication was sought from an independent study. Significant associations were found for age and comorbid conditions, including bipolar and personality disorders. Participants reporting TASI from one antidepressant were more likely to report TASI from other antidepressants. No genetic loci associated with TAS I (p < 5e-8) were identified. Of 32 independent variants with suggestive association (p < 1e-5), 27 lead SNPs were available in a replication dataset from the GENDEP study. Only one variant showed a consistent effect and nominal association in the independent replication sample. Classifiers were able to stratify non-TASI from TASI participants (AUC = 0.77) and those reporting treatment-attributed suicide attempts (AUC = 0.85). The pattern of TASI co-occurrence across participants suggest nonspecific factors underlying its etiology. These findings provide insights into the underpinnings of TASI and serve as a proof-of-concept of the use of classifiers for risk stratification.

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.

ObjectiveIdentifying brain differences associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and generating effective approaches to early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth.MethodsFirst, we examined associations among regional brain structure and STBs, which were assessed in six samples of youth with mood disorders, using the Columbia Suicide Severity Rating Scale (C-SSRS;N=577). Second, we combined this sample with a larger sample (total 21 sites) in which STBs were assessed using various instruments. MRI metrics were compared among healthy controls without STBs (HC;N=688), clinical controls without STBs (CC;N=648), and young people with psychiatric diagnoses and current suicidal ideation (N=406). In separate analyses, MRI metrics were compared among HCs (N=335), CCs (N=768), and suicide attempters (N=254).ResultsIn the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and history of actual suicide attempts (N=163) than those without (N=394; FDR-pd=.334). When expanding to more clinically heterogeneous samples, we also found lower surface area of the frontal pole in those with a history of suicide attempts (Cohen’sd=.22).ConclusionsLower frontal pole surface area may represent a vulnerability for a suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.

BACKGROUND Globally, there are fundamental shortcomings in mental health care systems, including restricted access, siloed services, interventions that are poorly matched to service users’ needs, underuse of personal outcome monitoring to track progress, exclusion of family and carers, and suboptimal experiences of care. Health information technologies (HITs) hold great potential to improve these aspects that underpin the enhanced quality of mental health care. OBJECTIVE Project Synergy aimed to co-design, implement, and evaluate novel HITs, as exemplified by the InnoWell Platform, to work with standard health care organizations. The goals were to deliver improved outcomes for specific populations under focus and support organizations to enact significant system-level reforms. METHODS Participating health care organizations included the following: Open Arms–Veterans & Families Counselling (in Sydney and Lismore, New South Wales [NSW]); NSW North Coast headspace centers for youth (Port Macquarie, Coffs Harbour, Grafton, Lismore, and Tweed Heads); the Butterfly Foundation’s National Helpline for eating disorders; Kildare Road Medical Centre for enhanced primary care; and Connect to Wellbeing North Coast NSW (administered by Neami National), for population-based intake and assessment. Service users, families and carers, health professionals, and administrators of services across Australia were actively engaged in the configuration of the InnoWell Platform to meet service needs, identify barriers to and facilitators of quality mental health care, and highlight potentially the best points in the service pathway to integrate the InnoWell Platform. The locally configured InnoWell Platform was then implemented within the respective services. A mixed methods approach, including surveys, semistructured interviews, and workshops, was used to evaluate the impact of the InnoWell Platform. A participatory systems modeling approach involving co-design with local stakeholders was also undertaken to simulate the likely impact of the platform in combination with other services being considered for implementation within the North Coast Primary Health Network to explore resulting impacts on mental health outcomes, including suicide prevention. RESULTS Despite overwhelming support for integrating digital health solutions into mental health service settings and promising impacts of the platform simulated under idealized implementation conditions, our results emphasized that successful implementation is dependent on health professional and service readiness for change, leadership at the local service level, the appropriateness and responsiveness of the technology for the target end users, and, critically, funding models being available to support implementation. The key places of interoperability of digital solutions and a willingness to use technology to coordinate health care system use were also highlighted. CONCLUSIONS Although the COVID-19 pandemic has resulted in the widespread acceptance of very basic digital health solutions, Project Synergy highlights the critical need to support equity of access to HITs, provide funding for digital infrastructure and digital mental health care, and actively promote the use of technology-enabled, coordinated systems of care.

Background Globally, there are fundamental shortcomings in mental health care systems, including restricted access, siloed services, interventions that are poorly matched to service users’ needs, underuse of personal outcome monitoring to track progress, exclusion of family and carers, and suboptimal experiences of care. Health information technologies (HITs) hold great potential to improve these aspects that underpin the enhanced quality of mental health care. Objective Project Synergy aimed to co-design, implement, and evaluate novel HITs, as exemplified by the InnoWell Platform, to work with standard health care organizations. The goals were to deliver improved outcomes for specific populations under focus and support organizations to enact significant system-level reforms. Methods Participating health care organizations included the following: Open Arms–Veterans & Families Counselling (in Sydney and Lismore, New South Wales [NSW]); NSW North Coast headspace centers for youth (Port Macquarie, Coffs Harbour, Grafton, Lismore, and Tweed Heads); the Butterfly Foundation’s National Helpline for eating disorders; Kildare Road Medical Centre for enhanced primary care; and Connect to Wellbeing North Coast NSW (administered by Neami National), for population-based intake and assessment. Service users, families and carers, health professionals, and administrators of services across Australia were actively engaged in the configuration of the InnoWell Platform to meet service needs, identify barriers to and facilitators of quality mental health care, and highlight potentially the best points in the service pathway to integrate the InnoWell Platform. The locally configured InnoWell Platform was then implemented within the respective services. A mixed methods approach, including surveys, semistructured interviews, and workshops, was used to evaluate the impact of the InnoWell Platform. A participatory systems modeling approach involving co-design with local stakeholders was also undertaken to simulate the likely impact of the platform in combination with other services being considered for implementation within the North Coast Primary Health Network to explore resulting impacts on mental health outcomes, including suicide prevention. Results Despite overwhelming support for integrating digital health solutions into mental health service settings and promising impacts of the platform simulated under idealized implementation conditions, our results emphasized that successful implementation is dependent on health professional and service readiness for change, leadership at the local service level, the appropriateness and responsiveness of the technology for the target end users, and, critically, funding models being available to support implementation. The key places of interoperability of digital solutions and a willingness to use technology to coordinate health care system use were also highlighted. Conclusions Although the COVID-19 pandemic has resulted in the widespread acceptance of very basic digital health solutions, Project Synergy highlights the critical need to support equity of access to HITs, provide funding for digital infrastructure and digital mental health care, and actively promote the use of technology-enabled, coordinated systems of care.

