Dataset Information

Sex Differences in Suicide-Related Symptoms in a Large Military Sample.

ABSTRACT: Little research has focused on suicide-related symptoms in female servicemembers, despite high rates of suicidal behaviors. This study examined sex differences in suicide-related risk factors in 3,374 U.S. Army Recruiters (91.9% male). Female servicemembers had a greater number of past major depressive and suicidal ideation episodes than males; there were no differences in suicide attempt histories or mental health visits. Females reported significantly fewer symptoms of current suicidal ideation, perceived burdensomeness, and acquired capability. No significant sex differences emerged for thwarted belongingness, insomnia, or agitation. Our findings provide evidence for sex differences in rates of suicide-related symptoms among military personnel.

SUBMITTER: Rogers ML

PROVIDER: S-EPMC5607862 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Sex Differences in Suicide-Related Symptoms in a Large Military Sample.

Rogers Megan L ML Ringer Fallon B FB Michaels Matthew S MS Chiurliza Bruno B Hagan Christopher R CR Chu Carol C Schneider Matthew E ME Lim Ingrid C IC Joiner Thomas E TE

Military behavioral health 20161025 1

Little research has focused on suicide-related symptoms in female servicemembers, despite high rates of suicidal behaviors. This study examined sex differences in suicide-related risk factors in 3,374 U.S. Army Recruiters (91.9% male). Female servicemembers had a greater number of past major depressive and suicidal ideation episodes than males; there were no differences in suicide attempt histories or mental health visits. Females reported significantly fewer symptoms of current suicidal ideatio ...[more]

PMID: 28944102

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Project description:BackgroundUS military engagements have consistently raised concern over the array of health outcomes experienced by service members postdeployment. Exploratory factor analysis has been used in studies of 1991 Gulf War-related illnesses, and may increase understanding of symptoms and health outcomes associated with current military conflicts in Iraq and Afghanistan. The objective of this study was to use exploratory factor analysis to describe the correlations among numerous physical and psychological symptoms in terms of a smaller number of unobserved variables or factors.MethodsThe Millennium Cohort Study collects extensive self-reported health data from a large, population-based military cohort, providing a unique opportunity to investigate the interrelationships of numerous physical and psychological symptoms among US military personnel. This study used data from the Millennium Cohort Study, a large, population-based military cohort. Exploratory factor analysis was used to examine the covariance structure of symptoms reported by approximately 50,000 cohort members during 2004-2006. Analyses incorporated 89 symptoms, including responses to several validated instruments embedded in the questionnaire. Techniques accommodated the categorical and sometimes incomplete nature of the survey data.ResultsA 14-factor model accounted for 60 percent of the total variance in symptoms data and included factors related to several physical, psychological, and behavioral constructs. A notable finding was that many factors appeared to load in accordance with symptom co-location within the survey instrument, highlighting the difficulty in disassociating the effects of question content, location, and response format on factor structure.ConclusionsThis study demonstrates the potential strengths and weaknesses of exploratory factor analysis to heighten understanding of the complex associations among symptoms. Further research is needed to investigate the relationship between factor analytic results and survey structure, as well as to assess the relationship between factor scores and key exposure variables.

Dataset Information

Sex Differences in Suicide-Related Symptoms in a Large Military Sample.

Publications

Sex Differences in Suicide-Related Symptoms in a Large Military Sample.

Similar Datasets

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