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Beyond the “at risk mental state” concept: transitioning to transdiagnostic psychiatry
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The “at risk mental state” for psychosis approach has been a catalytic, highly productive research paradigm over the last 25 years. In this paper we review that paradigm and summarize its key lessons, which include the valence of this phenotype for future psychosis outcomes, but also for comorbid, persistent or incident non‐psychotic disorders; and the evidence that onset of psychotic disorder can at least be delayed in ultra high risk (UHR) patients, and that some full‐threshold psychotic disorder may emerge from risk states not captured by UHR criteria. The paradigm has also illuminated risk factors and mechanisms involved in psychosis onset. However, findings from this and related paradigms indicate the need to develop new identification and diagnostic strategies. These findings include the high prevalence and impact of mental disorders in young people, the limitations of current diagnostic systems and risk identification approaches, the diffuse and unstable symptom patterns in early stages, and their pluripotent, transdiagnostic trajectories. The approach we have recently adopted has been guided by the clinical staging model and adapts the original “at risk mental state” approach to encompass a broader range of inputs and output target syndromes. This approach is supported by a number of novel modelling and prediction strategies that acknowledge and reflect the dynamic nature of psychopathology, such as dynamical systems theory, network theory, and joint modelling. Importantly, a broader transdiagnostic approach and enhancing specific prediction (profiling or increasing precision) can be achieved concurrently. A holistic strategy can be developed that applies these new prediction approaches, as well as machine learning and iterative probabilistic multimodal models, to a blend of subjective psychological data, physical disturbances (e.g., EEG measures) and biomarkers (e.g., neuroinflammation, neural network abnormalities) acquired through fine‐grained sequential or longitudinal assessments. This strategy could ultimately enhance our understanding and ability to predict the onset, early course and evolution of mental ill health, further opening pathways for preventive interventions.
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“Transdiagnostic models 197,198 recognise the fluid nature of mental illness in this age group and make a distinction between early clinical stages (which are assumed to have low rates of progression to severe, persistent, or recurrent disorders) and later stages (which are characterised by high rates of persistence, impairment, and disease extension). 199”
From The Lancet Psychiatry Commission on youth mental health (2024) · cites this paper as [198]
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“Although indicated prevention is currently the most promising avenue for preventive efforts, 198,275 universal and selective interventions also have value. 276,277”
From The Lancet Psychiatry Commission on youth mental health (2024) · cites this paper as [198]
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“These earliest expressions of psychopathology have high rates of co-occurrence, change from one clinical picture to another, and only gradually differentiate into more distinct mental disorders [67, 69, 70].”
From Efficacy of a transdiagnostic Internet prevention approach in adolescents (EMPATIA study): study protocol of a randomized controlled trial (2024) · cites this paper as [67]
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“The need to establish a 'threshold' for subsyndromal depression in order to distinguish it from 'ordinary feelings of sadness' has been widely acknowledged, and different solutions have been proposed. 61”
From Time for united action on depression: a Lancet–World Psychiatric Association Commission (2022) · cites this paper as [61]
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“But prevalence of subthreshold syndromes of depressive symptoms with shorter duration (typically two weeks) is as high as 17%. 61,169”
From Time for united action on depression: a Lancet–World Psychiatric Association Commission (2022) · cites this paper as [61]
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Metadata
- Authors
- McGorry, P. D., Hartmann, J. A., Spooner, R., & Nelson, B.
- Affiliations
- The University of Melbourne (AU)
- Venue
- World Psychiatry
- Publisher
- Wiley
- Published
- 2018-05-24
- Volume
- 17
- Issue
- 2
- Pages
- 133-142
- ISSN
- 1723-8617 (ISSN-L)
- 2051-5545
- PMC
- PMC5980504
- OpenAlex
- W2806195288
- Cited by
- 488
- References
- 95
- Citations by year
- 2026: 48 · 2025: 51 · 2024: 65 · 2023: 61 · 2022: 57 · 2021: 86 · 2020: 59 · 2019: 46 · 2018: 13
- FWCI
- 40.13
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- World Psychiatry (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Social Sciences › Arts and Humanities › Philosophy › Mental Health and Psychiatry
- Keywords
- clinical high risk for psychosis, transdiagnostic psychiatry, psychosis onset prediction, clinical staging model, psychosis risk syndromes, persistent psychosis, dynamical systems theory, network theory, joint modeling, machine learning, multimodal biomarkers, neuroinflammation, EEG biomarkers
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