Open access
RESEARCH ARTICLES
Published Online: 13 January 2023

Recent Stressful Experiences and Suicide Risk: Implications for Suicide Prevention and Intervention in U.S. Army Soldiers

Catherine L. Dempsey, Ph.D., MPH https://orcid.org/0000-0002-5712-6590, David M. Benedek, M.D., Kelly L. Zuromski, Ph.D., Matthew K. Nock, Ph.D., David A. Brent, M.D., Jingning Ao, MPH., Matthew W. Georg, MPH., … Show All … , Katy Haller, MSPH., Pablo A. Aliaga, M.S., Steven G. Heeringa, PhD., Ronald C. Kessler, Ph.D., Murray B. Stein, M.D., MPH., and Robert J. Ursano, M.D.Authors Info & Affiliations
Publication: Psychiatric Research and Clinical Practice
Volume 5, Number 1
https://doi.org/10.1176/appi.prcp.20220027
Track CitationsAdd to favorites
PDF/EPUB

Abstract

Objectives

To identify the extent to which the presence of recent stressful events are risk factors for suicide among active‐duty soldiers as reported by informants.

Methods

Next‐of‐kin (NOK) and supervisors (SUP) of active duty soldiers (n = 135) who died by suicide and two groups of living controls: propensity‐matched (n = 128) and soldiers who reported suicidal ideation in the past year, but did not die (SI) (n = 108) provided data via structured interviews from the Study to Assess Risk and Resilience in Servicemembers (Army STARRS). Multivariate logistic regression analyses were used to create a risk score for suicide.

Results

The odds of suicide increased significantly for soldiers experiencing relationship problems, military punishment, and perceived failure or humiliation in the month prior to death. Suicide risk models with these risk factors predicted suicide death among those who reported SI in the past year (OR = 5.9, [95% CI = 1.5, 24.0] χ2 = 6.24, p = 0.0125, AUC, 0.73 (0.7, 0.8) NOK) and (OR = 8.6, [95% CI = 1.4, 51.5] χ2 = 5.49, p = 0.0191, AUC, 0.78 (0.7, 0.8); SUP) suggesting the combination of these recent stressors may contribute to the transition from ideation to action.

Conclusions

Our findings suggest for the first time recent stressors distinguished suicide ideating controls from suicide decedents in the month prior to death as reported by informants. Implications for preventive intervention efforts for clinicians, supervisors and family members in identifying the transition from ideation to action are discussed.

HIGHLIGHTS

•
The study identified recent stressors that increased the odds of suicide death as reported by informants, and described how these recent stressors contributed to suicide risk, especially the transition from ideation to completed suicide, after controlling for lifetime stressors and history of mental disorders in service members.
•
The identification of relationship problems, military punishment, and perceived failure or humiliation in the month prior to death in service members is an actionable target for suicide prevention and intervention for clinicians, family members, and supervisors.
Suicide is a leading cause of death in the U.S. and represents a serious public health concern particularly among service members and veterans (1). The Department of Defense (DoD) reported the suicide mortality rate for active duty soldiers statistically increased from 20.3 to 28.7 per 100,000 service members in 2015 to 2020, which translates to 580 service members who died by suicide in 2020 (2). Besides death‐in‐combat, suicide death has become the leading cause of mortality in the military, making suicidal behaviors a growing cause of concern to the Department of the Army (3, 4).
Among military service members, specific stressful life events (e.g., legal problems, victimization, major financial crises, betrayal by a loved one, and separation/divorce other breakup) have been associated with suicide attempts, after separation/deactivation from the military (5). The experience of both interpersonal violence and sexual assault or harassment, especially among female soldiers, may have a dose‐response relationship with suicidal ideation and attempts (6, 7). In addition to interpersonal violence, relationship problems, major depression, posttraumatic stress disorder, and substance use disorder predicted suicide attempt in an active duty military population (8). For veterans, adverse socially‐determined lifetime stressful experiences such as homelessness, healthcare access, unemployment, and violence are some of the main risk factors associated with suicide death (9).
The specialized forms of training and the exceptional environments service members operate in expose them to military/deployment‐related stressors that their civilian counterparts are spared and may make them more vulnerable to family/social‐related stressful events. Military/deployment‐related stressful events include combat experience, combat injuries, conformity to rigorous unit requirements, and loss of colleagues during combat. Family/social‐related stressors prevalent among service members include failed romantic relationships, suicide of a close relative or friend, long periods of separation from family, infidelity, and romantic distress (10, 11, 12), Service members may be at greater risk of exposure and/or individuals may be more vulnerable to stressful events during deployment, and it may be useful to better understand the dynamics underlying the effects of adverse events in the 30 days leading up to suicide death, and to treat this period as a window of opportunity for intervention. This study may have important and timely policy implications for suicide prevention in military populations allowing for an opportunity to assess stressors immediately preceding suicide death.
The purpose of the current study is to identify the extent to which the presence of recent stressful events, lifetime traumatic stressors, and history of lifetime mental health disorders by administrative record are risk factors for suicide among active duty U.S. Army Soldiers, as reported by informants. A better understanding of how and to what extent these risk factors are associated with increased risk of suicide death, may assist both supervisors and family members in identifying those most at risk to inform preventive interventions. Further, we will explore other factors that may differentiate those who report suicidal ideation, from those who died by suicide, to identify how one moves from suicidal thoughts to action. We hypothesized that recent stressors such as interpersonal violence, legal problems, and family/social/relationship problems, after controlling for lifetime history of mental health disorders, and lifetime stressors would increase the risk of suicide death, and the combination of these factors may exacerbate symptoms of distress.

