This research developed and compared firearm-specific and method-agnostic machine-learning models using data from 800,579 Army veterans, revealing that model choice and intervention thresholds impact predictive accuracy and fairness, guiding tailored suicide prevention efforts.
- Claire Houtsma
- Chris J. Kennedy
- Ronald C. Kessler