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Protecting brain health is a goal of early intervention. We explored whether sleep quality or chronotype could predict white matter (WM) integrity in emerging mental disorders. Young people (N = 364) accessing early‐intervention clinics underwent assessments for chronotype, subjective sleep quality, and diffusion tensor imaging. Using machine learning, we examined whether chronotype or sleep quality (alongside diagnostic and demographic factors) could predict four measures of WM integrity: fractional anisotropy (FA), and radial, axial, and mean diffusivities (RD, AD and MD). We prioritised tracts that showed a univariate association with sleep quality or chronotype and considered predictors identified by ≥80% of machine learning (ML) models as 'important'. The most important predictors of WM integrity were demographics (age, sex and education) and diagnosis (depressive and bipolar disorders). Subjective sleep quality only predicted FA in the perihippocampal cingulum tract, whereas chronotype had limited predictive importance for WM integrity. To further examine links with mood disorders, we conducted a subgroup analysis. In youth with depressive and bipolar disorders, chronotype emerged as an important (often top‐ranking) feature, predicting FA in the cingulum (cingulate gyrus), AD in the anterior corona radiata and genu of the corpus callosum, and RD in the corona radiata, anterior corona radiata, and genu of corpus callosum. Subjective quality was not important in this subgroup analysis. In summary, chronotype predicted altered WM integrity in the corona radiata and corpus callosum, whereas subjective sleep quality had a less significant role, suggesting that circadian factors may play a more prominent role in WM integrity in emerging mood disorders. [ABSTRACT FROM AUTHOR]

BackgroundAustralia’s mental health care system has long been fragmented and under-resourced, with services falling well short of demand. In response, the World Economic Forum has recently called for the rapid deployment of smarter, digitally enhanced health services to facilitate effective care coordination and address issues of demand. The University of Sydney’s Brain and Mind Centre (BMC) has developed an innovative digital health solution that incorporates 2 components: a highly personalized and measurement-based (data-driven) model of youth mental health care and a health information technology (HIT) registered on the Australian Register of Therapeutic Goods. Importantly, research into implementation of such solutions considers education and training of clinicians to be essential to adoption and optimization of use in standard clinical practice. The BMC’s Youth Mental Health and Technology Program has subsequently developed a comprehensive education and training program to accompany implementation of the digital health solution. ObjectiveThis paper describes the protocol for an evaluation study to assess the effectiveness of the education and training program on the adoption and optimization of use of the digital health solution in service delivery. It also describes the proposed tools to assess the impact of training on knowledge and skills of mental health clinicians. MethodsThe evaluation study will use the Kirkpatrick Evaluation Model as a framework with 4 levels of analysis: Reaction (to education and training), Learning (knowledge acquired), Behavior (practice change), and Results (client outcomes). Quantitative and qualitative data will be collected using a variety of tools, including evaluation forms, pre- and postknowledge questionnaires, skill development and behavior change scales, as well as a real-time clinical practice audit. ResultsThis project is funded by philanthropic funding from Future Generation Global. Ethics approval has been granted via Sydney Local Health District’s Human Research Ethics Committee. At the time of this publication, clinicians and their services were being recruited to this study. The first results are expected to be submitted for publication in 2021. ConclusionsThe education and training program teaches clinicians the necessary knowledge and skills to assess, monitor, and manage complex needs; mood and psychotic syndromes; and trajectories of youth mental ill-health using a HIT that facilitates a highly personalized and measurement-based model of care. The digital health solution may therefore guide clinicians to help young people recover low functioning associated with subthreshold diagnostic presentations and prevent progression to more serious mental ill-health. International Registered Report Identifier (IRRID)PRR1-10.2196/24697

