Statistical and artificial intelligence techniques to identify risk factors for suicide in children and adolescents.

Journal: Science progress
PMID: 37787380

Abstract

BACKGROUND: Suicidal Behaviors and Thoughts are a relevant public health issue that includes suicidal ideation, non-suicidal self-harm, attempted suicide, and failed suicides. Since there is a progression of suicidal behaviors, whereby suicide is more likely to be completed if there have already been previous behaviors or attempts to harm oneself, WHO has highlighted the need to detect early predictors of such suicidal behaviors, which can help identify individuals at risk, plan prevention strategies and implement specific therapeutic interventions, particularly in young people, thus reducing the number of deaths. This retrospective observational study aimed to identify early predictors of suicidal risk in 237 inpatients admitted for Suicidal Behaviors and Thoughts at Child and Adolescent Psychiatry Emergency Unit of the Meyer Children's Hospital, Florence, Italy.

Authors

  • Michaela Servi
  • Silvia Chiaro
    Child Neurology and Psychiatry Unit, Neuroscience Department, Children's Hospital A. Meyer IRCCS, Florence, Italy.
  • Elisa Mussi
  • Giovanni Castellini
    Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, Italy.
  • Alberta Mereu
    Department of Mental Health and Pathological Addiction, UOSD Child and Adolescent Psychiatry and Psychotherapy, Maggiore Hospital "C.A. Pizzardi" Largo B. Nigrisoli 2, Bologna, Italy.
  • Yary Volpe
  • Tiziana Pisano
    Child Neurology and Psychiatry Unit, Neuroscience Department, Children's Hospital A. Meyer IRCCS, Florence, Italy.

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