Themes and Findings of Recent Research Using Army STARRS Data
Journal Title: Biomedical Journal of Scientific & Technical Research (BJSTR) - Year 2017, Vol 1, Issue 2
Abstract
United States military service members and veterans are a group at high risk for suicide. The idea that service members survive the battlefield to return home and commit suicide stings of depressive irony but studies show that the majority of service members and veterans have been exposed to, or affected by, suicide and that the suicide rate among U.S. veterans is increasing, possibly due to numerous deployments and the high tempo operations of modern warfare. Amongst the most notable efforts to study suicide amongst service members in recent years has been the Study. To assess risk and resilience (STARRS) and the study to assess risk and resilience longitudinal study (STARRS-LS). A collaborative effort between the Department of Defense and several universities, STARRS and STARRS-LS constitutes one of the largest studies to date regarding suicide amongst service members. Additionally, the data collected for STARRS has facilitated a large amount of research since its conclusion in 2015. Most of this research has sought to characterize those soldiers most at risk for suicide or to create novel methods to predict suicide amongst soldiers. Our review sought to identify, summarize, and discuss themes amongst the most recent published research that utilized STARRS data to examine suicide. Accordingly, this study aimed to use a validated FE models of thoracolumbar junctional T11- T12 and T12-L1 functional spinal units (FSUs) validated under physiological loading modes: flexion, extension, lateral bending and axial rotation, and to compare the kinematics in terms of the locations and loci of instantaneous axes of rotation (IARs) . The prevalence of suicide amongst military members has been well above the national average for several decades [1]. Concurrent to the wars in Afghanistan and Iraq, rates of suicide and suicide attempts amongst service members increased significantly [2]. Mirroring the increase in suicides, suicide attempts have also risen sharply during this time. While rates of suicide and suicide attempts amongst members of all services increased during this time period [1], the Army experienced the largest increases [1]. In 2007, 2008, and 2009 the Army experienced record high numbers of suicides amongst its members (STARRS-LS, 2017). In response the Army, beginning in 2009, initiated a massive effort to study suicide amongst its members titled the “Study To Assess Risk & Resilience in Service Members” (STARRS). To conduct STARRS, the Army assembled a multidisciplinary group of researchers to create and implement a comprehensive study to assist the Army in reducing suicides amongst its members. Initial data collected for STARRS was used to complete eight different studies (STARRS-LS, 2017). Examples of the types of data collected in these studies include administrative data, neurocognitive tests, blood samples, and questionnaires among others (STARRS-LS, 2017). The scope of STARRS was massive; administrative records representing 1.6 million active duty soldiers were compiled and examined in addition to data from over 100,000 active duty soldiers using questionnaires and neuro-cognitive tests (STARRS-LS, 2017). While STARRS concluded its initial collection of data in 2015, The Study To Assess Risk And Resilience Longitudinal Study (STARRS-LS) is ongoing until 2020 and aims to collect data from 72,000 soldiers who participated in the initial STARRS as they continue their careers in the Army or transition back into civilian life (STARRS-LS, 2017). The data gathered from both STARRS and STARRS-LS has and continues to be used by researchers seeking to understand suicide better. Since 2012, data from the eight original studies collected for STARRS has been utilized to create over 50 new studies (STARRS-LS, 2017). Research utilizing STARRS data has encompassed a broad variety of research questions. Much of the research has centered on identifying demographic traits and experiences of individuals in the Army who have committed suicide [3-5]. Additionally, STARRS data has been used in research aimed at creating algorithms to predict suicidal behavior amongst soldiers [6-8]. The topic was chosen from Healthy People 2020 list of leading health indicators. A broad, scoping search was undertaken to identify key terms, assess the depth and availability of literature, and establish a structure for the review. The amount of research regarding suicide and the military is vast and required that the search strategy be refined in order for this literature review to be manageable. STARRS and STARRS-LS were utilized to ensure that that information reviewed was recent and relevant to military suicides. While this still produce a very large amount of studies it helped to refine the search. Further inclusion criteria was developed and applied, studies must have been published within the past five years and must have been cited by another source at least one time. This helped to ensure both recent and quality research was being reviewed. Fifteen studies were found that met the stated inclusion criteria and were chosen to be reviewed; this was agreed to be enough data to ensure a thorough review of literature from different viewpoints. All studies were read and keywords, demographic information, trends, treatment options, and prevention strategies were extracted. “Keywords” were defined as words or phrases that appeared in multiple papers and had significance to the study or its results. Similarities and differences between studies and outcomes were identified. Thirteen, of these studies utilized quantitative methods of research which allowed for the study of large numbers of participants and the ease of comparing numeric data outcomes. The remaining two studies focused on using qualitative methods which allowed for a deeper look at cause and effect as well as the examination of the effect of multiple variables.
Authors and Affiliations
Joseph Sayre, Grant Voyles
Keywords
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- EP ID EP567119
- DOI 10.26717/BJSTR.2017.01.000189
- Views 165
- Downloads 0
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