Hostname: page-component-5d59c44645-klj7v Total loading time: 0 Render date: 2024-02-21T19:50:12.859Z Has data issue: false hasContentIssue false

Predicting early transition from sub-syndromal presentations to major mental disorders

Published online by Cambridge University Press:  02 January 2018

Shane P.M. Cross*
Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
Jan Scott
Academic Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle, UK
Ian B. Hickie
Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
Shane P.M. Cross, Brain and Mind Centre, University of Sydney, 100 Mallet Street, Camperdown, NSW 2050, Australia. E-mail:
Rights & Permissions [Opens in a new window]


Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Transition from at-risk state to full syndromal mental disorders is underexplored for unipolar and bipolar disorders compared with psychosis.


Prospective, trans-diagnostic study of rates and predictors of early transition from sub-threshold to full syndromal mental disorder.


One-year outcome of 243 consenting youth aged 15–25 years with a sub-syndromal presentation of a potentially severe mental disorder. Survival analysis and odds ratio (OR) for predictors of transition identified from baseline clinical and demographic ratings.


About 17% (n=36) experienced transition to a major mental disorder. Independent of syndromal diagnosis, transition was significantly more likely in individuals who were NEET (not in education, employment or training), in females and in those with more negative psychological symptoms (e.g. social withdrawal).


NEET status and negative symptoms are modifiable predictors of illness trajectory across diagnostic categories and are not specific to transition to psychosis.

Copyright © The Royal College of Psychiatrists 2017


Declaration of interest

I.B.H. has been a Commissioner in Australia's National Mental Health Commission since 2012. He was a board member of headspace: National Youth Mental Health Foundation until January 2012. He has led a range of community-based and pharmaceutical industry-supported depression awareness and education and training programmes. He has led projects for health professionals and the community supported by governmental, community agency and pharmaceutical industry partners (Wyeth, Eli Lilly, Servier, Pfizer, AstraZeneca) for the identification and management of depression and anxiety. He has received honoraria for presentations of his own work at educational seminars supported by a number of non-government organisations and the pharmaceutical industry (including Servier, Pfizer, AstraZeneca and Eli Lilly). He is a member of the Medical Advisory Panel for Medibank Private and also a board member of Psychosis Australia Trust. He leads an investigator-initiated study of the effects of agomelatine on circadian parameters (supported in part by Servier) and has participated in a multicentre clinical trial of the effects of agomelatine on sleep architecture in depression and a Servier-supported study of major depression and sleep disturbance in primary care settings.


