A prognostic model for predicting functional impairment in youth mental health services DOI Creative Commons
Frank Iorfino, Rafael Oliveira,

Sally Cripps

et al.

European Psychiatry, Journal Year: 2024, Volume and Issue: 67(1)

Published: Jan. 1, 2024

Abstract Background Functional impairment is a major concern among those presenting to youth mental health services and can have profound impact on long-term outcomes. Early recognition prevention for at risk of functional essential guide effective care. Yet, identifying challenging impacts the appropriate allocation indicated early intervention strategies. Methods We developed prognostic model predict young person’s social occupational trajectory over 3 months. The sample included 718 people (12–25 years) engaged in A Bayesian random effects was designed using demographic clinical factors performance evaluated held-out test data via 5-fold cross-validation. Results Eight were identified as optimal set prediction: employment, education, or training status; self-harm; psychotic-like experiences; physical comorbidity; childhood-onset syndrome; illness type; stage; circadian disturbances. had an acceptable area under curve (AUC) 0.70 (95% CI, 0.56–0.81) overall, indicating its utility predicting For with good baseline functioning, it showed excellent (AUC = 0.80, 0.67–0.79) individuals deterioration. Conclusions validated trajectories 3-month period. This serves foundation further tool development demonstrates potential enhancing outcomes preventing decline.

Language: Английский

A prognostic model for predicting functional impairment in youth mental health services DOI Creative Commons
Frank Iorfino, Rafael Oliveira,

Sally Cripps

et al.

European Psychiatry, Journal Year: 2024, Volume and Issue: 67(1)

Published: Jan. 1, 2024

Abstract Background Functional impairment is a major concern among those presenting to youth mental health services and can have profound impact on long-term outcomes. Early recognition prevention for at risk of functional essential guide effective care. Yet, identifying challenging impacts the appropriate allocation indicated early intervention strategies. Methods We developed prognostic model predict young person’s social occupational trajectory over 3 months. The sample included 718 people (12–25 years) engaged in A Bayesian random effects was designed using demographic clinical factors performance evaluated held-out test data via 5-fold cross-validation. Results Eight were identified as optimal set prediction: employment, education, or training status; self-harm; psychotic-like experiences; physical comorbidity; childhood-onset syndrome; illness type; stage; circadian disturbances. had an acceptable area under curve (AUC) 0.70 (95% CI, 0.56–0.81) overall, indicating its utility predicting For with good baseline functioning, it showed excellent (AUC = 0.80, 0.67–0.79) individuals deterioration. Conclusions validated trajectories 3-month period. This serves foundation further tool development demonstrates potential enhancing outcomes preventing decline.

Language: Английский

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