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Lookup NU author(s): Emeritus Professor Jan Scott
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Copyright © Cambridge University Press 2017 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.
Author(s): Lee RSC, Hermens DF, Scott J, O'Dea B, Glozier N, Scott EM, Hickie IB
Publication type: Article
Publication status: Published
Journal: Psychological Medicine
Print publication date: 01/09/2017
Online publication date: 10/04/2017
Acceptance date: 01/02/2017
ISSN (print): 0033-2917
ISSN (electronic): 1469-8978
Publisher: Cambridge University Press
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