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A transdiagnostic study of education, employment, and training outcomes in young people with mental illness

Published online by Cambridge University Press:  10 April 2017

R. S. C. Lee ,
D. F. Hermens ,
J. Scott ,
B. O'Dea ,
N. Glozier ,
E. M. Scott  and
I. B. Hickie
R. S. C. Lee*
Affiliation:
Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia Brain and Mental Health Laboratory, Monash University, Melbourne, VIC, Australia
D. F. Hermens
Affiliation:
Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
J. Scott
Affiliation:
Academic Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK Centre for Affective Disorders, Institute of Psychiatry, Psychology and Neuroscience, London, UK
B. O'Dea
Affiliation:
Faculty of Medicine, Black Dog Institute, UNSW, Sydney, NSW, Australia
N. Glozier
Affiliation:
Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
E. M. Scott
Affiliation:
Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
I. B. Hickie
Affiliation:
Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
*
*Address for correspondence: R. S. C. Lee, Ph.D., Brain and Mind Centre, 94 Mallett Street, Camperdown, NSW, Australia. (Email: sze.lee@sydney.edu.au)
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Abstract

Background

Optimizing functional recovery in young individuals with severe mental illness constitutes a major healthcare priority. The current study sought to quantify the cognitive and clinical factors underpinning academic and vocational engagement in a transdiagnostic and prospective youth mental health cohort. The primary outcome measure was ‘not in education, employment or training’ (‘NEET’) status.

Method

A clinical sample of psychiatric out-patients aged 15–25 years (n = 163) was assessed at two time points, on average, 24 months apart. Functional status, and clinical and neuropsychological data were collected. Bayesian structural equation modelling was used to confirm the factor structure of predictors and cross-lagged effects at follow-up.

Results

Individually, NEET status, cognitive dysfunction and negative symptoms at baseline were predictive of NEET status at follow-up (p < 0.05). Baseline cognitive functioning was the only predictor of follow-up NEET status in the multivariate Bayesian model, while controlling for baseline NEET status. For every 1 s.d. deficit in cognition, the probability of being disengaged at follow-up increased by 40% (95% credible interval 19–58%). Baseline NEET status predicted poorer negative symptoms at follow-up (β = 0.24, 95% credible interval 0.04–0.43).

Conclusions

Disengagement with education, employment or training (i.e. being NEET) was reported in about one in four members of this cohort. The initial level of cognitive functioning was the strongest determinant of future NEET status, whereas being academically or vocationally engaged had an impact on future negative symptomatology. If replicated, these findings support the need to develop early interventions that target cognitive phenotypes transdiagnostically.

Keywords

RDoCneurocognitionfunctional outcomeunemploymentNEET
Type
Original Articles
Information
Psychological Medicine , Volume 47 , Issue 12 , September 2017 , pp. 2061 - 2070
Copyright
Copyright © Cambridge University Press 2017 

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