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: Major depressive disorder (MDD) can have severe impacts on function and quality of life. Up to one third of patients will have an inadequate response to their first line of treatment, with subsequent lines of therapy associated with lower remission rates and higher relapse rates. Recently esketamine has become available for Australian patients, and this agent provides an additional treatment option for those with MDD who have had an inadequate response to two or more antidepressant therapies during the current moderate to severe depressive episode. This paper provides an expert panel's practical recommendations and clinical guidance for establishing esketamine clinics in Australia. Methods: An expert panel (n = 11) comprising psychiatrists, mental health care nurses, pharmacists, and individuals with experience establishing esketamine clinics was convened in Sydney. The panel developed practical recommendations and clinical guidance, which were then further refined. Results: Five key areas were identified: practical considerations for esketamine clinic set‐up, including multidisciplinary care considerations; patient selection; administering esketamine; adverse event management and long‐term follow‐up. Conclusions: Guidance presented in this paper should assist Australian clinicians to set up an esketamine clinic, and provide practical advice on the infrastructure and clinical requirements for treatment of patients with this agent. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the potential impact of the recently announced 'Safeguards' initiative on mental health-related emergency department presentation rates for children and adolescents (0−17 years). This state-funded initiative aims to establish 25 Child and Adolescent Acute Response Teams across New South Wales. Methods: We estimated the effects of the 'Safeguards' initiative using a state-level dynamic model of child and adolescent acute mental health care. Potential reductions in total numbers of mental health-related emergency department presentations and re-presentations (i.e. presentations within 3 months of an initial presentation) were assessed via a series of simulation experiments in which we systematically varied the total number of Child and Adolescent Acute Response Teams and the mean duration of care per patient. Results: Assuming a mean treatment duration of 6 weeks per patient, 25 Child and Adolescent Acute Response Teams are projected to reduce total numbers of mental health-related emergency department presentations and re-presentations over the period 2022–2031 by 15.0% (95% interval, 12.0−18.2%) and 31.7% (26.2−37.8%), respectively. Increasing the total number of Child and Adolescent Acute Response Teams above 25 has minimal additional impact on projected reductions in numbers of emergency department presentations and re-presentations, provided the mean duration of care is no more than 8 weeks. However, where the mean duration of care is greater than 4 weeks, a decrease in the number of Child and Adolescent Acute Response Teams below 25 reduces the potential effectiveness of the 'Safeguards' initiative significantly. Conclusion: Our simulation results indicate that full and timely implementation will be critical if the potentially substantial impact of the 'Safeguards' initiative on demand for hospital-based emergency mental health care is to be realised. [ABSTRACT FROM AUTHOR]

Aim: This retrospective cohort study aimed to identify the cardiometabolic characteristics, cross‐sectionally and longitudinally, associated with clinical stage in youth accessing early intervention mental health services. Methods: Cardiometabolic data we collected in 511 young people (aged 12–25 years at entry) receiving mental health care at the early intervention services in Sydney, Australia. Results: The majority of young people (N = 448, 87.67%) were classified in stage 1a or 1b at entry. At entry to care, there was no cross‐sectional relationship between clinical stage and age, gender, fasting insulin, fasting glucose, updated homeostatic model assessment for insulin resistance (HOMA2‐IR) score, BMI or waist circumference. Of the 111 (21.7%) young people initially classified at stage 1a ('non‐specific symptoms') and the 337 (65.9%) classified in stage 1b ('attenuated syndromes'), 40 individuals transitioned to stage 2+ (7.8%) ("full‐threshold disorders") longitudinally. No cardiometabolic factors predicted clinical stage transitions. However, those with an increase in BMI over the course of care (n = 54) were 1.46 (OR; 95% CI: 1.02–2.17) times more likely to progress to stage 2+ at follow up. Conclusions: Whilst no relationships were found between demographic or cardiometabolic variables and clinical stage at entry to care, an increased BMI over time was associated with clinical stage transition longitudinally. Further longitudinal research is needed to understand the demographic, clinical, illness progression or treatment factors associated with changes in cardiometabolic status. [ABSTRACT FROM AUTHOR]

