Recently, there has been increased focus on sub-threshold stages of mental disorders, with attempts to model and predict progression to full-threshold disorder. Given this considerable research attention and clinical significance, it is timely to analyse the assumptions of theoretical models in the field. Research into predicting onset of mental disorder has shown an overreliance on one-off sampling of cross-sectional data (i.e., a "snapshot" of clinical state and other risk markers) and may benefit from taking dynamic changes into account. Cross-disciplinary approaches to complex system structures and changes, such as dynamical systems theory, network theory, instability mechanisms, chaos theory and catastrophe theory, offer potent models that can be applied to emergence (or decline) of psychopathology, including psychosis prediction and transdiagnostic symptom emergence. Staging provides a useful framework to research dynamic prediction in psychiatry. Psychiatric research may benefit from approaching psychopathology as a system rather than a category, identifying dynamics of system change (e.g., abrupt/gradual psychosis onset), factors to which these systems are most sensitive (e.g., interpersonal dynamics, neurochemical change), and individual variability in system architecture and change. The next generation of prediction studies may more accurately model the highly dynamic nature of psychopathology and system change, with treatment implications, such as introducing a means of identifying critical risk periods for mental state deterioration.

Diagnosis plays a critical role in guiding treatment selection and predicting potential outcomes or the illness course. Traditional psychiatric diagnostic systems have largely failed to facilitate this. Clinical staging in psychiatry has emerged as a potential solution and offers the benefit of linking stage of illness to interventions that are proportional to both current need and the risk of progression. However, the model remains largely heuristic and is not yet fit for purpose in the clinical realm. In this concluding chapter, future directions to evolve and enhance clinical staging as a practical framework are proposed. At a fundamental level, there remain questions as to whether staging can span the full range of mental ill health and onsets across the lifespan. Efforts to create an international consensus model for transdiagnostic clinical staging are underway. Such a consensus could facilitate a coordinated global approach to research and may assist in resolving outstanding questions. To strengthen clinical staging, future research should involve a range of research methodologies and designs, including ecological momentary assessment, machine learning, and sequential clinical trials, which involve transdiagnostic cohorts of patients. In particular, research that integrates clinical staging and dynamic prediction approaches, such as network analysis and joint modelling, can contribute to refining the prediction of onset and course of mental illness and better guide intervention. Ultimately, the true value of clinical staging will be realised if it becomes a fundamental pillar of the diagnostic approach in mental health and becomes a pathway to superior treatment options that are more personalised and preventive in nature.

The identification of people at high risk for future mental disorders is accompanied by the imperative to provide stage-adequate treatments that successfully prevent progression to more severe illness stages. Current evidence-based treatments include psychological and psychosocial treatments on one hand as well as pharmacotherapy. The latter is limited by inadequate efficacy and prominent side effects in many cases, making the discovery of novel biological treatment strategies necessary. Such novel treatments need to be safe, effective, characterised by a benign side effect profile and accessible to young people. In this chapter, emerging biological treatment approaches are reviewed and discussed in regard to their potential impact on early intervention and clinical staging. Substances reviewed here include long-chain omega-3 fatty acids (fish oil), n-acetylcysteine (NAC), cannabidiol and repeated transcranial magnetic stimulation (rTMS) with a particular focus on recent advancements in their application in youth with incipient mental disorders. Finally, research priorities in the field of treatment trials are discussed in this chapter.

Over the last two decades application of the clinical staging model in mental health has been advocated to improve diagnosis, intervention, prediction of illness trajectory and, ultimately, outcomes. The model offers a substantive advance for mental health care as it goes beyond traditional fixed categories to incorporate a stepwise continuum to guide much more appropriate treatment planning and prognosis. In this chapter, an overview of this advanced type of clinical staging is provided. With its focus on the continuum of mental illness, and underlying differential trajectories of illness progression that are not well captured by current categorical diagnostic practice, staging addresses the key limitations of traditional diagnostic categorical systems. It proposes that effective, safe and timely stage-specific treatments can be implemented to inhibit and delay illness onset and progression. It also enables biomarkers to be analysed according not only to syndrome but also stage. The model is supported by a number of clinical, longitudinal and neurobiological studies. Whilst clinical staging has clear and immediate potential benefits, further research investigating risk and protective factors and treatment outcomes across different stages and the creation of tools that clinicians can routinely use will determine the ultimate utility and value of the model.

