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Mental Disorders, Comorbidity, and Pre-enlistment Suicidal Behavior Among New Soldiers in the U.S. Army: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

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Title: Mental Disorders, Comorbidity, and Pre-enlistment Suicidal Behavior Among New Soldiers in the U.S. Army: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).
Authors: Nock, Matthew K.1, Ursano, Robert J.2, Heeringa, Steven G.3, Stein, Murray B.4, Jain, Sonia5, Raman, Rema6, Sun, Xiaoying5, Chiu, Wai Tat7, Colpe, Lisa J.8, Fullerton, Carol S.2, Gilman, Stephen E.9, Hwang, Irving7, Naifeh, James A.2, Rosellini, Anthony J.7, Sampson, Nancy A.7, Schoenbaum, Michael8, Zaslavsky, Alan M.7, Kessler, Ronald C.7, Army STARRS Collaborators (CORPORATE AUTHOR)
Source: Suicide & Life-Threatening Behavior. Oct2015, Vol. 45 Issue 5, p588-599. 12p. 3 Charts.
Subject Terms: *Psychological resilience, *Data analysis, Mental illness, Comorbidity, Suicidal behavior in military personnel
Abstract: We examined the associations between mental disorders and suicidal behavior (ideation, plans, and attempts) among new soldiers using data from the New Soldier Study (NSS) component of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS; N = 38,507). Most new soldiers with a pre-enlistment history of suicide attempt reported a prior mental disorder (59.0%). Each disorder examined was associated with increased odds of suicidal behavior (ORs = 2.6-8.6). Only PTSD and disorders characterized by irritability and impulsive/aggressive behavior (i.e., bipolar disorder, conduct disorder, oppositional defiant disorder, and attention-deficit/hyperactivity disorder) predicted unplanned attempts among ideators. Mental disorders are important predictors of pre-enlistment suicidal behavior among new soldiers and should figure prominently in suicide screening and prevention efforts. [ABSTRACT FROM AUTHOR]
Copyright of Suicide & Life-Threatening Behavior is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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PubType: Academic Journal
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  Data: Mental Disorders, Comorbidity, and Pre-enlistment Suicidal Behavior Among New Soldiers in the U.S. Army: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).
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  Data: <searchLink fieldCode="JN" term="%22Suicide+%26+Life-Threatening+Behavior%22">Suicide & Life-Threatening Behavior</searchLink>. Oct2015, Vol. 45 Issue 5, p588-599. 12p. 3 Charts.
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  Data: We examined the associations between mental disorders and suicidal behavior (ideation, plans, and attempts) among new soldiers using data from the New Soldier Study (NSS) component of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS; N = 38,507). Most new soldiers with a pre-enlistment history of suicide attempt reported a prior mental disorder (59.0%). Each disorder examined was associated with increased odds of suicidal behavior (ORs = 2.6-8.6). Only PTSD and disorders characterized by irritability and impulsive/aggressive behavior (i.e., bipolar disorder, conduct disorder, oppositional defiant disorder, and attention-deficit/hyperactivity disorder) predicted unplanned attempts among ideators. Mental disorders are important predictors of pre-enlistment suicidal behavior among new soldiers and should figure prominently in suicide screening and prevention efforts. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Suicide & Life-Threatening Behavior is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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