There is significant interest in the possible influence of chronotype on clinical states in young people with emerging mental disorders. We apply a dynamic approach (bivariate latent change score modelling) to examine the possible prospective influence of chronotype on depressive and hypo/manic symptoms in a youth cohort with predominantly depressive, bipolar, and psychotic disorders (N = 118; 14–30-years), who completed a baseline and follow-up assessment of these constructs (mean interval = 1.8-years). Our primary hypotheses were that greater baseline eveningness would predict increases in depressive but not hypo/manic symptoms. We found moderate to strong autoregressive effects for chronotype (β = -0.447 to −0.448, p < 0.001), depressive (β = -0.650, p < 0.001) and hypo/manic symptoms (β = -0.819, p < 0.001). Against our predictions, baseline chronotypes did not predict change in depressive (β = -0.016, p = 0.810) or hypo/manic symptoms (β = 0.077, p = 0.104). Similarly, the change in chronotype did not correlate with the change in depressive symptoms (β = -0.096, p = 0.295) nor did the change in chronotype and the change in hypo/manic symptoms (β = -0.166, p = 0.070). These data suggest that chronotypes may have low utility for predicting future hypo/manic and depressive symptoms in the short term, or that more frequent assessments over longer periods are needed to observe these associations. Future studies should test whether other circadian phenotypes (e.g. sleep-wake variability) are better indicators of illness course. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objectives: Emerging evidence suggests a role of circadian dysrhythmia in the switch between "activation" states (i.e., objective motor activity and subjective energy) in bipolar I disorder. Methods: We examined the evidence with respect to four relevant questions: (1) Are natural or environmental exposures that can disrupt circadian rhythms also related to the switch into high‐/low‐activation states? (2) Are circadian dysrhythmias (e.g., altered rest/activity rhythms) associated with the switch into activation states in bipolar disorder? (3) Do interventions that affect the circadian system also affect activation states? (4) Are associations between circadian dysrhythmias and activation states influenced by other "third" factors? Results: Factors that naturally or experimentally alter circadian rhythms (e.g., light exposure) have been shown to relate to activation states; however future studies need to measure circadian rhythms contemporaneously with these natural/experimental factors. Actigraphic measures of circadian dysrhythmias are associated prospectively with the switch into high‐ or low‐activation states, and more studies are needed to establish the most relevant prognostic actigraphy metrics in bipolar disorder. Interventions that can affect the circadian system (e.g., light therapy, lithium) can also reduce the switch into high‐/low‐activation states. Whether circadian rhythms mediate these clinical effects is an unknown but valuable question. The influence of age, sex, and other confounders on these associations needs to be better characterised. Conclusion: Based on the reviewed evidence, our view is that circadian dysrhythmia is a plausible driver of transitions into high‐ and low‐activation states and deserves prioritisation in research in bipolar disorders. [ABSTRACT FROM AUTHOR]

Background: The nature of sleep-wake abnormalities in individuals with mental disorders remains unclear. The present study aimed to examine the differences in objective ambulatory measures of the sleep-wake and activity cycles across young people with anxiety, mood or psychotic disorders. Methods: Participants underwent several days of actigraphy monitoring. We divided participants into 5 groups (control, anxiety disorder, unipolar depression, bipolar disorder, psychotic disorder) according to primary diagnosis. Results: We enrolled 342 participants aged 12-35 years in our study: 41 healthy controls, 56 with anxiety disorder, 135 with unipolar depression, 80 with bipolar disorder and 30 with psychotic disorders. Compared with the control group, sleep onset tended to occur later in the anxiety, depression and bipolar groups; sleep offset occurred later in all primary diagnosis groups; the sleep period was longer in the anxiety, bipolar and psychosis groups; total sleep time was longer in the psychosis group; and sleep efficiency was lower in the depression group, with a similar tendency for the anxiety and bipolar groups. Sleep parameters were significantly more variable in patient subgroups than in controls. Cosinor analysis revealed delayed circadian activity profiles in the anxiety and bipolar groups and abnormal circadian curve in the psychosis group. Limitations: Although statistical analyses controlled for age, the sample included individuals from preadolescence to adulthood. Most participants from the primary diagnosis subgroups were taking psychotropic medications, and a large proportion had other comorbid mental disorders. Conclusion: Our findings suggest that delayed and disorganized sleep offset times are common in young patients with various mental disorders. However, other sleep-wake cycle disturbances appear to be more prominent in broad diagnostic categories., Introduction Sleep-wake cycle disturbances are part of the symptomatology of several mental disorders and commonly exacerbate the clinical profiles of such disorders. For instance, sleep-wake disturbances have been associated with [...]

Objective: Youth with early-onset mood or psychotic disorders are occasionally prescribed metformin to manage cardiometabolic risk. This retrospective study explores the demographic, clinical and metabolic factors associated with metformin prescription youth with mood or psychotic disorders. Method: Participants included 72 youth with mood or psychotic disorders from a young adult mental health inpatient unit, of which 18 (33%) were newly prescribed metformin, and 54 (66%) were not prescribed metformin. Demographic and clinical information were extracted from the patients' medical files along with body mass index (BMI), fasting serum bloods and calculated updated homeostatic model of insulin resistance assessment (HOMA2-IR) scores to compare profiles between groups. Results: Of those prescribed metformin, 83% were overweight or obese and 72% had elevated HOMA2-IR scores. Of those not receiving metformin treatment, 41% were overweight or obese and 22% had elevated HOMA2-IR scores. Youth prescribed metformin had significantly higher BMI, and elevated markers of insulin resistance, but did not differ to those not prescribed metformin on other demographic, clinical or metabolic factors. Conclusions: While metformin is prescribed to some youth with mood or psychotic disorders displaying markers of cardiometabolic disturbance, there is a need to develop clearer treatment guidelines for metformin in these youth. [ABSTRACT FROM AUTHOR]

