Improving risk prediction accuracy for new soldiers in the U.S. Army by adding self-report survey data to administrative data

Improving risk prediction accuracy for new soldiers in the U.S. Army by adding self-report survey data to administrative data

Abstract Background High rates of mental disorders, suicidality, and interpersonal violence early in the military career have raised interest in implementing preventive interventions with high-risk new enlistees. The Army Study to Assess Risk and Resilience in Servicemembers (STARRS) developed risk-...

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Bibliographic Details
Main Authors: Samantha L. Bernecker, Anthony J. Rosellini, Matthew K. Nock, Wai Tat Chiu, Peter M. Gutierrez, Irving Hwang, Thomas E. Joiner, James A. Naifeh, Nancy A. Sampson, Alan M. Zaslavsky, Murray B. Stein, Robert J. Ursano, Ronald C. Kessler
Format: Article
Language:English
Published: BMC 2018-04-01
Series:BMC Psychiatry
Subjects:
Army
Military
Predictive modeling
Risk assessment
Violence
Sexual assault
Online Access:http://link.springer.com/article/10.1186/s12888-018-1656-4

Internet

http://link.springer.com/article/10.1186/s12888-018-1656-4

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