Most mental disorders emerge before the age of 25 years and, if left untreated, have the potential to lead to considerable lifetime burden of disease. Many services struggle to manage high demand and have difficulty matching individuals to timely interventions due to the heterogeneity of disorders. The technological implementation of clinical staging for youth mental health may assist the early detection and treatment of mental disorders. We describe the development of a theory-based automated protocol to facilitate the initial clinical staging process, its intended use, and strategies for protocol validation and refinement. The automated clinical staging protocol leverages the clinical validation and evidence base of the staging model to improve its standardization, scalability, and utility by deploying it using Health Information Technologies (HIT). Its use has the potential to enhance clinical decision-making and transform existing care pathways, but further validation and evaluation of the tool in real-world settings is needed.

Neurocognitive impairment is commonly associated with functional disability in established depressive, bipolar and psychotic disorders. However, little is known about the longer-term functional implications of these impairments in early phase transdiagnostic cohorts. We aimed to examine associations between neurocognition and functioning at baseline and over time. We used mixed effects models to investigate associations between neurocognitive test scores and longitudinal social and occupational functioning (“Social and Occupational Functioning Assessment Scale”) at 1–7 timepoints over five-years in 767 individuals accessing youth mental health services. Analyses were adjusted for age, sex, premorbid IQ, and symptom severity. Lower baseline functioning was associated with male sex (coefficient −3.78, 95% CI −5.22 to −2.34 p

Neuropsychological assessments have provided the field of psychiatry with important information about patients. As an assessment tool, a neuropsychological battery can be useful in a clinical setting; however, implementation as standard clinical care in an inpatient unit has not been extensively evaluated. A computerized cognitive battery was administered to 103 current young adult inpatients (19.2 ± 3.1 years; 72% female) with affective disorder. Neurocognitive tasks included Verbal Recognition Memory (VRM), Attention Switching (AST), Paired Association Learning (PAL), and Rapid Visual Processing (RVP). Patients also completed a computerized self-report questionnaire evaluating subjective impressions of their cognition. Hierarchical cluster analysis determined three neurocognitive subgroups: cluster 1 (n = 17) showed a more impaired neurocognitive profile on three of the four variables compared to their peers in cluster 2 (n = 59), and cluster 3 (n = 27), who had the most impaired attentional shifting. Two of the four neurocognitive variables were significantly different between all three cluster groups (verbal learning and sustained attention). Overall group results showed an association between poorer sustained attention and increased suicidal ideation. These findings strengthen the idea that neurocognitive profiles may play an important role in better understanding the severity of illness in young inpatients with major psychiatric disorders.

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.

Objectives The heterogeneity and comorbidity of major mental disorders presenting in adolescents and young adults has fostered calls for trans-diagnostic research. This study examines early expressions of psychopathology and risk and trans-diagnostic caseness in a community cohort of twins and non-twin siblings. Methods Using data from the Brisbane Longitudinal Twin Study, we estimated median number of self-rated psychiatric symptoms, prevalence of subthreshold syndromes, family history of mood and/or psychotic disorders, and likelihood of subsequent trans-diagnostic caseness (individuals meeting diagnostic criteria for mood and/or psychotic syndromes). Next, we used cross-validated Chi-Square Automatic Interaction Detector (CHAID) analyses to identify the nature and relative importance of individual self-rated symptoms that predicted trans-diagnostic caseness. We examined the positive and negative predictive values (PPV; NPV) and accuracy of all classifications (Area under the Curve and 95% confidence intervals: AUC; 95% CI). Results Of 1815 participants (Female 1050, 58%; mean age 26.40), more than one in four met caseness criteria for a mood and/or psychotic disorder. Examination of individual factors indicated that the AUC was highest for subthreshold syndromes, followed by family history then self-rated psychiatric symptoms, and that NPV always exceeded PPV for caseness. In contrast, the CHAID analysis (adjusted for age, sex, twin status) generated a classification tree comprising six trans-diagnostic symptoms. Whilst the contribution of two symptoms (need for sleep; physical activity) to the model was more difficult to interpret, CHAID analysis indicated that four self-rated symptoms (sadness; feeling overwhelmed; impaired concentration; paranoia) offered the best discrimination between cases and non-cases. These four symptoms showed different associations with family history status. Conclusions The findings need replication in independent cohorts. However, the use of CHAID might provide a means of identifying specific subsets of trans-diagnostic symptoms representing clinical phenotypes that predict transition to caseness in individuals at risk of onset of major mental disorders.