METHOD

Data are from a psychological autopsy component of the Army Study to Assess Risk and Resilience among Servicemembers (Army STARRS) (13). Recruitment and data collection procedures were approved by the Humans Subjects Committees of The University of Michigan, Ann Arbor, MI; the Uniformed Services University, Bethesda, MD; and all other collaborating organizations. Due to space constraints, please refer to study procedures published elsewhere (Supplemental S1) (13).

Sample

Cases

The suicide cases were U.S. Army Soldiers (n = 135) who died by suicide while on active duty between August 01, 2011‐November 01, 2013. This sample excluded soldiers in the Army Reserve and National Guard and soldiers who died while deployed, as these soldiers were excluded from the pool of control soldiers by the design of the Army STARRS (14). The research team interviewed a next‐of‐kin (NOK) and/or first‐line Army supervisor (SUP) for n = 135 suicides. The response rates for the NOK and SUP cases were 61.6% and 69.5% respectively.

Controls

The controls were drawn from a large (N = 5428) representative sample of living soldiers who participated in the Army STARRS All Army Study (AAS). Two groups of living controls were selected in two different manners. First, propensity‐score matched (15) (PS) controls (n = 128) were matched to Army suicide decedents on 22 sociodemographic and military characteristics. The second group of controls reported suicidal ideation (SI) in the past year in the AAS survey (n = 118). (16) Neither group of controls differed from eligible AAS respondents who did not participate on: sex, race/ethnicity, marital status, or age of entry into the Army. However, controls were slightly older, had more dependents, were higher rank, and had higher educational attainment; although these effects were small in magnitude (rs = 0.09–0.18). The response rates for the NOK and SUP propensity‐matched (PS) and ideator (SI) controls were 66.7% and 56.7% respectively.

Measures

The psychological autopsy interview included 26 sections assessing a wide range of risk and protective factors for suicide. The development of the psychological autopsy interview is described elsewhere (13). Measures are provided in the supplemental materials (Supplemental S2).

Psychiatric disorders

Classic mental health disorder is defined as a lifetime history of any of the following 22 diagnoses as indicated by administrative ICD‐9 codes: ADHD, adjustment disorder, alcohol, anxiety, bipolar, conduct/ODD, minor depression, MDD, eating disorders, non‐affective psychosis, organic mental disorders, other disorders, other impulse‐control disorders, personality disorders, sex disorders, sleep disorders, somatoform/dissociative disorders, traumatic stress, PTSD, drug‐induced mental illness, drug abuse without dependence, or drug dependence.

Lifetime stressors

The SLE items were adapted from the Life Event Questionnaire (17) and the Department of Defense Health Survey of Health Related Behaviors among Active Duty Military Personnel. (18) Informants reported number of times the suicide decedent experienced 14 lifetime traumatic SLEs, and 15 deployment related SLEs. Informants then asked how many times in the suicide decedent's life an event occurred, and if the event occurred in the past 12 months. Items were dichotomized for subsequent analyses (yes/no).

