Age-stratified predictions of suicide attempts using machine learning in middle and late adolescence.

Journal: Journal of affective disorders
PMID: 39142588

Abstract

BACKGROUND: Prevalence of suicidal behaviour increases rapidly in middle to late adolescence. Predicting suicide attempts across different ages would enhance our understanding of how suicidal behaviour manifests in this period of rapid development. This study aimed to develop separate models to predict suicide attempts within a cohort at middle and late adolescence. It also sought to examine differences between the models derived across both developmental stages.

Authors

  • Karen Kusuma
    University of New South Wales, Sydney, NSW 2052, Australia. Electronic address: k.kusuma@unsw.edu.au.
  • Mark Larsen
    University of New South Wales, Sydney, NSW 2052, Australia.
  • Juan C Quiroz
    Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
  • Michelle Torok
    Black Dog Institute, University of New South Wales, Randwick, NSW, Australia.

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