IntroductionApproximately 75% of major mental illness occurs before the age of 25 years. Despite this, our capacity to provide effective, early and personalised interventions is limited by insufficient evidence for characterising early-stage, and less specific, presentations of major mental disorders in youth populations. This article describes the protocol for setting up a large-scale database that will collect longitudinal, prospective data that incorporate clinical, social and occupational function, neuropsychological, circadian, metabolic, family history and genetic metrics. By collecting data in a research-purposed, standardised manner, the ‘Neurobiology Youth Follow-up Study’ should improve identification, characterisation and profiling of youth attending mental healthcare, to better inform diagnosis and treatment at critical time points. The overall goal is enhanced long-term clinical and functional outcomes.Methods and analysisThis longitudinal clinical cohort study will invite participation from youth (12–30 years) who seek help for mental health-related issues at an early intervention service (headspace Camperdown) and linked services. Participants will be prospectively tracked over 3 years with a series of standardised multimodal assessments at baseline, 6, 12, 24 and 36 months. Evaluations will include: (1) clinician-administered and self-report assessments determining clinical stage, pathophysiological pathways to illness, diagnosis, symptomatology, social and occupational function; (2) neuropsychological profile; (3) sleep–wake patterns and circadian rhythms; (4) metabolic markers and (5) genetics. These data will be used to: (1) model the impact of demographic, phenomenological and treatment variables, on clinical and functional outcomes; (2) map neurobiological profiles and changes onto a transdiagnostic clinical stage and pathophysiological mechanisms framework.Ethics and disseminationThis study protocol has been approved by the Human Research Ethics Committee of the Sydney Local Health District (2020/ETH01272, protocol V.1.3, 14 October 2020). Research findings will be disseminated through peer-reviewed journals and presentations at scientific conferences and to user and advocacy groups. Participant data will be de-identified.

Background The schizophrenia polygenic risk score (SCZ-PRS) is an emerging tool in psychiatry. Aims We aimed to evaluate the utility of SCZ-PRS in a young, transdiagnostic, clinical cohort. Method SCZ-PRSs were calculated for young people who presented to early-intervention youth mental health clinics, including 158 patients of European ancestry, 113 of whom had longitudinal outcome data. We examined associations between SCZ-PRS and diagnosis, clinical stage and functioning at initial assessment, and new-onset psychotic disorder, clinical stage transition and functional course over time in contact with services. Results Compared with a control group, patients had elevated PRSs for schizophrenia, bipolar disorder and depression, but not for any non-psychiatric phenotype (for example cardiovascular disease). Higher SCZ-PRSs were elevated in participants with psychotic, bipolar, depressive, anxiety and other disorders. At initial assessment, overall SCZ-PRSs were associated with psychotic disorder (odds ratio (OR) per s.d. increase in SCZ-PRS was 1.68, 95% CI 1.08–2.59, P = 0.020), but not assignment as clinical stage 2+ (i.e. discrete, persistent or recurrent disorder) (OR = 0.90, 95% CI 0.64–1.26, P = 0.53) or functioning (R = 0.03, P = 0.76). Longitudinally, overall SCZ-PRSs were not significantly associated with new-onset psychotic disorder (OR = 0.84, 95% CI 0.34–2.03, P = 0.69), clinical stage transition (OR = 1.02, 95% CI 0.70–1.48, P = 0.92) or persistent functional impairment (OR = 0.84, 95% CI 0.52–1.38, P = 0.50). Conclusions In this preliminary study, SCZ-PRSs were associated with psychotic disorder at initial assessment in a young, transdiagnostic, clinical cohort accessing early-intervention services. Larger clinical studies are needed to further evaluate the clinical utility of SCZ-PRSs, especially among individuals with high SCZ-PRS burden.

The demand for mental health services is projected to rapidly increase as a direct and indirect result of the COVID-19 pandemic. Given that young people are disproportionately disadvantaged by mental illness and will face further challenges related to the COVID-19 pandemic, it is crucial to deliver appropriate mental health care to young people as early as possible. Integrating digital health solutions into mental health service delivery pathways has the potential to greatly increase efficiencies, enabling the provision of “right care, first time.” We propose an innovative digital health solution for demand management intended for use by primary youth mental health services, comprised of (1) a youth mental health model of care (ie, the Brain and Mind Centre Youth Model) and (2) a health information technology specifically designed to deliver this model of care (eg, the InnoWell Platform). We also propose an operational protocol of how this solution could be applied to primary youth mental health service delivery processes. By “flipping” the conventional service delivery models of majority in-clinic and minority web-delivered care to a model where web-delivered care is the default, this digital health solution offers a scalable way of delivering quality youth mental health care both in response to public health crises (such as the COVID-19 pandemic) and on an ongoing basis in the future.

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.

Background Despite the widely acknowledged potential for health information technologies to improve the accessibility, quality and clinical safety of mental health care, implementation of such technologies in services is frequently unsuccessful due to varying consumer, health professional, and service-level factors. The objective of this co-design study was to use process mapping (i.e. service mapping) to illustrate the current consumer journey through primary mental health services, identify barriers to and facilitators of quality mental health care, and highlight potential points at which to integrate the technology-enabled solution to optimise the provision of care based on key service performance indicators. Methods Interactive, discussion-based workshops of up to six hours were conducted with representative stakeholders from each participating service, including health professionals, service managers and administrators from Open Arms – Veterans & Families Counselling Service (Sydney), a counselling service for veterans and their families, and five headspace centres in the North Coast Primary Health Network, primary youth mental health services. Service maps were drafted and refined in real time during the workshops. Through both group discussion and the use of post-it notes, participants worked together to evaluate performance indicators (e.g. safety) at each point in the consumer journey (e.g. intake) to indicate points of impact for the technology-enabled solution, reviewing and evaluating differing opinions in order to reach consensus. Results Participants (n=84 across participating services) created service maps illustrating the current consumer journey through the respective services and highlighting barriers to and facilitators of quality mental health care. By consensus, the technology-enabled solution as facilitated by the InnoWell Platform was noted to enable the early identification of risk, reduce or eliminate lengthy intake processes, enable routine outcome monitoring to revise treatment plans in relation to consumer response, and serve as a personal data record for consumers, driving person-centred, coordinated care. Conclusions Service mapping was shown to be an effective methodology to understand the consumer’s journey through a service and served to highlight how the co-designed technology-enabled solution can optimise service pathways to improve the accessibility, quality and clinical safety of care relative to key service performance indicators, facilitating the delivery of the right care.

UNSTRUCTURED The demand for mental health services is projected to rapidly increase as a direct and indirect result of the COVID-19 pandemic. Given that young people are disproportionately disadvantaged by mental illness and will face further challenges related to the COVID-19 pandemic, it is crucial to deliver appropriate mental health care to young people as early as possible. Integrating digital health solutions into mental health service delivery pathways has the potential to greatly increase efficiencies, enabling the provision of “right care, first time.” We propose an innovative digital health solution for demand management intended for use by primary youth mental health services, comprised of (1) a youth mental health model of care (ie, the Brain and Mind Centre Youth Model) and (2) a health information technology specifically designed to deliver this model of care (eg, the InnoWell Platform). We also propose an operational protocol of how this solution could be applied to primary youth mental health service delivery processes. By “flipping” the conventional service delivery models of majority in-clinic and minority web-delivered care to a model where web-delivered care is the default, this digital health solution offers a scalable way of delivering quality youth mental health care both in response to public health crises (such as the COVID-19 pandemic) and on an ongoing basis in the future.

BackgroundA priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making regarding a service response in terms of more detailed assessments and/or intervention. The aim of this study was to predict self-harm within six-months after initial presentation.MethodThe study included 1962 young people (12–30 years) presenting to youth mental health services in Australia. Six machine learning algorithms were trained and tested with ten repeats of ten-fold cross-validation. The net benefit of these models were evaluated using decision curve analysis.ResultsOut of 1962 young people, 320 (16%) engaged in self-harm in the six months after first assessment and 1642 (84%) did not. The top 25% of young people as ranked by mean predicted probability accounted for 51.6% - 56.2% of all who engaged in self-harm. By the top 50%, this increased to 82.1%-84.4%. Models demonstrated fair overall prediction (AUROCs; 0.744–0.755) and calibration which indicates that predicted probabilities were close to the true probabilities (brier scores; 0.185–0.196). The net benefit of these models were positive and superior to the ‘treat everyone’ strategy. The strongest predictors were (in ranked order); a history of self-harm, age, social and occupational functioning, sex, bipolar disorder, psychosis-like experiences, treatment with antipsychotics, and a history of suicide ideation.ConclusionPrediction models for self-harm may have utility to identify a large sub population who would benefit from further assessment and targeted (low intensity) interventions. Such models could enhance health service approaches to identify and reduce self-harm, a considerable source of distress, morbidity, ongoing health care utilisation and mortality.

Background Neurocognitive impairment is recognised as a risk factor for suicidal behaviour in adults. The current study aims to determine whether neurocognitive deficits also predict ongoing or emergent suicidal behaviour in young people with affective disorders. Methods Participants were aged 12-30 years and presented to early intervention youth mental health clinics between 2008 and 2018. In addition to clinical assessment a standardised neurocognitive assessment was conducted at baseline. Clinical data was extracted from subsequent visits using a standardised proforma. Results Of the 635 participants who met inclusion criteria (mean age 19.6 years, 59% female, average follow up 476 days) 104 (16%) reported suicidal behaviour during care. In 5 of the 10 neurocognitive domains tested (cognitive flexibility, processing speed, working memory, verbal memory and visuospatial memory) those with suicidal behaviour during care were superior to clinical controls. Better general neurocognitive function remained a significant predictor (OR=1.94, 95% CI 1.29- 2.94) of suicidal behaviour in care after controlling for other risk factors. Limitations The neurocognitive battery used was designed for use with affective and psychotic disorders and may not have detected some deficits more specific to suicidal behaviour. Conclusion Contrary to expectations, better neurocognitive functioning predicts suicidal behaviour during care in young people with affective disorders. While other populations with suicidal behaviour, such as adults with affective disorders or young people with psychotic disorders, tend to experience neurocognitive deficits which may limit their capacity to engage in some interventions, this does not appear to be the case for young people with affective disorders.

Background Evidence from family and twin studies suggests that mood and anxiety disorders, and related temperamental factors may share common etiologic factors. We examine the familial aggregation and coaggregation of anxiety disorder subtypes and anxiety-related temperamental traits, and their association with mood disorders. Methods A total of 477 probands and 549 first-degree adult relatives from a large community based family study of affective spectrum disorders completed semi-structured diagnostic interviews and self-reported assessments of temperamental traits including: negative affectivity on the ‘Positive and Negative Affect Schedule’ (PANAS), neuroticism anxiety on the ‘Zuckerman-Kuhlman Personality Questionnaire’ (ZKPQ), and anxiety sensitivity on the ‘Anxiety Sensitivity Index’ (ASI). Results The anxiety-related temperamental traits of negative affectivity, neuroticism anxiety and anxiety sensitivity had significant familial specificity, even after controlling for comorbid mood and anxiety disorders in probands and relatives. Yet, these traits in probands did not predict anxiety disorders in relatives. Although some anxiety subtypes were familial, there were no longer familial links between anxiety disorder subtypes (generalized anxiety disorder, social anxiety or panic disorder) after controlling for mood disorder subtypes in probands and relatives. Limitations Cross-sectional interviews were used to estimate disorders, and self-report measures were used for temperamental traits. Conclusions These results confirm previous research regarding familial overlap between anxiety subtypes and mood disorders, however their shared liability cannot be fully explained by anxiety-related temperamental traits. These findings suggest that anxiety-related temperamental traits may indicate a vulnerability for mood and anxiety disorders or a potential consequence of these conditions.

Background: There is growing evidence to support the need for personalised intervention in the early stages of a major psychiatric illness, as well as the clear delineation of subgroups in psychiatric disorders based on cognitive impairment. Affective disorders are often accompanied by neurocognitive deficits; however a lack of research among young adult inpatients highlights the need to assess the utility of cognitive testing in this population. Methods: A computerised cognitive battery was administered to 50 current inpatient young adults (16–30 years; 75% female) with an affective disorder. Patients also completed a computerised self-report questionnaire (to measure demographics and clinical features) that included items evaluating subjective impressions of their cognition. Results: Hierarchical cluster analysis determined two neurocognitive subgroups: cluster 1 (n = 16) showed more severe impairments in sustained attention and memory as well as higher anxiety levels, compared to their peers in cluster 2 (n = 30) who showed the most impaired attentional switching. Across the sample, poor sustained attention was significantly correlated with higher levels of current anxiety and depressive symptoms, whereas poor verbal memory was significantly associated with increased psychological distress. Limitations: This study has a relatively small sample size (due to it being a pilot/feasibility study). Furthermore, future studies should aim to assess inpatient samples compared to community care samples, as well as healthy controls, on a larger scale. Conclusions: The findings suggest neurocognitive profiles are important in understanding phenotypes within young people with severe affective disorders. With clear subgroups based on cognitive impairment being demonstrated, the clinical utility and use of new and emerging technologies is warranted in such inpatients facilities. This pilot/feasibility study has strengthened the utility of cognitive screening as standard clinical care in an inpatient unit.