Recent stressors

To capture whether SLEs occurred in the past week, past month, past year or more than a year, informants were asked whether the suicide decedent experienced 17 stressful experiences in the past week, month, year or more than a year before the decedent's death. Items were dichotomized (yes/no) for absence of presence of a recent SLE.

Statistical Analyses

Sample weights

Post‐stratification weights were developed based on the analysis of the Historical Administrative Data Study (HADS)1 Army sample, using predictors of suicide found in administrative records and known population information gathered from the Army snapshot data set (14, 16, 19). Item‐level missing data were handled in a process described in the Army STARRS study design and methodology publication (14).

Univariable models

Logistic regression models tested the significance of each item comparing suicide deaths (cases) to the controls (PS and SI controls), while adjusting for significant demographics. Coefficients were exponentiated in logistic models to create ORs with 95% CIs and χ2 tests were performed when fitting each of the logistic regression models. To correct for multiple comparisons, we used the false discovery rate, (20) within each sample (NOK and SUP) for PS controls and SI controls comparisons, separately. The false discovery rate was conducted using the p.adjust function in R, version 3.4.2 (21). Models whose calculation involved cells with n < 5 were corrected with Firth's penalized likelihood method to help address small sample size bias. All tests were 2‐sided and considered significant at p ≤ 0.05. All other analyses were conducted using SAS, version 9.4 (22).

Risk scores

To construct risk score regression models for suicide death, we identified lifetime SLEs, recent SLEs, lifetime survey mood disorder or lifetime class mental health disorder statistically significant at p ≤ 0.05 after FDR adjustment in the univariate analyses. The risk score variable was constructed by giving a point for each item the NOK and SUP endorsed in the past month. Standardized Chronbach Coefficient Alphas and Pearson Correlations were obtained for the NOK and SUP risk scores to check for internal consistency. After creating the risk score construct, a logistic regression model was fit using this score construct variable as an independent variable while adjusting for significant demographics. For the logistic regression, we examined this variable both as a continuous variable and as categorical variable (1+ score vs. 0) and constructed models for each. A receiver operating characteristic curve (AUC) and 95% CI was calculated to evaluate model fit.

Multivariable models

To explore predictors of suicide death we examined lifetime and recent SLEs in multivariable models adjusting for significant demographics and history of lifetime classic mental health disorders. A step‐wise model selection approach identified the most parsimonious model. In the NOK and SUP multivariable models, the independent variables included those significant in the univariable analyses after FDR adjustment with a p‐value ≤ 0.05. Interactions were assessed using multivariable models containing each variable of interest and a multiplicative interaction term. Those interactions whose models had sufficient cell sizes for model convergence and a p‐value ≤ 0.05 were considered significant. Population attributable risk (PAR) was calculated using Levin's Formula [% PAR = (Pe × (RR ‐ 1))/(Pe × (RR ‐ 1) + 1) × 100] to estimate the proportion of cases in the population that can be attributed to a specific risk factor. (23) PARP calculations are reported for lifetime SLEs significant after FDR adjustment in the univariable models.2

RESULTS

Comparisons of cases and controls on sociodemographic and Army history variables revealed few differences for the NOK and SUP informant samples. (Supplemental Table S3).

Univariable Models

Psychiatric disorders

NOK reported suicide descedents were five times more likely than PS controls to have a history of lifetime classic mental health disorder from the administrative record NOK (OR = 5.0 [95% CI = 2.3, 10.8] χ2 = 16.83, p < 0.0001) and for similarly for SUP (OR = 5.8 [95% CI = 3.2, 10.5] χ2 = 33.40, p < 0.0001).

Lifetime stressors

NOK reported suicide decedents were four times more likely to have a lifetime history of interpersonal violence (e.g., sexual assault or rape) (OR = 4.2 [95% CI = 1.5, 11.5] χ2 = 7.54, p = 0.0420) compared to PS controls and three times as likely to have experienced the suicide of a close friend or relative (OR = 3.0 [95% CI = 1.5, 6.3] χ2 = 8.87, p = 0.0406), but not SUP. Interestingly, NOK reported the protective effects of experiencing a disaster (OR = 0.2 [95% CI = 0.1, 0.9] χ2 = 4.29, p = 0.1792).

