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Predicting suicide attempts among U.S. Army soldiers after leaving active duty using information available before leaving active duty: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS)

Molecular Psychiatry volume 27, pages 1631–1639 (2022)Cite this article

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Abstract

Suicide risk is elevated among military service members who recently transitioned to civilian life. Identifying high-risk service members before this transition could facilitate provision of targeted preventive interventions. We investigated the feasibility of doing this by attempting to develop a prediction model for self-reported suicide attempts (SAs) after leaving or being released from active duty in the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS). This study included two self-report panel surveys (LS1: 2016–2018, LS2: 2018–2019) administered to respondents who previously participated while on active duty in one of three Army STARRS 2011–2014 baseline self-report surveys. We focus on respondents who left active duty >12 months before their LS survey (n = 8899). An ensemble machine learning model using predictors available prior to leaving active duty was developed in a 70% training sample and validated in a 30% test sample. The 12-month self-reported SA prevalence (SE) was 1.0% (0.1). Test sample AUC (SE) was 0.74 (0.06). The 15% of respondents with highest predicted risk included nearly two-thirds of 12-month SAs and over 80% of medically serious 12-month SAs. These results show that it is possible to identify soldiers at high post-transition self-report SA risk before the transition. Future model development is needed to examine prediction of SAs assessed by administrative data and using surveys administered closer to the time of leaving active duty.

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Fig. 1
Fig. 2: Receiver operating characteristic curves in the test sample and subsamples (n = 2671).
Fig. 3: Predictor importance based on kernel SHAP values in the test sample (n = 2671)1.

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Acknowledgements

IHS was supported in part by a grant from the National Institute of Mental Health (T32MH019836). Army STARRS was sponsored by the Department of the Army and funded under cooperative agreement number U01MH087981 with the U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Mental Health (NIH/NIMH). Subsequently, STARRS-LS was sponsored and funded by the Department of Defense (USUHS grant numbers HU00011520004 and HU0001202003). The grants were administered by the Henry M. Jackson Foundation for the Advancement of Military Medicine Inc. (HJF). The contents are solely the responsibility of the authors and do not necessarily represent the views of the Department of Health and Human Services, NIMH, the Department of the Army, Department of Defense or HJF. The Army STARRS Team consists of Co-Principal Investigators: RJU, MD (Uniformed Services University) and MBS, MD, MPH (University of California San Diego and VA San Diego Healthcare System). ite Principal Investigators: James Wagner, PhD (University of Michigan) and RCK, PhD (Harvard Medical School). Army scientific consultant/liaison: Kenneth Cox, MD, MPH (Office of the Assistant Secretary of the Army (Manpower and Reserve Affairs)). Other team members: Pablo A. Aliaga, MA (Uniformed Services University); David M. Benedek, MD (Uniformed Services University); Laura Campbell-Sills, PhD (University of California San Diego); Carol S. Fullerton, PhD (Uniformed Services University); Nancy Gebler, MA (University of Michigan); Meredith House, BA (University of Michigan); Paul E. Hurwitz, MPH (Uniformed Services University); Sonia Jain, PhD (University of California San Diego); Tzu-Cheg Kao, PhD (Uniformed Services University); Lisa Lewandowski-Romps, PhD (University of Michigan); AL, PhD (University of Washington and Fred Hutchinson Cancer Research Center); Holly Herberman Mash, PhD (Uniformed Services University); James A. Naifeh, PhD (Uniformed Services University); Matthew K. Nock, PhD (Harvard University); Victor Puac-Polanco, MD, DrPH (Harvard Medical School); NAS, BA (Harvard Medical School); and Alan M. Zaslavsky, PhD (Harvard Medical School). As a cooperative agreement, scientists employed by the National Institute of Mental Health and U.S. Army liaisons and consultants collaborated to develop the study protocol and data collection instruments, supervise data collection, interpret results, and prepare reports. Although a draft of the manuscript was submitted to the U.S. Army and National Institute of Mental Health for review and comment before submission for publication, this was done with the understanding that comments would be no more than advisory.

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Authors and Affiliations

  1. National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA

    Ian H. Stanley, Brian P. Marx & Dawne Vogt

  2. Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA

    Ian H. Stanley, Brian P. Marx & Dawne Vogt

  3. Minneapolis VA Health Care System, Minneapolis, MN, USA

    Carol Chu

  4. Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, USA

    Carol Chu

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

    Sarah M. Gildea, Irving H. Hwang, Andrew J. King, Maria V. Petukhova, Nancy A. Sampson & Ronald C. Kessler

  6. Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA

    Chris J. Kennedy

  7. Department of Statistics, University of Washington, Seattle, WA, USA

    Alex Luedtke

  8. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    Alex Luedtke

  9. VA Health Services Research and Development Service, Washington, DC, USA

    Robert O’Brien

  10. Department of Psychiatry, University of California San Diego, La Jolla, CA, USA

    Murray B. Stein

  11. School of Public Health, University of California San Diego, La Jolla, CA, USA

    Murray B. Stein

  12. VA San Diego Healthcare System, La Jolla, CA, USA

    Murray B. Stein

  13. Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD, USA

    Robert J. Ursano

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Contributions

RCK, MBS, and RJU developed the concept and design of the study. CJK, AJK, AL, MVP, NAS, MBS, RJU, and RCK analyzed the data. IHH, AJK, and MVP conducted statistical analysis. IHS and RCK wrote the paper, and IHS, CC, SMG, IHH, AJK, CJK, AL, BPM, RO, MVP, NAS, DV, MBS, RJU, and RCK provided critical input towards the manuscript draft. MBS, RJU, and RCK acquired the funding.

Corresponding author

Correspondence to Ronald C. Kessler.

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Competing interests

In the past 3 years, RCK was a consultant for Datastat, Inc., Holmusk, RallyPoint Networks, Inc., and Sage Therapeutics. He has stock options in Mirah, PYM, and Roga Sciences. In the past 3 years MBS received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, atai Life Sciences, Boehringer Ingelheim, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, Engrail Therapeutics, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech. MBS has stock options in Oxeia Biopharmaceuticals and EpiVario. He is paid for his editorial work on Depression and Anxiety (Editor-in-Chief), Biological Psychiatry (Deputy Editor), and UpToDate (Co-Editor-in-Chief for Psychiatry). The other authors declare that they have no conflict of interest.

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Stanley, I.H., Chu, C., Gildea, S.M. et al. Predicting suicide attempts among U.S. Army soldiers after leaving active duty using information available before leaving active duty: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS). Mol Psychiatry 27, 1631–1639 (2022). https://doi.org/10.1038/s41380-021-01423-4

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