Purpose The Brain and Mind Centre (BMC) Optymise cohort assesses multiple clinical and functional domains longitudinally in young people presenting for mental health care and treatment. Longitudinal tracking of this cohort will allow investigation of the relationships between multiple outcome domains across the course of care. Subsets of Optymise have completed detailed neuropsychological and neurobiological assessments, permitting investigation of associations between these measures and longitudinal course. Participants Young people (aged 12–30) presenting to clinics coordinated by the BMC were recruited to a research register (n=6743) progressively between June 2008 and July 2018. To date, 2767 individuals have been included in Optymise based on the availability of at least one detailed clinical assessment. Measures Trained researchers use a clinical research proforma to extract key data from clinical files to detail social and occupational functioning, clinical presentation, self-harm and suicidal thoughts and behaviours, alcohol and other substance use, physical health comorbidities, personal and family history of mental illness, and treatment utilisation at the following time points: baseline, 3, 6, 12, 24, 36, 48, and 60 months, and time last seen. Findings to date There is moderate to substantial agreement between raters for data collected via the proforma. While wide variations in individual illness course are clear, social and occupational outcomes suggest that the majority of cohort members show no improvement in functioning over time. Differential rates of longitudinal transition are reported between early and late stages of illness, with a number of baseline factors associated with these transitions. Furthermore, there are longitudinal associations between prior suicide attempts and inferior clinical and functional outcomes. Future plans Future reports will detail the longitudinal course of each outcome domain and examine multidirectional relationships between these domains both cross-sectionally and longitudinally, and explore in subsets the associations between detailed neurobiological measures and clinical, social and functional outcomes.

PurposeThe Brain and Mind Centre (BMC)Optymisecohort assesses multiple clinical and functional domains longitudinally in young people presenting for mental health care and treatment. Longitudinal tracking of this cohort will allow investigation of the relationships between multiple outcome domains across the course of care. Subsets ofOptymisehave completed detailed neuropsychological and neurobiological assessments, permitting investigation of associations between these measures and longitudinal course.ParticipantsYoung people (aged 12–30) presenting to clinics coordinated by the BMC were recruited to a research register (n=6743) progressively between June 2008 and July 2018. To date, 2767 individuals have been included inOptymisebased on the availability of at least one detailed clinical assessment.MeasuresTrained researchers use a clinical research proforma to extract key data from clinical files to detail social and occupational functioning, clinical presentation, self-harm and suicidal thoughts and behaviours, alcohol and other substance use, physical health comorbidities, personal and family history of mental illness, and treatment utilisation at the following time points: baseline, 3, 6, 12, 24, 36, 48, and 60 months, and time last seen.Findings to dateThere is moderate to substantial agreement between raters for data collected via the proforma. While wide variations in individual illness course are clear, social and occupational outcomes suggest that the majority of cohort members show no improvement in functioning over time. Differential rates of longitudinal transition are reported between early and late stages of illness, with a number of baseline factors associated with these transitions. Furthermore, there are longitudinal associations between prior suicide attempts and inferior clinical and functional outcomes.Future plansFuture reports will detail the longitudinal course of each outcome domain and examine multidirectional relationships between these domains both cross-sectionally and longitudinally, and explore in subsets the associations between detailed neurobiological measures and clinical, social and functional outcomes.

Background Neurocognitive impairments robustly predict functional outcome. However, heterogeneity in neurocognition is common within diagnostic groups, and data-driven analyses reveal homogeneous neurocognitive subgroups cutting across diagnostic boundaries. Aims To determine whether data-driven neurocognitive subgroups of young people with emerging mental disorders are associated with 3-year functional course. Method Model-based cluster analysis was applied to neurocognitive test scores across nine domains from 629 young people accessing mental health clinics. Cluster groups were compared on demographic, clinical and substance-use measures. Mixed-effects models explored associations between cluster-group membership and socio-occupational functioning (using the Social and Occupational Functioning Assessment Scale) over 3 years, adjusted for gender, premorbid IQ, level of education, depressive, positive, negative and manic symptoms, and diagnosis of a primary psychotic disorder. Results Cluster analysis of neurocognitive test scores derived three subgroups described as ‘normal range’ (n = 243, 38.6%), ‘intermediate impairment’ (n = 252, 40.1%), and ‘global impairment’ (n = 134, 21.3%). The major mental disorder categories (depressive, anxiety, bipolar, psychotic and other) were represented in each neurocognitive subgroup. The global impairment subgroup had lower functioning for 3 years of follow-up; however, neither the global impairment (B = 0.26, 95% CI −0.67 to 1.20; P = 0.581) or intermediate impairment (B = 0.46, 95% CI −0.26 to 1.19; P = 0.211) subgroups differed from the normal range subgroup in their rate of change in functioning over time. Conclusions Neurocognitive impairment may follow a continuum of severity across the major syndrome-based mental disorders, with data-driven neurocognitive subgroups predictive of functional course. Of note, the global impairment subgroup had longstanding functional impairment despite continuing engagement with clinical services.

