Comparing the Army's Suicide Rate to the General U.S. Population: Identifying Suitable Characteristics, Data Sources, and Analytic Approaches

Abstract

Over the past 15 years, the suicide rate among members of the U.S. armed forces has doubled, with the greatest increase observed among soldiers in the Army (Mancha et al., 2014). This increasing rate is paralleled by a smaller increase the general U.S. population (Curtin, Warner, and Hedegaard, 2016), observed across both genders, in virtually every age group, and in nearly every state. An empirical question exists: What is the extent or degree to which the suicide trend in the Army is unique to the Army, relative to what is observed in the general population? The Army has typically attempted to address this question by standardizing the general population to look like the military population on demographic characteristics (e.g., age and gender are used most frequently [Watkins et al., 2018; Reimann and Mazuchowski, 2018] and race/ethnicity as well on occasion) (Ramchand et al., 2011). Standardization aims to make the general population look like the Army population on the characteristics being used in the procedure, thereby allowing for comparisons that are done on populations with the same characteristics and minimizing the ability of the included characteristics to explain the observed rate differences.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2020
Accession Number
AD1095544

Entities

People

  • Andrew R Morral
  • Beth A. Griffin
  • Erin N. Leidy
  • Geoffrey E. Grimm
  • Lisa H. Jaycox
  • Lynsay Ayer
  • Rajeev Ramchand
  • Rosanna Smart
  • Steven Davenport
  • Terry L Schell

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  • RAND Corporation

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  • Engineered Resilient Systems
  • Human Systems

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  • African Americans
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  • Enlisted Personnel
  • Ethnic Groups
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  • Health Services
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  • Medical Personnel
  • Mental Disorders
  • Military Medicine
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  • Psychiatry
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  • Gender and Food Studies
  • Psychological Intervention/Treatment for Stress, Anxiety, PTSD, and Related Emotional and Cognitive Health Symptoms.
  • Systems Analysis and Design