SAFEGUARD: Transforming Military Suicide Prevention Through Predictive Analytics and Targeted Interventions.

Abstract

PURPOSE OF REVIEW: Machine learning predictive modeling can support scalable prevention of suicide-related behavior (SRB). SAFEGUARD is a three-pronged universal, indicated, and clinical SRB-prevention intervention system focused on key military career touchpoints. RECENT FINDINGS: The targeted SAFEGUARD interventions are designed to improve on the mixed results of universal interventions. Level Up uses digital tools, personalized messaging, and remote booster sessions to deliver customized universal military-focused cognitive behavioral therapy skills training designed to reduce SRBs during first duty assignments. Operation Life Force delivers remote group dialectical behavior therapy skills training with a mental toughness focus to soldiers identified during annual physicals as high-risk for SRBs. Pathfinding delivers remote wrap-around case management after psychiatric inpatient discharge to soldiers identified as high-risk for SRBs. SAFEGUARD is a data-driven system for SRB prevention that delivers targeted best-practice interventions at critical points to optimize impact and efficiently use mental health resources across the military.