Recent stressors3

NOK reported suicide decedents were more likely to experience the following recent SLEs compared to PS controls: 1) spouse or partner left him/her (OR = 10.4 [95% CI = 3.5, 30.9] χ2 = 18.01, p = 0.0009); 2) serious betrayal by someone else close to him/her (OR = 5.3 [95% CI = 1.5, 18.0] χ2 = 8.25, p = 0.0365); 3) serious argument/break up with a close friend or family member (OR = 5.9 [95% CI = 2.4, 14.5] χ2 = 15.01, p = 0.0027); 4) he/she caused an accident where someone else was hurt or property was damaged (OR = 3.0 [95% CI = 1.2, 7.8] χ2 = 5.33, p = 0.1255); 5) didn't get promoted (OR = 4.3 [95% CI = 1.3, 14.1] χ2 = 7.81, p = 0.0402); 6) received military punishment (e.g. Court Martial, Article 15, Captain's Mast, Office Hours, Letter of Reprimand) (OR = 56.4 [95% CI = 7.2, 439.8] χ2 = 14.84, p = 0.0027); 7) trouble with the police (OR = 3.7 [95% CI = 1.5, 8.9] χ2 = 8.25, p = 0.0162); 8) arrested for an incident not related to driving (OR = 1.8 [95% CI = 0.8, 4.0] χ2 = 8.25, p = 0.0365); 9) some type of perceived failure or humiliation (OR = 24.4 [95% CI = 9.2, 64.5] χ2 = 42.34, p < 0.0001) and 10) any other very stressful event (OR = 4.7 [95% CI = 2.0, 11.1] χ2 = 13.20, p = 0.0050).
SUP reported suicide decedents were more likely to experience a number of SLEs compared to PS controls: (1) spouse or partner left him/her (OR = 16.4 [95% CI = 4.4, 61.4] χ2 = 19.93, p = 0.0001); (2) serious ongoing arguments with a close friend or family member (OR = 10.4 [95% CI = 2.5, 43.8] χ2 = 10.42, p = 0.0165); (3) trouble with the police (civilian or military) (OR = 7.9 [95% CI = 2.2, 28.4] χ2 = 11.00, p = 0.0090); 4) arrested for an incident not related to driving (OR = 8.8 [95% CI = 1.6, 47.2] χ2 = 8.48, p = 0.0370); (5) experienced some type of perceived failure or humiliation (OR = 18.3 [95% CI = 5.6, 60.1] χ2 = 25.00, p < 0.0001) and (6) any other very stressful event (OR = 5.3 [95% CI = 2.2, 12.3] χ2 = 16.09, p = 0.0030) (Tables 1 and 2).
TABLE 1. Next‐of‐kin univariable logistic regression model of reported lifetime and recent stressful events
CharacteristicsNext of kin
CasesControls (propensity)Controls (12‐month ideation)
(n = 61)(n = 128)(n = 108)
%%ORa, b(95% CI)%ORa, b(95% CI)
I. Lifetime trauma stressors (Ever)
a. Serious physical assault (e.g., mugging)
Yes versus No20.9711.352.1(1.0, 4.6)19.021.0(0.2, 5.3)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  3.53, 0.2111 <0.01, 0.9732
b. Sexual assault or rape
Yes versus No17.074.654.2(1.5, 11.5)7.482.5(0.2, 26.4)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  7.54, 0.0420 0.58, 0.9732
c. Serious assault happened to a close friend or relative
Yes versus No28.6921.471.3(0.7, 2.7)21.641.3(0.3, 6.3)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.76, 0.5377 0.09, 0.9732
d. Murder of a close friend or relative
Yes versus No10.0811.381.0(0.4, 2.6)11.730.8(0.1, 6.2)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  <0.01, 0.9480 0.05, 0.9732
e. Suicide of a close friend or relative
Yes versus No28.2210.363.0(1.5, 6.3)13.212.6(0.4, 15.9)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  8.87, 0.0406 1.12, 0.9732
f. Attempted suicide of a close friend or relative
Yes versus No14.7116.051.0(0.4, 2.2)14.291.0(0.2, 6.2)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.01, 0.9480 <0.01, 0.9732
g. Combat death of a close friend or relative
Yes versus No34.0637.770.9(0.5, 1.7)34.910.8(0.2, 3.4)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.16, 0.8113 0.05, 0.9732
h. Accidental death of a close friend or relative
Yes versus No36.5626.101.6(0.8, 2.9)25.621.5(0.4, 6.5)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  1.86, 0.3462 0.35, 0.9732