For over a decade a transdiagnostic clinical staging framework for youth with anxiety, mood and psychotic disorders (linked with measurement of multidimensional outcomes), has been utilised in over 8,000 young people presenting to the enhanced primary (headspace) and secondary care clinics of the Brain and Mind Centre of the University of Sydney. This framework has been evaluated alongside a broad range of other clinical, neurobiological, neuropsychological, brain imaging, circadian, metabolic, longitudinal cohort and controlled intervention studies. This has led to specific tests of its concurrent, discriminant and predictive validity. These extensive data provide strong preliminary evidence that: i) varying stages of illness are associated with predicted differences in a range of independent and objectively measured neuropsychological and other biomarkers (both cross-sectionally and longitudinally); and, ii) that earlier stages of illness progress at variable rates to later and more severe or persistent disorders. Importantly, approximately 15-20% of those young people classed as stage 1b or ‘attenuated’ syndromes at presentation progress to more severe or persistent disorders. Consequently, this cohort should be the focus of active secondary prevention trials. In clinical practice, we are moving to combine the staging framework with likely pathophysiological paths (e.g. neurodevelopmental-psychotic, anxiety-depression, circadian-bipolar) to underpin enhanced treatment selection.

Although mental health issues are the key health concern for young people, contributing 45% of the total burden of disease for those aged 10-24 years, young people have the poorest access to mental health care. Current service approaches are insufficient, poorly designed and not well supported. Transformational reform of mental health care is needed, based on principles of evidence-informed care, early intervention, and a focus on the developmental period of greatest need and capacity to benefit from investment: emerging adulthood. The most appropriate care models for this period place emphasis on offering care that is appropriate to early stages of illness, pre-emptive in nature, and with a strong preventive focus. This sits best with a clinical staging approach, which distinguishes earlier and milder clinical phenomena from those that accompany illness progression and chronicity. This provides a clinically useful framework that is sensitive to risk/benefit considerations and facilitates the selection of earlier, safer interventions, and favours a preventive or pre-emptive treatment approach. In this chapter, rapidly emerging examples of modern, stigma-free cultures of care designed and operated with young people themselves are described. This includes headspace and technologically enhanced service delivery models. Future directions for youth services are also described.

Although mental health issues are the key health concern for young people, contributing 45% of the total burden of disease for those aged 10-24 years, young people have the poorest access to mental health care. Current service approaches are insufficient, poorly designed and not well supported. Transformational reform of mental health care is needed, based on principles of evidence-informed care, early intervention, and a focus on the developmental period of greatest need and capacity to benefit from investment: emerging adulthood. The most appropriate care models for this period place emphasis on offering care that is appropriate to early stages of illness, pre-emptive in nature, and with a strong preventive focus. This sits best with a clinical staging approach, which distinguishes earlier and milder clinical phenomena from those that accompany illness progression and chronicity. This provides a clinically useful framework that is sensitive to risk/benefit considerations and facilitates the selection of earlier, safer interventions, and favours a preventive or pre-emptive treatment approach. In this chapter, rapidly emerging examples of modern, stigma-free cultures of care designed and operated with young people themselves are described. This includes headspace and technologically enhanced service delivery models. Future directions for youth services are also described.

A fundamental aim of diagnosis is to guide treatment planning and predict illness course. Yet for too long psychiatric diagnosis, grounded on traditional silo-based approaches, has lacked clinical utility. This chapter explores the purpose of diagnosis and classification as well as the inability to validate diagnosis in psychiatry. It is proposed that new testable models are needed to improve the utility of diagnosis and support more personalised and sequential treatment selection. A number of new approaches have been put forward, including hierarchical and network-based methods, however at present, these offer limited value in guiding treatment selection. Clinical staging offers a viable solution. Clinical staging in psychiatry recognises that mental disorders are not static and discretely defined entities, but rather they are syndromes that overlap and develop in stages. The model ensures that interventions are proportional to both need and the risk of progressing to later stages and more established syndromes, which are likely to be comorbid, persistent, recurrent and disabling. Ultimately, it advocates a transdiagnostic approach to intervention, with a pre-emptive focus, that is based on risk-benefit considerations and patient needs. Clinical staging also provides a framework in which underlying biological mechanisms can be linked to each stage, to build a personalised and pre-emptive psychiatry.

A fundamental aim of diagnosis is to guide treatment planning and predict illness course. Yet for too long psychiatric diagnosis, grounded on traditional silo-based approaches, has lacked clinical utility. This chapter explores the purpose of diagnosis and classification as well as the inability to validate diagnosis in psychiatry. It is proposed that new testable models are needed to improve the utility of diagnosis and support more personalised and sequential treatment selection. A number of new approaches have been put forward, including hierarchical and network-based methods, however at present, these offer limited value in guiding treatment selection. Clinical staging offers a viable solution. Clinical staging in psychiatry recognises that mental disorders are not static and discretely defined entities, but rather they are syndromes that overlap and develop in stages. The model ensures that interventions are proportional to both need and the risk of progressing to later stages and more established syndromes, which are likely to be comorbid, persistent, recurrent and disabling. Ultimately, it advocates a transdiagnostic approach to intervention, with a pre-emptive focus, that is based on risk-benefit considerations and patient needs. Clinical staging also provides a framework in which underlying biological mechanisms can be linked to each stage, to build a personalised and pre-emptive psychiatry.