BACKGROUND Although numerous studies have demonstrated sex differences in the prevalence of suicidal thoughts and behaviors (STB), there is a clear lack of research examining the similarities and differences between men and women in terms of the relationship between STB, transitional life events, and the coping strategies employed after experiencing such events when they are perceived as stressful. OBJECTIVE This study aims to examine the differences between men’s and women’s experiences of STB, sociodemographic predictors of STB, and how coping responses after experiencing a stressful transitional life event predict STB. METHODS A web-based self-report survey was used to assess the health and well-being of a voluntary community-based sample of men and women aged 16 years and older, living in Australia, Canada, New Zealand, the United Kingdom, and the United States, who were recruited using web-based social media promotion and snowballing. RESULTS In total, 10,765 eligible web-based respondents participated. Compared with men, a significantly greater proportion of women reported STB (PPP<.001). Coping strategies significantly explained 19.0% of the STB variance for men (F16,1027=14.64; PF16,1977=36.45; P CONCLUSIONS This research highlights multiple risk factors for STB, one of which includes experiencing at least one stressful transitional life event in the past 12 months. When individuals are experiencing such events, support from services and the community alike should consider using sex-specific or targeted strategies, as this research indicates that compared with women, more men do nothing when experiencing stress after a transitional life event and may be waiting until they experience STB to engage with their social networks for support.

IntroductionUnderstanding the risk of premature death from suicide, accident and injury and other physical health conditions in people seeking healthcare for mental disorders is essential for delivering targeted clinical interventions and secondary prevention strategies. It is not clear whether morbidity and mortality outcomes in hospital-based adult cohorts are applicable to young people presenting to early-intervention services.Methods and analysisThe current data linkage project will establish the Brain and Mind Patient Research Register–Mortality and Morbidity (BPRR-M&M) database. The existing Brain and Mind Research Institute Patient Research Register (BPRR) is a cohort of 6743 young people who have accessed primary care-based early-intervention services; subsets of the BPRR contain rich longitudinal clinical, neurobiological, social and functional data. The BPRR will be linked with the routinely collected health data from emergency department (ED), hospital admission and mortality databases in New South Wales from January 2010 to November 2020. Mortality will be the primary outcome of interest, while hospital presentations will be a secondary outcome. The established BPRR-M&M database will be used to establish mortality rates and rates of ED presentations and hospital admissions. Survival analysis will determine how time to death or hospital presentation varies by identified social, demographic and clinical variables. Bayesian modelling will be used to identify predictors of these morbidity and mortality outcomes.Ethics and disseminationThe study has been reviewed and approved by the human research ethics committee of the Sydney Local Health District (2019/ETH00469). All data will be non-identifiable, and research findings will be disseminated through peer-reviewed journals and scientific conference presentations.

A key population-health priority is to reduce the rates of premature death and illness burden due to the common anxiety and mood disorders that typically have their onset during adolescence and early-adult years. From an individual clinical and health services planning perspective, evidence relating to the potential impacts of early identification, secondary prevention, and enhanced long-term care strategies is required. Over the past decade, we have accumulated substantial cross-sectional and longitudinal evidence from a cohort of more than 7000 individuals detailing how these types of services can be developed, structured, and evaluated for young people with emerging mood disorders. A clear conclusion is that impairment and concurrent morbidity is well-established in these young people (mean age 18 years) by the time they present for mental health-focused care. A clear caveat, however, is that early identification, followed by standard care, does not automatically result in improved outcomes. While much work is yet to be done in the development of individual-level and service-level care packages to reduce morbidity and mortality, our key findings support the utility of clinical staging as an adjunct to traditional diagnostic frameworks, the recognition of at least three pathophysiological underlying paths (resulting in different age-dependent phenotypes in childhood and adolescence), and a strong focus on implementing a genuinely multidimensional assessment and longitudinal outcomes framework.