1 Gore, FM, Bloem, PJN, Patton, GC, Ferguson, J, Joseph, V, Coffey, C, et al. Global burden of disease in young people aged 10–24 years: a systematic analysis. Lancet 2011; 377: 2093–102.CrossRefGoogle ScholarPubMed
2 Kessler, RC, Amminger, GP, Aguilar-Gaxiola, S, Alonso, J, Lee, S, Ustun, TB. Age of onset of mental disorders: a review of recent literature. Curr Opin Psychiatry 2007; 20: 359–64.CrossRefGoogle ScholarPubMed
3 Hickie, I, Scott, J, McGorry, P. Clinical staging for mental disorders: a new development in diagnostic practice in mental health. Med J Aust 2013; 198: 461–2.CrossRefGoogle ScholarPubMed
4 Scott, J, Leboyer, M, Hickie, I, Berk, M, Kapczinski, F, Frank, E, et al. Clinical staging in psychiatry: a cross-cutting model of diagnosis with heuristic and practical value. Br J Psychiatry 2013; 202: 243–5.CrossRefGoogle ScholarPubMed
5 Hartmann, JA, Yuen, HP, McGorry, PD, Yung, AR, Lin, A, Wood, SJ, et al. Declining transition rates to psychotic disorder in “ultra-high risk” clients: investigation of a dilution effect. Schizophr Res 2016; 170: 130–6.CrossRefGoogle ScholarPubMed
6 Simon, AE, Velthorst, E, Nieman, DH, Linszen, D, Umbricht, D, de Haan, L. Ultra high-risk state for psychosis and non-transition: a systematic review. Schizophr Res 2011; 132: 817.CrossRefGoogle ScholarPubMed
7 Simon, AE, Borgwardt, S, Riecher-Rössler, A, Velthorst, E, de Haan, L, Fusar-Poli, P. Moving beyond transition outcomes: meta-analysis of remission rates in individuals at high clinical risk for psychosis. Psychiatry Res 2013; 209: 266–72.CrossRefGoogle ScholarPubMed
8 Cross, SP, Hermens, DF, Scott, EM, Ottavio, A, McGorry, PD, Hickie, IB. A clinical staging model for early intervention youth mental health services. Psychiatr Serv 2014; 65: 939–43.CrossRefGoogle ScholarPubMed
9 Cross, SP, Hermens, DF, Hickie, IB. Treatment patterns and short-term outcomes in an early intervention youth mental health service. Early Interv Psychiatry 2014.Google Scholar
10 Cross, SPM, Hermens, DF, Scott, J, Salvador-Carulla, L, Hickie, IB. Differential impact of current diagnosis and clinical stage on attendance at a youth mental health service. Early Interv Psychiatry 2017; 11: 255–62.CrossRefGoogle Scholar
11 Fusar-Poli, P, Yung, AR, McGorry, P, van Os, J. Lessons learned from the psychosis high-risk state: towards a general staging model of prodromal intervention. Psychol Med 2014; 44: 1724.CrossRefGoogle ScholarPubMed
12 Valmaggia, L, Stahl, D, Yung, A, Nelson, B, Fusar-Poli, P, McGorry, P, et al. Negative psychotic symptoms and impaired role functioning predict transition outcomes in the at-risk mental state: a latent class cluster analysis study. Psychol Medicine 2013; 43: 2311–25.CrossRefGoogle Scholar
13 Yung, AR, Phillips, LJ, Yuen, HP, Francey, SM, McFarlane, CA, Hallgren, M, et al. Psychosis prediction: 12-month follow up of a high-risk (“prodromal”) group. Schizophr Res 2003; 60: 2132.CrossRefGoogle ScholarPubMed
14 Dragt, S, Nieman, DH, Veltman, D, Becker, HE, van de Fliert, R, de Haan, L, et al. Environmental factors and social adjustment as predictors of a first psychosis in subjects at ultra high risk. Schizophr Res 2011; 125: 6976.CrossRefGoogle ScholarPubMed
15 Fusar-Poli, P, Byrne, M, Valmaggia, L, Day, F, Tabraham, P, Johns, L, et al. Social dysfunction predicts two years clinical outcome in people at ultra high risk for psychosis. J Psychiatr Res 2010; 44: 294301.CrossRefGoogle ScholarPubMed
16 Ising, H, Ruhrmann, S, Burger, N, Rietdijk, J, Dragt, S, Klaassen, R, et al. Development of a stage-dependent prognostic model to predict psychosis in ultra-high-risk patients seeking treatment for co-morbid psychiatric disorders. Psychol Med 2016; 46: 1839–51.CrossRefGoogle ScholarPubMed
17 Scott, J, Fowler, D, McGorry, P, Birchwood, M, Killackey, E, Christensen, H, et al. Adolescents and young adults who are not in employment, education, or training. BMJ 2013; 347: f5270.CrossRefGoogle ScholarPubMed
18 Hickie, IB, Scott, EM, Hermens, DF, Naismith, SL, Guastella, AJ, Kaur, M, et al. Applying clinical staging to young people who present for mental health care. Early Interv Psychiatry 2013; 7: 3143.CrossRefGoogle ScholarPubMed
19 McGorry, P, Tanti, C, Stokes, R, Hickie, I, Carnell, K, Littlefield, L, et al. headspace: Australia's National Youth Mental Health Foundation – where young minds come first. Med J Aust 2007; 187: S6870.CrossRefGoogle ScholarPubMed
20 Kessler, RC, Andrews, G, Colpe, LJ, Hiripi, E, Mroczek, DK, Normand, SLT, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med 2002; 32: 959–76.CrossRefGoogle ScholarPubMed
21 Shafer, A. Meta-analysis of the brief psychiatric rating scale factor structure. Psychol Assess 2005; 17: 324–35.CrossRefGoogle ScholarPubMed
22 Goldman, H, Skodol, A, Lave, T. Revising axis V for DSM-IV: a review of measures of social functioning. Am J Psychiatry 1992; 149: 1148–56.Google ScholarPubMed
23 O’Dea, B, Glozier, N, Purcell, R, McGorry, PD, Scott, J, Feilds, K-L, et al. A cross-sectional exploration of the clinical characteristics of disengaged (NEET) young people in primary mental healthcare. BMJ Open. 2014; 4: e006378.CrossRefGoogle ScholarPubMed
24 O’Connor, K, Nelson, B, Lin, A, Wood, SJ, Yung, A, Thompson, A. Are UHR patients who present with hallucinations alone at lower risk of transition to psychosis? Psychiatry Res 2015; 235: 177–96.Google ScholarPubMed
25 Baggio, S, Iglesias, K, Deline, S, Studer, J, Henchoz, Y, Mohler-Kuo, M, et al. Not in education, employment, or training status among young Swiss men. Longitudinal associations with mental health and substance use. J Adolesc Health 2015; 56: 238–43.CrossRefGoogle ScholarPubMed
26 Brandizzi, M, Valmaggia, L, Byrne, M, Jones, C, Iwegbu, N, Badger, S, et al. Predictors of functional outcome in individuals at high clinical risk for psychosis at six years follow-up. J Psychiatr Res 2015; 65: 115–23.CrossRefGoogle ScholarPubMed
Submit a response


No eLetters have been published for this article.