i. He/She witnessed someone being seriously injured or killed
Yes versus No36.3428.251.6(0.8, 3.1)39.240.8(0.2, 3.5)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  2.08, 0.3462 0.05, 0.9732
j. He/She discovered or handled a dead body
Yes versus No16.9925.540.6(0.3, 1.3)33.870.4(0.1, 1.6)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  1.58, 0.3654 1.74, 0.9732
k. He/She had a life‐threatening illness or injury
Yes versus No10.088.371.2(0.4, 3.4)8.121.2(0.1, 12.0)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.15, 0.8113 0.01, 0.9732
l. He/She was in a disaster (for example, Hurricane, fire, flood, earthquake) where he/she could have died
Yes versus No4.4413.220.2(0.1, 0.9)19.040.2(0.0, 1.3)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  4.29, 0.17922.80, 0.9732 
II. Psychiatric disorders
Classic mental health disorder (Admin)78.0239.785.0(2.3, 10.8)61.452.0(0.5, 8.3)
Yes versus No   16.83, <0.0001  0.83, 0.3862
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c     
III. Recent stressful life events
a. A serious financial problem
Past month versus Never25.9417.782.0(0.9, 4.4)8.394.5(0.5, 41.7)
Lifetime versus Never35.2130.301.4(0.7, 2.9)32.611.5(0.4, 6.1)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  3.18, 0.2829 1.84, 0.7696
b. Spouse or partner left him/her
Past month versus Never21.512.5210.4(3.5, 30.9)2.709.4(0.3, 345.3)
Lifetime versus Never22.5927.251.1(0.5, 2.3)30.850.9(0.2, 4.0)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  18.01, 0.0009 1.54, 0.7696
c. He/She went through a divorce
Past month versus Never3.093.171.2(0.2, 7.0)5.100.4(0.0, 8.7)
Lifetime versus Never13.7115.980.8(0.3, 1.9)26.840.4(0.1, 2.0)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.36, 0.8833 1.50, 0.7696
d. Spouse or partner cheated on him/her
Past month versus Never5.980.00‐‐1.065.9(0.0, ‐)
Lifetime versus Never19.6924.730.9(0.4, 1.8)30.670.6(0.1, 2.6)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.12, 0.9396 0.92, 0.7696
e. Serious betrayal by someone else close to him/her
Past month versus Never11.622.415.3(1.5, 18.0)1.1811.2(0.1, ‐)
Lifetime versus Never23.2516.681.7(0.8, 3.6)21.551.2(0.2, 6.0)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  8.25, 0.0365 0.81, 0.7696
f. Serious ongoing arguments or break‐up with some other close friend or family member
Past month versus Never25.604.875.9(2.4, 14.5)5.145.8(0.4, 89.6)
Lifetime versus Never22.2425.081.4(0.6, 2.9)28.081.0(0.2, 4.8)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  15.01, 0.0027 1.66, 0.7696
h. He/She caused an accident where someone else was hurt or property was damaged
Past month versus Never10.890.00‐‐0.5920.9(0.0, ‐)
Lifetime versus Never14.716.243.0(1.2, 7.8)9.611.7(0.2, 14.3)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  5.33, 0.1255 0.85, 0.7696
i. He/She didn't get promoted when he/she thought he/she should have been
Past month versus Never12.242.644.3(1.3, 14.1)2.324.7(0.1, 234.7)
Lifetime versus Never16.9925.340.6(0.3, 1.4)28.680.5(0.1, 2.6)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  7.81, 0.0402 1.39, 0.7696
j. He/She got a lower score than he/she expected on his/her efficiency report or performance rating
Past month versus Never6.994.141.2(0.3, 4.4)1.066.3(0.0, ‐)
Lifetime versus Never12.3620.720.5(0.2, 1.3)21.570.5(0.1, 2.9)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  2.29, 0.3765 1.10, 0.7696
k. He/She received military punishment (for example, Court Martial, Article 15, Captain's Mast, Office Hours, Letter of reprimand, other)
Past month versus Never21.310.4656.4(7.2, 439.8)2.709.5(0.3, 342.8)
Lifetime versus Never13.9016.501.1(0.4, 2.5)15.761.0(0.2, 6.1)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  14.84, 0.0027 1.53, 0.7696
