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Using self-report surveys at the beginning of service to develop multi-outcome risk models for new soldiers in the U.S. Army

Published online by Cambridge University Press:  04 April 2017

A. J. Rosellini ,
M. B. Stein ,
D. M. Benedek ,
P. D. Bliese ,
W. T. Chiu ,
I. Hwang ,
J. Monahan ,
M. K. Nock ,
M. V. Petukhova  and
N. A. Sampson
...Show all authors
A. J. Rosellini
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA
M. B. Stein
Affiliation:
Departments of Psychiatry and Family Medicine & Public Health, University of California San Diego, La Jolla, California, USA VA San Diego Healthcare System, San Diego, CA, USA
D. M. Benedek
Affiliation:
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University School of Medicine, Bethesda, MD, USA
P. D. Bliese
Affiliation:
Darla Moore School of Business, University of South Carolina, Columbia, South Carolina, USA
W. T. Chiu
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA
I. Hwang
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA
J. Monahan
Affiliation:
School of Law, University of Virginia, Charlottesville, VA, USA
M. K. Nock
Affiliation:
Department of Psychology, Harvard University, Cambridge, Massachusetts, USA
M. V. Petukhova
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA
N. A. Sampson
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA
A. E. Street
Affiliation:
National Center for PTSD, VA Boston Healthcare System, Boston, Massachusetts, USA Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts, USA
A. M. Zaslavsky
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA
R. J. Ursano
Affiliation:
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University School of Medicine, Bethesda, MD, USA
R.C. Kessler*
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA
*
*Address for correspondence: R. C. Kessler, Ph.D., Department of Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA, USA. (Email: Kessler@hcp.med.harvard.edu)
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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.

Keywords

Armydisciplinary problemsmental healthmilitarypredictive modelingrisk assessmentviolence
Type
Original Articles
Information
Psychological Medicine , Volume 47 , Issue 13 , October 2017 , pp. 2275 - 2287
Copyright
Copyright © Cambridge University Press 2017 

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