Mood and psychotic syndromes most often emerge during adolescence and young adulthood, a period characterised by major physical and social change. Consequently, the effects of adolescent-onset mood and psychotic syndromes can have long term consequences. A key clinical challenge for youth mental health is to develop and test new systems that align with current evidence for comorbid presentations and underlying neurobiology, and are useful for predicting outcomes and guiding decisions regarding the provision of appropriate and effective care. Our highly personalised and measurement-based care model includes three core concepts: ▶ A multidimensional assessment and outcomes framework that includes: social and occupational function; self-harm, suicidal thoughts and behaviour; alcohol or other substance misuse; physical health; and illness trajectory. ▶ Clinical stage. ▶ Three common illness subtypes (psychosis, anxious depression, bipolar spectrum) based on proposed pathophysiological mechanisms (neurodevelopmental, hyperarousal, circadian). The model explicitly aims to prevent progression to more complex and severe forms of illness and is better aligned to contemporary models of the patterns of emergence of psychopathology. Inherent within this highly personalised approach is the incorporation of other evidence-based processes, including real-time measurement-based care as well as utilisation of multidisciplinary teams of health professionals. Data-driven local system modelling and personalised health information technologies provide crucial infrastructure support to these processes for better access to, and higher quality, mental health care for young people. CHAPTER 1: MULTIDIMENSIONAL OUTCOMES IN YOUTH MENTAL HEALTH CARE: WHAT MATTERS AND WHY?: Mood and psychotic syndromes present one of the most serious public health challenges that we face in the 21st century. Factors including prevalence, age of onset, and chronicity contribute to substantial burden and secondary risks such as alcohol or other substance misuse. Mood and psychotic syndromes most often emerge during adolescence and young adulthood, a period characterised by major physical and social change; thus, effects can have long term consequences. We propose five key domains which make up a multidimensional outcomes framework that aims to address the specific needs of young people presenting to health services with emerging mental illness. These include social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness type, stage and trajectory. Impairment and concurrent morbidity are well established in young people by the time they present for mental health care. Despite this, services and health professionals tend to focus on only one aspect of the presentation - illness type, stage and trajectory - and are often at odds with the preferences of young people and their families. There is a need to address the disconnect between mental health, physical health and social services and interventions, to ensure that youth mental health care focuses on the outcomes that matter to young people. CHAPTER 2: COMBINING CLINICAL STAGE AND PATHOPHYSIOLOGICAL MECHANISMS TO UNDERSTAND ILLNESS TRAJECTORIES IN YOUNG PEOPLE WITH EMERGING MOOD AND PSYCHOTIC SYNDROMES: Traditional diagnostic classification systems for mental disorders map poorly onto the early stages of illness experienced by young people, and purport categorical distinctions that are not readily supported by research into genetic, environmental and neurobiological risk factors. Consequently, a key clinical challenge in youth mental health is to develop and test new classification systems that align with current evidence on comorbid presentations, are consistent with current understanding of underlying neurobiology, and provide utility for predicting outcomes and guiding decisions regarding the provision of appropriate and effective care. This chapter outlines a transdiagnostic framework for classifying common adolescent-onset mood and psychotic syndromes, combining two independent but complementary dimensions: clinical staging, and three proposed pathophysiological mechanisms. Clinical staging reflects the progression of mental disorders and is in line with the concept used in general medicine, where more advanced stages are associated with a poorer prognosis and a need for more intensive interventions with a higher risk-to-benefit ratio. The three proposed pathophysiological mechanisms are neurodevelopmental abnormalities, hyperarousal and circadian dysfunction, which, over time, have illness trajectories (or pathways) to psychosis, anxious depression and bipolar spectrum disorders, respectively. The transdiagnostic framework has been evaluated in young people presenting to youth mental health clinics of the University of Sydney's Brain and Mind Centre, alongside a range of clinical and objective measures. Our research to date provides support for this framework, and we are now exploring its application to the development of more personalised models of care. CHAPTER 3: A COMPREHENSIVE ASSESSMENT FRAMEWORK FOR YOUTH MENTAL HEALTH: GUIDING HIGHLY PERSONALISED AND MEASUREMENT-BASED CARE USING MULTIDIMENSIONAL AND OBJECTIVE MEASURES: There is an urgent need for improved care for young people with mental health problems, in particular those with subthreshold mental disorders that are not sufficiently severe to meet traditional diagnostic criteria. New comprehensive assessment frameworks are needed to capture the biopsychosocial profile of a young person to drive highly personalised and measurement-based mental health care. We present a range of multidimensional measures involving five key domains: social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness type, stage and trajectory. Objective measures include: neuropsychological function; sleep-wake behaviours and circadian rhythms; metabolic and immune markers; and brain structure and function. The recommended multidimensional measures facilitate the development of a comprehensive clinical picture. The objective measures help to further develop informative and novel insights into underlying pathophysiological mechanisms and illness trajectories to guide personalised care plans. A panel of specific multidimensional and objective measures are recommended as standard clinical practice, while others are recommended secondarily to provide deeper insights with the aim of revealing alternative clinical paths for targeted interventions and treatments matched to the clinical stage and proposed pathophysiological mechanisms of the young person. CHAPTER 4: PERSONALISING CARE OPTIONS IN YOUTH MENTAL HEALTH: USING MULTIDIMENSIONAL ASSESSMENT, CLINICAL STAGE, PATHOPHYSIOLOGICAL MECHANISMS, AND INDIVIDUAL ILLNESS TRAJECTORIES TO GUIDE TREATMENT SELECTION: New models of mental health care for young people require that interventions be matched to illness type, clinical stage, underlying pathophysiological mechanisms and individual illness trajectories. Narrow syndrome-focused classifications often direct clinical attention away from other key factors such as functional impairment, self-harm and suicidality, alcohol or other substance misuse, and poor physical health. By contrast, we outline a treatment selection guide for early intervention for adolescent-onset mood and psychotic syndromes (ie, active treatments and indicated and more specific secondary prevention strategies). This guide is based on experiences with the Brain and Mind Centre's highly personalised and measurement-based care model to manage youth mental health. The model incorporates three complementary core concepts: ▶A multidimensional assessment and outcomes framework including: social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness trajectory. ▶Clinical stage. ▶Three common illness subtypes (psychosis, anxious depression, bipolar spectrum) based on three underlying pathophysiological mechanisms (neurodevelopmental, hyperarousal, circadian). These core concepts are not mutually exclusive and together may facilitate improved outcomes through a clinical stage-appropriate and transdiagnostic framework that helps guide decisions regarding the provision of appropriate and effective care options. Given its emphasis on adolescent-onset mood and psychotic syndromes, the Brain and Mind Centre's model of care also respects a fundamental developmental perspective - categorising childhood problems (eg, anxiety and neurodevelopmental difficulties) as risk factors and respecting the fact that young people are in a period of major biological and social transition. Based on these factors, a range of social, psychological and pharmacological interventions are recommended, with an emphasis on balancing the personal benefit-to-cost ratio. CHAPTER 5: A SERVICE DELIVERY MODEL TO SUPPORT HIGHLY PERSONALISED AND MEASUREMENT-BASED CARE IN YOUTH MENTAL HEALTH: Over the past decade, we have seen a growing focus on creating mental health service delivery models that better meet the unique needs of young Australians. Recent policy directives from the Australian Government recommend the adoption of stepped-care services to improve the appropriateness of care, determined by severity of need. Here, we propose that a highly personalised approach enhances stepped-care models by incorporating clinical staging and a young person's current and multidimensional needs. It explicitly aims to prevent progression to more complex and severe forms of illness and is better aligned to contemporary models of the patterns of emergence of psychopathology. Inherent within a highly personalised approach is the incorporation of other evidence-based processes, including real-time measurement-based care and use of multidisciplinary teams of health professionals. Data-driven local system modelling and personalised health information technologies provide crucial infrastructure support to these processes for better access to, and higher quality of, mental health care for young people.