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Aim: Young people with common mood disorders face the prospect of shortened life expectancy largely due to premature cardiovascular disease. Metabolic dysfunction is a risk factor for premature cardiovascular disease. There is an ongoing debate whether metabolic dysfunction can be simply explained by weight gain secondary to psychotropic medications or whether shared genetic vulnerability, intrinsic immune‐metabolic disturbances or other system perturbations (e.g. dysregulated sympathetic nervous system, circadian dysfunction) are more relevant determinants of premature cardiovascular disease. Thus, we aimed to investigate underlying drivers of metabolic dysfunction and premature cardiovascular disease in young people in the early phases of common mood disorders. Methods: We evaluated the relationships between insulin resistance (assessed by HOMA2‐IR) and body mass index (BMI), sex, diagnosis, medication, inflammatory markers and hormonal factors in 327 inpatients with emerging affective and major mood disorders admitted to the Young Adult Mental Health Unit, St Vincent's Private Hospital, Sydney. Results: While HOMA2‐IR scores were positively associated with BMI (rs = 0.465, p <.001), they were also higher in those prescribed mood stabilizers (p =.044) but were not associated with specific diagnoses, other medication types or the number of prescribed medications. Further, high‐sensitivity C‐reactive protein levels (but not thyroid‐stimulating hormone and ferritin levels) were positively associated with HOMA2‐IR (rs = 0. 272, p <.001) and BMI (rs =. 409, p <.001). Conclusions: In addition to BMI, other non‐specific markers of inflammation are associated with early metabolic dysfunction in young people with emerging affective and major mood disorders. [ABSTRACT FROM AUTHOR]

Background: Predictors 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. Method: Multi-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. Results: Of 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. Conclusions: Identifying 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper presents a case study of an innovative direct-to-consumer preclinic triage system designed to reduce predicted peak demand for Australian mental health services as a result of COVID-19 and its associated socioeconomic consequences by guiding Australians to the right mental health care first time. Our innovative, digital health solution comprises two components: (1) a highly personalised and measurement-based model of care (Brain and Mind Centre model of care) that considers both the heterogeneity of mental disorders and other underlying comorbidities, as well as clinical staging; and (2) a health information technology (i.e. the InnoWell Platform). This digital health solution has been embedded as part of standard service delivery into a community-based intake service, thus resulting in a redesigned service model. The service model is currently being implemented as part of a pilot feasibility study, the marker of acceptability at the health professional and service level, and is now under active evaluation to determine its effect on outcomes for consumers, health professionals and the service. For the purposes of this paper, this model served as a prototype for the preclinic triage system that was conceptualised for national scalability at the primary health network level. When implemented at a national level, our direct-to-consumer preclinic triage system is expected to be an effective population health demand management strategy to address the rapidly emerging mental health demand crisis in Australia, and is aligned with the recent recommendation from the Productivity Commission to develop a sustainable national digital platform to facilitate the assessment and referral process to ensure access to mental health care matched to an individual's level of need. What is known about the topic?: Although there is increased recognition of the mental health demand crisis in Australia as a result of the COVID-19 pandemic, little has been done to 'flatten' the curve. The Australian Government committed additional funding to support the Better Access Pandemic Support measure; however, this approach to care fails to appreciate both the disparities in service availability across Australia and the gap fees that are prohibitive to some of those seeking help. Furthermore, the expansion of this program may only result in those in care remaining in care, thus further delaying access to those in need. What does this paper add?: This paper describes a digital health solution, comprised of a highly personalised and measurement-based model of care coupled with a health information technology, that has been embedded as part of standard service delivery. Consumers seeking mental health care complete a multidimensional self-report assessment via the technology, the results of which are available in real-time and used to facilitate triage to pathways of care as indicated by the severity of the consumer's illness and level of need to more effectively and efficiently allocate consumers to care. The redesigned service model is now under active evaluation to determine its effects on outcomes at consumer, health professional and service levels. What are the implications for practitioners?: The redesigned local service model served as a prototype for our innovative direct-to-consumer preclinic triage system specifically designed to allocate consumers to self-management, ambulatory care or acute care based on clinical stage and level of need. It is our hypothesis that the preclinic triage system will be an effective population health demand management strategy. Importantly, the proposed preclinic triage system aligns with the recent recommendation from the Productivity Commission for the Australian Government to fund the development and sustained implementation of a digital platform to facilitate assessment and referral to evidence-based interventions matched to a consumer's level of need. [ABSTRACT FROM AUTHOR]