l. He/She had trouble with the police (civilian or military)
Past month versus Never20.230.00‐‐0.5972.3(0.0, ‐)
Lifetime versus Never23.986.173.7(1.5, 8.9)9.704.1(0.5, 31.3)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  8.25, 0.0162 2.90, 0.7696
n. He/She was arrested for an incident not related to driving
Past month versus Never7.800.00‐‐0.00‐‐
Lifetime versus Never17.8011.901.8(0.8, 4.0)5.414.2(0.3, 56.9)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  8.25, 0.0365 1.14, 0.7696
q. He/She experienced some type of perceived failure or humiliation, such as letting down those around him/her in some way
Past month versus Never39.923.2124.4(9.2, 64.5)5.0216.1(1.1, 242.7)
Lifetime versus Never20.8915.713.0(1.3, 6.9)15.332.8(0.5, 15.9)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  42.34, <0.0001 4.79, 0.7696
r. Any other very stressful event
Past month versus Never22.326.354.7(2.0, 11.1)7.614.3(0.4, 44.0)
Lifetime versus Never24.7217.982.0(1.0, 4.2)13.503.0(0.4, 20.7)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  13.20, 0.0050 2.33, 0.7696
Note: Bold values are statistically significant at p‐value ≤ 0.05. Table abbreviated due to space constraints. Results for excluded variables available upon request.
Abbreviations: FDR, false discovery rate; OR, odds ratio.
a
ORs statistics obtained from separate multivariate logistic regression models testing differences between cases and each control group.
b
Each predictor was adjusted for deployment status (never, previously) and number of years of active service, but not each other.
c
p values have been corrected using false discovery rate (fdr).
TABLE 2. Supervisor univariable logistic regression model of reported lifetime and recent stressful events
CharacteristicsSupervisor
CasesControls (Propensity)Controls (12‐month ideation)
(n = 107)(n = 80)(n = 73)
%%ORa, b(95% CI)%ORa, b(95% CI)
I. Lifetime trauma stressors (Ever)
a. Serious physical assault (for example, mugging)
Yes versus No4.831.953.0(0.7, 13.4)5.440.9(0.0, 23.3)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  2.00, 0.5455 <0.01, 0.9774
b. Sexual assault or rape
Yes versus No7.860.808.6(1.1, 65.3)0.00‐‐
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  4.29, 0.2681‐  
c. Serious assault happened to a close friend or relative
Yes versus No9.905.261.9(0.7, 5.0)7.971.2(0.1, 17.3)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  1.49, 0.5455 0.02, 0.9774
d. Murder of a close friend or relative
Yes versus No3.294.570.8(0.2, 3.1)6.460.5(0.0, 11.0)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.09, 0.8252 0.17, 0.9774
e. Suicide of a close friend or relative
Yes versus No12.445.912.2(0.9, 5.4)7.121.8(0.1, 28.6)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  2.65, 0.4821 0.17, 0.9774
f. Attempted suicide of a close friend or relative
Yes versus No6.183.002.0(0.6, 7.1)5.861.0(0.0, 22.3)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  1.13, 0.5754 <0.01, 0.9774
g. Combat death of a close friend or relative
Yes versus No19.3323.550.9(0.5, 1.7)31.260.5(0.1, 2.7)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.13, 0.8252 0.55, 0.9774
h. Accidental death of a close friend or relative
Yes versus No9.5111.720.7(0.3, 1.6)9.540.9(0.1, 11.2)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.66, 0.6997 0.01, 0.9774
i. He/She witnessed someone being seriously injured or killed
Yes versus No22.9019.741.5(0.8, 2.8)22.641.1(0.2, 6.7)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  1.42, 0.5455 0.02, 0.9774
j. He/She discovered or handled a dead body
Yes versus No15.2219.940.8(0.4, 1.6)22.710.6(0.1, 3.6)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.36, 0.6997 0.27, 0.9774
k. He/She had a life‐threatening illness or injury