Project Synergy aims to test the potential of new and emerging technologies to enhance the quality of mental health care provided by traditional face-to-face services. Specifically, it seeks to ensure that consumers get the right care, first time (delivery of effective mental health care early in the course of illness). Using co-design with affected individuals, Project Synergy has built, implemented and evaluated an online platform to assist the assessment, feedback, management and monitoring of people with mental disorders. It also promotes the maintenance of wellbeing by collating health and social information from consumers, their supportive others and health professionals. This information is reported back openly to consumers and their service providers to promote genuine collaborative care. The online platform does not provide stand-alone medical or health advice, risk assessment, clinical diagnosis or treatment; instead, it supports users to decide what may be suitable care options. Using an iterative cycle of research and development, the first four studies of Project Synergy (2014-2016) involved the development of different types of online prototypes for young people (i) attending university; (ii) in three disadvantaged communities in New South Wales; (iii) at risk of suicide; and (iv) attending five headspace centres. These contributed valuable information concerning the co-design, build, user testing and evaluation of prototypes, as well as staff experiences during development and service quality improvements following implementation. Through ongoing research and development (2017-2020), these prototypes underpin one online platform that aims to support better multidimensional mental health outcomes for consumers; more efficient, effective and appropriate use of health professional knowledge and clinical skills; and quality improvements in mental health service delivery.

Importance The large contribution of psychiatric disorders to premature death and persistent disability among young people means that earlier identification and enhanced long-term care for those who are most at risk of developing life-threatening or chronic disorders is critical. Clinical staging as an adjunct to diagnosis to address emerging psychiatric disorders has been proposed for young people presenting for care; however, the longer-term utility of this system has not been established. Objectives To determine the rates of transition from earlier to later stages of anxiety, mood, psychotic, or comorbid disorders and to identify the demographic and clinical characteristics that are associated with the time course of these transitions. Design, Setting, and Participants A longitudinal, observational study of 2254 persons aged 12 to 25 years who obtained mental health care at 2 early intervention mental health services in Sydney, Australia, and were recruited to a research register between June 18, 2008, and July 24, 2018 (the Brain and Mind Centre Optymise Cohort). Main Outcomes and Measures The primary outcome of this study was transition from earlier to later clinical stages. A multistate Markov model was used to examine demographic (ie, age, sex, engagement in education, employment, or both) and clinical (ie, social and occupational function, clinical presentation, personal history of mental illness, physical health comorbidities, treatment use, self-harm, suicidal thoughts and behaviors) factors associated with these transitions. Results Of the 2254 individuals included in the study, mean (SD) age at baseline was 18.18 (3.33) years and 1330 (59.0%) were female. Data on race/ethnicity were not available. Median (interquartile range) follow-up was 14 (5-33) months. Of 685 participants at stage 1a (nonspecific symptoms), 253 (36.9%) transitioned to stage 1b (attenuated syndromes). Transition was associated with lower social functioning (hazard ratio [HR], 0.77; 95% CI, 0.66-0.90), engagement with education, employment, or both (HR, 0.47; 95% CI, 0.25-0.91), manic-like experiences (HR, 2.12; 95% CI, 1.19-3.78), psychotic-like experiences (HR, 2.13; 95% CI, 1.38-3.28), self-harm (HR, 1.42; 95% CI, 1.01-1.99), and older age (HR, 1.27; 95% CI, 1.11-1.45). Of 1370 stage 1b participants, 176 (12.8%) transitioned to stage 2 (full-threshold) disorders. Transition was associated with psychotic-like experiences (HR, 2.31; 95% CI, 1.65-3.23), circadian disturbance (HR, 1.66; 95% CI, 1.17-2.35), psychiatric medication (HR, 1.43; 95% CI, 1.03-1.99), childhood psychiatric disorder (HR, 1.62; 95% CI, 1.03-2.54), and older age (HR, 1.24; 95% CI, 1.05-1.45). Conclusions and Relevance Differential rates of progression from earlier to later stages of anxiety, mood, psychotic, or comorbid disorders were observed in young persons who presented for care at various stages. Understanding the rate and factors associated with transition assists planning of stage-specific clinical interventions and secondary prevention trials.

Mental disorders that commonly emerge during adolescence and young adulthood are associated with substantial immediate burden and risks, as well as potentially imparting lifetime morbidity and premature mortality. While the development of health services that are youth focused and prioritize early intervention has been a critical step forward, an ongoing challenge is the heterogeneous nature of symptom profiles and illness trajectories. Consequently, it is often difficult to provide quality mental health care, at scale, that addresses the broad range of health, social, and functional needs of young people. Here, we describe a new digital platform designed to deliver personalized and measurement-based care. It provides health services and clinicians with the tools to directly address the multidimensional needs of young people. The term "personalized" describes the notion that the assessment of, and the sequence of interventions for, mental disorders are tailored to the young person-and their changing needs over time, while "measurement-based" describes the use of systematic and continuing assessment of a young person's outcomes over the entire course of clinical care. Together, these concepts support a framework for care that transcends a narrow focus on symptom reduction or risk reduction. Instead, it prioritizes a broader focus on enhancing social, health, and physical outcomes for young people and a commitment to tracking these outcomes throughout this key developmental period. Now, with twenty-first century technologies, it is possible to provide health services with the tools needed to deliver quality mental health care.

ObjectivesTo report the distribution and predictors of insulin resistance (IR) in young people presenting to primary care-based mental health services.DesignCross-sectional.SettingHeadspace-linked clinics operated by the Brain and Mind Centre of the University of Sydney.Participants768 young people (66% female, mean age 19.7±3.5, range 12–30 years).Main outcome measuresIR was estimated using the updated homeostatic model assessment (HOMA2-IR). Height and weight were collected from direct measurement or self-report for body mass index (BMI).ResultsFor BMI, 20.6% of the cohort were overweight and 10.2% were obese. However, 6.9 mmol/L). By contrast, 9.9% had a HOMA2-IR score >2.0 (suggesting development of IR) and 11.7% (n=90) had a score between 1.5 and 2. Further, there was a positive correlation between BMI and HOMA2-IR (r=0.44, p(2,361)=52.1, pConclusionsEmerging IR is evident in a significant subgroup of young people presenting to primary care-based mental health services. While the major modifiable risk factor is BMI, a large proportion of the variance is not accounted for by other demographic, clinical or treatment factors. Given the early emergence of IR, secondary prevention interventions may need to commence prior to the development of full-threshold or major mood or psychotic disorders.