A Controlled Trial Using Natural Language Processing to Examine the Language of Suicidal Adolescents in the Emergency Department

Suicide Life Threat Behav. 2016 Apr;46(2):154-9. doi: 10.1111/sltb.12180. Epub 2015 Aug 7.


What adolescents say when they think about or attempt suicide influences the medical care they receive. Mental health professionals use teenagers' words, actions, and gestures to gain insight into their emotional state and to prescribe what they believe to be optimal care. This prescription is often inconsistent among caregivers, however, and leads to varying outcomes. This variation could be reduced by applying machine learning as an aid in clinical decision support. We designed a prospective clinical trial to test the hypothesis that machine learning methods can discriminate between the conversation of suicidal and nonsuicidal individuals. Using semisupervised machine learning methods, the conversations of 30 suicidal adolescents and 30 matched controls were recorded and analyzed. The results show that the machines accurately distinguished between suicidal and nonsuicidal teenagers.

Publication types

  • Controlled Clinical Trial

MeSH terms

  • Adolescent
  • Decision Support Techniques
  • Emergency Service, Hospital*
  • Female
  • Humans
  • Machine Learning
  • Male
  • Natural Language Processing*
  • Prospective Studies
  • Risk Assessment*
  • Suicidal Ideation*
  • Suicide, Attempted / prevention & control
  • Suicide, Attempted / psychology*
  • Verbal Behavior*