Citation

Rosellini AJ, Stein MB, Benedek DM, Bliese PD, Chiu WT, Hwang I, Monahan J, Nock MK, Petukhova MV, Sampson NA, Street AE, Zaslavsky AM, Ursano RJ, Kessler RC. Psychol. Med. 2017; 47(13): 2275-2287.

Affiliation

Department of Health Care Policy,Harvard Medical School,Boston, Massachusetts,USA.

Copyright

(Copyright © 2017, Cambridge University Press)

DOI

10.1017/S003329171700071X

PMID

28374665

Abstract

BACKGROUND: The U.S. Army uses universal preventives interventions for several negative outcomes (e.g. suicide, violence, sexual assault) with especially high risks in the early years of service. More intensive interventions exist, but would be cost-effective only if targeted at high-risk soldiers. We report results of efforts to develop models for such targeting from self-report surveys administered at the beginning of Army service.

METHODS: 21 832 new soldiers completed a self-administered questionnaire (SAQ) in 2011-2012 and consented to link administrative data to SAQ responses. Penalized regression models were developed for 12 administratively-recorded outcomes occurring by December 2013: suicide attempt, mental hospitalization, positive drug test, traumatic brain injury (TBI), other severe injury, several types of violence perpetration and victimization, demotion, and attrition.

RESULTS: The best-performing models were for TBI (AUC = 0.80), major physical violence perpetration (AUC = 0.78), sexual assault perpetration (AUC = 0.78), and suicide attempt (AUC = 0.74). Although predicted risk scores were significantly correlated across outcomes, prediction was not improved by including risk scores for other outcomes in models. Of particular note: 40.5% of suicide attempts occurred among the 10% of new soldiers with highest predicted risk, 57.2% of male sexual assault perpetrations among the 15% with highest predicted risk, and 35.5% of female sexual assault victimizations among the 10% with highest predicted risk.

CONCLUSIONS: Data collected at the beginning of service in self-report surveys could be used to develop risk models that define small proportions of new soldiers accounting for high proportions of negative outcomes over the first few years of service.

Language: en

Keywords

Army; disciplinary problems; mental health; military; predictive modeling; risk assessment; violence