A practical risk calculator for suicidal behavior among transitioning U.S. Army soldiers: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS)

Abstract

Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 09, 2023
Source ID
10.1017/s0033291723000491

Entities

People

  • Alex Luedtke
  • Andrew J King
  • Brian P Marx
  • Chris J Kennedy
  • Emily R Edwards
  • Erin P. Finley
  • Ian H Stanley
  • Irving Hwang
  • Jaclyn C. Kearns
  • Joseph C. Geraci
  • Maria V. Petukhova
  • Marianne Goodman
  • Murray B. Stein
  • Nancy A. Sampson
  • Richard W. Seim
  • Robert Ursano
  • Ronald C Kessler
  • Sarah M. Gildea

Organizations

  • National Institute of Mental Health
  • United States Department of Defense

Tags

Readers

  • Computer Science.
  • Military Mobilization and Reserve Forces Studies.
  • Psychological Intervention/Treatment for Stress, Anxiety, PTSD, and Related Emotional and Cognitive Health Symptoms.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy