Dataset Information

Resilience in Army STARRS: Evaluating psychometrics of a multi-dimensional resilience measure.

ABSTRACT: As policymakers and the U.S. military continue to place an emphasis on the resilience of servicemembers, it is critical to utilize psychometrically sound and valid scales to measure resilience. Using two independent samples of Army soldiers-in-training, this study explored the measurement of resilience in the Army Study to Assess Risk and Resilience among Servicemembers (Army STARRS) New Soldier Study Component (NSS). Exploratory factor analysis (EFA) was used to identify the factor structure of a measure of resilience within the Army STARRS NSS. Confirmatory factor analysis (CFA) was then used to confirm the factor structure, then internal reliability was assessed. Convergent validity of the identified resilience factors was examined using two-tailed bivariate correlations. The EFA identified a three-factor structure of a measure of resilience. The CFA confirm the first-order three-factor structure of stress tolerance, positive orientation, and social resources. Each factor was uniquely distinct from measures of the likelihood of generalized anxiety disorder and major depressive disorder, lifetime stressful events, and social network. Findings highlights the utility of a three-factor aggregate measure of resilience in the Army STARRS NSS and provide practitioners with a more nuanced picture of the role of resilience among soldiers-in-training.

SUBMITTER: Reed-Fitzke K

PROVIDER: S-EPMC10617280 | biostudies-literature | 2023 Nov-Dec

REPOSITORIES: biostudies-literature

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Resilience in Army STARRS: Evaluating psychometrics of a multi-dimensional resilience measure.

Reed-Fitzke Kayla K Ferraro Anthony J AJ Duncan James M JM Wojciak Armeda S AS Hamilton Alexus A Pippert Hilary D HD

Military psychology : the official journal of the Division of Military Psychology, American Psychological Association 20221021 6

As policymakers and the U.S. military continue to place an emphasis on the resilience of servicemembers, it is critical to utilize psychometrically sound and valid scales to measure resilience. Using two independent samples of Army soldiers-in-training, this study explored the measurement of resilience in the Army Study to Assess Risk and Resilience among Servicemembers (Army STARRS) New Soldier Study Component (NSS). Exploratory factor analysis (EFA) was used to identify the factor structure of ...[more]

PMID: 37903165

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Project description:ImportanceThe Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) is a multicomponent study designed to generate actionable recommendations to reduce Army suicides and increase knowledge of risk and resilience factors for suicidality.ObjectivesTo present data on prevalence, trends, and basic sociodemographic and Army experience correlates of suicides and accident deaths among active duty Regular Army soldiers between January 1, 2004, and December 31, 2009, and thereby establish a foundation for future Army STARRS investigations.Design, setting, and participantsAnalysis of trends and predictors of suicide and accident deaths using Army and Department of Defense administrative data systems. Participants were all members of the US Regular Army serving at any time between 2004 and 2009.Main outcomes and measuresDeath by suicide or accident during active Army service.ResultsThe suicide rate rose between 2004 and 2009 among never deployed and currently and previously deployed Regular Army soldiers. The accident death rate fell sharply among currently deployed soldiers, remained constant among the previously deployed, and trended upward among the never deployed. Increased suicide risk was associated with being a man (or a woman during deployment), white race/ethnicity, junior enlisted rank, recent demotion, and current or previous deployment. Sociodemographic and Army experience predictors were generally similar for suicides and accident deaths. Time trends in these predictors and in the Army's increased use of accession waivers (which relaxed some qualifications for new soldiers) do not explain the rise in Army suicides.Conclusions and relevancePredictors of Army suicides were largely similar to those reported elsewhere for civilians, although some predictors distinct to Army service emerged that deserve more in-depth analysis. The existence of a time trend in suicide risk among never-deployed soldiers argues indirectly against the view that exposure to combat-related trauma is the exclusive cause of the increase in Army suicides.

Project description:ImportanceThe US Army experienced a sharp increase in soldier suicides beginning in 2004. Administrative data reveal that among those at highest risk are soldiers in the 12 months after inpatient treatment of a psychiatric disorder.ObjectiveTo develop an actuarial risk algorithm predicting suicide in the 12 months after US Army soldier inpatient treatment of a psychiatric disorder to target expanded posthospitalization care.Design, setting, and participantsThere were 53,769 hospitalizations of active duty soldiers from January 1, 2004, through December 31, 2009, with International Classification of Diseases, Ninth Revision, Clinical Modification psychiatric admission diagnoses. Administrative data available before hospital discharge abstracted from a wide range of data systems (sociodemographic, US Army career, criminal justice, and medical or pharmacy) were used to predict suicides in the subsequent 12 months using machine learning methods (regression trees and penalized regressions) designed to evaluate cross-validated linear, nonlinear, and interactive predictive associations.Main outcomes and measuresSuicides of soldiers hospitalized with psychiatric disorders in the 12 months after hospital discharge.ResultsSixty-eight soldiers died by suicide within 12 months of hospital discharge (12.0% of all US Army suicides), equivalent to 263.9 suicides per 100,000 person-years compared with 18.5 suicides per 100,000 person-years in the total US Army. The strongest predictors included sociodemographics (male sex [odds ratio (OR), 7.9; 95% CI, 1.9-32.6] and late age of enlistment [OR, 1.9; 95% CI, 1.0-3.5]), criminal offenses (verbal violence [OR, 2.2; 95% CI, 1.2-4.0] and weapons possession [OR, 5.6; 95% CI, 1.7-18.3]), prior suicidality [OR, 2.9; 95% CI, 1.7-4.9], aspects of prior psychiatric inpatient and outpatient treatment (eg, number of antidepressant prescriptions filled in the past 12 months [OR, 1.3; 95% CI, 1.1-1.7]), and disorders diagnosed during the focal hospitalizations (eg, nonaffective psychosis [OR, 2.9; 95% CI, 1.2-7.0]). A total of 52.9% of posthospitalization suicides occurred after the 5% of hospitalizations with highest predicted suicide risk (3824.1 suicides per 100,000 person-years). These highest-risk hospitalizations also accounted for significantly elevated proportions of several other adverse posthospitalization outcomes (unintentional injury deaths, suicide attempts, and subsequent hospitalizations).Conclusions and relevanceThe high concentration of risk of suicide and other adverse outcomes might justify targeting expanded posthospitalization interventions to soldiers classified as having highest posthospitalization suicide risk, although final determination requires careful consideration of intervention costs, comparative effectiveness, and possible adverse effects.

Dataset Information

Resilience in Army STARRS: Evaluating psychometrics of a multi-dimensional resilience measure.

Publications

Resilience in Army STARRS: Evaluating psychometrics of a multi-dimensional resilience measure.

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