Evidence map›Paper›PMID 39475323›Full record

ArticleInternational journal of methods in psychiatric research2024

A prediction model for differential resilience to the effects of combat-related stressors in US army soldiers.

Ronald C Kessler, Robert M Bossarte, Irving Hwang, Alex Luedtke, James A Naifeh, Matthew K Nock, Maria Petukhova, Ekaterina Sadikova, Nancy A Sampson, Erik Sverdrup and 5 more

Abstract read
In one paragraph

Article in International journal of methods in psychiatric research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Post-traumatic stress disorder.Nature reviews. Disease primers · 2026
    Review
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  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Ronald C KesslerDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0003-4831-2305
Robert M BossarteDepartment of Psychiatry and Behavioral Neuroscience, Morsani School of Medicine Tampa, University of South Florida, Tampa, Florida, USA.
Irving HwangDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.
Alex LuedtkeDepartment of Statistics, University of Washington, Seattle, Washington, USA.
James A NaifehDepartment of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University School of Medicine, Bethesda, Maryland, USA.ORCID 0000-0001-7248-3054
Matthew K NockDepartment of Psychology, Harvard University, Cambridge, Massachusetts, USA.
Maria PetukhovaDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.
Ekaterina SadikovaDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.
Nancy A SampsonDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.
Erik SverdrupDepartment of Econometrics & Business Statistics, Monash University, Melbourne, Victoria, Australia.
Jose R ZubizarretaDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.
Stefan WagerGraduate School of Business, Stanford University, Stanford, California, USA.
James WagnerSurvey Research Center, Institute for Social Research, University of Michigan-Ann Arbor, Ann Arbor, Michigan, USA.
Murray B SteinDepartments of Psychiatry and Family Medicine and Public Health, University of California San Diego, La Jolla, California, USA.
Robert J UrsanoDepartment of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University School of Medicine, Bethesda, Maryland, USA.

Funding

Modifiable Risk and Protective Factors for Suicidal Behaviors in the US ArmyU01MH087981 · NIMH · HENRY M. JACKSON FDN FOR THE ADV MIL/MED · PI STEIN, MURRAY B., URSANO, ROBERT J. · 2009 to 2013
$65.0M
NIMH NIH HHS U01 MH087981NIMH NIH HHS U01MH087981U.S. Army U01MH087981U.S. Department of Defense HU0001-15-2-0004
6 · The paper itself

Abstract

objectivesTo develop a composite score for differential resilience to effects of combat-related stressors (CRS) on persistent DSM-IV post-traumatic stress disorder (PTSD) among US Army combat arms soldiers using survey data collected before deployment.

methodsA sample of n = 2542 US Army combat arms soldiers completed a survey shortly before deployment to Afghanistan and then again two to three and 8-9 months after redeployment. Retrospective self-reports were obtained about CRS. Precision treatment methods were used to determine whether differential resilience to persistent PTSD in the follow-up surveys could be developed from pre-deployment survey data in a 60% training sample and validated in a 40% test sample.

results40.8% of respondents experienced high CRS and 5.4% developed persistent PTSD. Significant test sample heterogeneity was found in resilience (t = 2.1, p = 0.032), with average treatment effect (ATE) of high CRS in the 20% least resilient soldiers of 17.1% (SE = 5.5%) compared to ATE = 3.8% (SE = 1.2%) in the remaining 80%. The most important predictors involved recent and lifetime pre-deployment distress disorders.

conclusionsA reliable pre-deployment resilience score can be constructed to predict variation in the effects of high CRS on persistent PTSD among combat arms soldiers. Such a score could be used to target preventive interventions to reduce PTSD or other resilience-related outcomes.

Indexed as

Combat DisordersMilitary PersonnelResilience, PsychologicalStress Disorders, Post-TraumaticAdolescentAdultAfghan Campaign 2001-FemaleFollow-Up StudiesHumansMaleRetrospective StudiesStress, PsychologicalUnited StatesYoung Adultmilitary deploymentpost‐traumatic stress disorder (PTSD)precision treatmentresilience

Identifiers

PMID39475323
PMCPMC11523145

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.