Literature DB >> 30598236

Predicting suicide attempts among soldiers who deny suicidal ideation in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

Samantha L Bernecker1, Kelly L Zuromski1, Peter M Gutierrez2, Thomas E Joiner3, Andrew J King4, Howard Liu4, Matthew K Nock5, Nancy A Sampson4, Alan M Zaslavsky4, Murray B Stein6, Robert J Ursano7, Ronald C Kessler8.   

Abstract

Most nonfatal suicide attempts and suicide deaths occur among patients who deny suicidal ideation (SI) during suicide risk screenings. Little is known about risk factors for suicidal behaviors among such patients. We investigated this in a representative sample of U.S. Army soldiers who denied lifetime SI in a survey and were then followed through administrative records for up to 45 months to learn of administratively-recorded suicide attempts (SA). A novel two-stage risk assessment approach was used that combined first-stage prediction from administrative records to find the subsample of SI deniers with highest subsequent SA risk and then used survey reports to estimate a second-stage model identifying the subset of individuals in the high-risk subsample at highest SA risk. 70% of survey respondents denied lifetime SI. Administrative data identified 30% of this 70% who accounted for 81.2% of subsequent administratively-recorded SAs. A relatively small number of self-report survey variables were then used to create a prediction model that identified 10% of the first-stage high-risk sample (i.e., 3% of all soldiers) at highest SA risk (accounting for 45% of SAs in the total sample). We close by discussing potential applications of this approach for identifying future SI deniers at highest SA risk.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Army; Machine learning; Military; Risk assessment; Suicidal ideation; Suicide attempt

Year:  2018        PMID: 30598236     DOI: 10.1016/j.brat.2018.11.018

Source DB:  PubMed          Journal:  Behav Res Ther        ISSN: 0005-7967


  9 in total

Review 1.  Development of Autonomic Nervous System Assays as Point-of-Care Tests to Supplement Clinical Judgment in Risk Assessment for Suicidal Behavior: A Review.

Authors:  William V McCall; Peter B Rosenquist; Brian J Miller
Journal:  Curr Psychiatry Rep       Date:  2022-01-25       Impact factor: 5.285

2.  Machine Learning Methods to Evaluate the Depression Status of Chinese Recruits: A Diagnostic Study.

Authors:  Mengxue Zhao; Zhengzhi Feng
Journal:  Neuropsychiatr Dis Treat       Date:  2020-11-12       Impact factor: 2.570

Review 3.  Suicide prediction models: a critical review of recent research with recommendations for the way forward.

Authors:  Ronald C Kessler; Robert M Bossarte; Alex Luedtke; Alan M Zaslavsky; Jose R Zubizarreta
Journal:  Mol Psychiatry       Date:  2019-09-30       Impact factor: 15.992

4.  Association between neurocognitive functioning and suicide attempts in U.S. Army Soldiers.

Authors:  Samantha N Hoffman; Charles T Taylor; Laura Campbell-Sills; Michael L Thomas; Xiaoying Sun; James A Naifeh; Ronald C Kessler; Robert J Ursano; Ruben C Gur; Sonia Jain; Murray B Stein
Journal:  J Psychiatr Res       Date:  2020-11-07       Impact factor: 4.791

5.  Assessment of a Risk Index for Suicide Attempts Among US Army Soldiers With Suicide Ideation: Analysis of Data From the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

Authors:  Kelly L Zuromski; Samantha L Bernecker; Peter M Gutierrez; Thomas E Joiner; Andrew J King; Howard Liu; James A Naifeh; Matthew K Nock; Nancy A Sampson; Alan M Zaslavsky; Murray B Stein; Robert J Ursano; Ronald C Kessler
Journal:  JAMA Netw Open       Date:  2019-03-01

6.  The Role of Past Suicidal Behavior on Current Suicidality: A Retrospective Study in the Israeli Military.

Authors:  Leah Shelef; Jessica M Rabbany; Peter M Gutierrez; Ron Kedem; Ariel Ben Yehuda; J John Mann; Assaf Yacobi
Journal:  Int J Environ Res Public Health       Date:  2021-01-14       Impact factor: 3.390

Review 7.  Artificial intelligence and suicide prevention: a systematic review.

Authors:  Alban Lejeune; Aziliz Le Glaz; Pierre-Antoine Perron; Johan Sebti; Enrique Baca-Garcia; Michel Walter; Christophe Lemey; Sofian Berrouiguet
Journal:  Eur Psychiatry       Date:  2022-02-15       Impact factor: 5.361

8.  Partnered implementation of the veteran sponsorship initiative: protocol for a randomized hybrid type 2 effectiveness-implementation trial.

Authors:  Joseph C Geraci; Erin P Finley; Emily R Edwards; Sheila Frankfurt; A Solomon Kurz; Nipa Kamdar; Megan E Vanneman; Leonard M Lopoo; Hannah Patnaik; Jean Yoon; Nicholas Armstrong; Ashley L Greene; Gilly Cantor; Joseph Wrobleski; Erin Young; Matthew Goldsmith; Richard W Seim; Marianne Goodman
Journal:  Implement Sci       Date:  2022-07-08       Impact factor: 7.960

9.  Development and validation study of the suicide screening questionnaire-observer rating (SSQ-OR).

Authors:  Young-Hwan Choi; Vidal Yook; Kyojin Yang; Yaehee Cho; Deok Hee Lee; Hwa Jung Lee; Dong Hun Lee; Hong Jin Jeon
Journal:  Front Psychiatry       Date:  2022-08-12       Impact factor: 5.435

  9 in total

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