Yes versus No3.293.710.9(0.2, 3.5)0.546.8(0.0, ‐)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.05, 0.8306 0.16, 0.9774
l. He/She was in a disaster (for example, Hurricane, fire, flood, earthquake) where he/she could have died
Yes versus No2.4615.160.2(0.0, 0.6)7.250.3(0.0, 6.7)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  7.50, 0.0868 0.50, 0.9774
II. Psychiatric disorders
Classic mental health disorder (Admin)
Yes versus No77.1338.65.8(3.2, 10.5)62.591.9(0.4, 8.8)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c   33.40, <0.0001  0.75, 0.3862
II. Recent stressful events
a. A serious financial problem
Past month versus Never17.297.722.6(1.1, 5.8)11.021.5(0.1, 15.4)
Lifetime versus Never21.2321.791.0(0.5, 1.9)30.000.6(0.1, 3.3)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  5.11, 0.1418 0.57, 0.9767
b. Spouse or partner left him/her
Past month versus Never22.241.9416.4(4.4, 61.4)5.594.7(0.2, 104.0)
Lifetime versus Never23.9417.622.0(1.1, 3.9)30.251.0(0.2, 4.7)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  19.93, <0.0001 1.01, 0.9767
c. He/She went through a divorce
Past month versus Never2.362.740.6(0.1, 3.4)0.882.8(0.0, ‐)
Lifetime versus Never18.4015.121.4(0.7, 2.8)15.421.3(0.2, 9.7)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  1.16, 0.6716 0.14, 0.9767
d. Spouse or partner cheated on him/her
Past month versus Never6.650.00‐‐1.574.6(0.0, ‐)
Lifetime versus Never18.878.932.5(1.2, 5.5)17.151.2(0.2, 7.9)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  5.46, 0.1418 0.30, 0.9767
e. Serious betrayal by someone else close to him/her
Past month versus Never5.540.00‐‐0.00‐‐
Lifetime versus Never12.2613.850.9(0.4, 2.0)10.291.3(0.1, 13.8)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.03, 0.9969 0.05, 0.9767
f. Serious ongoing arguments or break‐up with some other close friend or family member
Past month versus Never13.761.6610.4(2.5, 43.8)0.00‐‐
Lifetime versus Never13.6211.201.4(0.6, 3.0)12.141.3(0.1, 11.8)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  10.42, 0.0165 0.05, 0.9767
h. He/She caused an accident where someone else was hurt or property was damaged
Past month versus Never4.831.702.6(0.5, 12.9)3.141.7(0.0, 99.5)
Lifetime versus Never5.937.950.9(0.3, 2.4)3.322.0(0.0, 109.2)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  1.45, 0.6016 0.18, 0.9767
i. He/She didn't get promoted when he/she thought he/she should have been
Past month versus Never0.820.681.2(0.1, 23.2)4.020.2(0.0, 12.1)
Lifetime versus Never14.7224.470.5(0.2, 0.9)22.250.6(0.1, 3.3)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  5.08, 0.1418 0.92, 0.9767
j. He/She got a lower score than he/she expected on his/her efficiency report or performance rating
Past month versus Never4.002.191.4(0.3, 6.7)4.410.6(0.0, 22.6)
Lifetime versus Never4.1120.110.1(0.0, 0.4)29.850.1(0.0, 0.6)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  12.67, 0.0081 6.01, 0.8910
k. He/She received military punishment (for example, Court Martial, Article 15, Captain's Mast, Office Hours, Letter of reprimand, other)
Past month versus Never16.650.00‐‐0.8821.6(0.0, ‐)
Lifetime versus Never13.1815.881.0(0.5, 2.2)23.190.6(0.1, 3.7)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  0.01, 0.9969 0.93, 0.9767
l. He/She had trouble with the police (civilian or military)
Past month versus Never16.542.197.9(2.2, 28.4)2.568.1(0.1, 674.8)
Lifetime versus Never11.5417.450.7(0.3, 1.4)7.002.1(0.1, 34.9)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  11.00, 0.0090 1.10, 0.9767
n. He/She was arrested for an incident not related to driving
Past month versus Never9.791.218.8(1.6,47.2)0.00‐‐
Lifetime versus Never9.084.112.4(0.8, 7.0)2.983.7(0.1, 229.7)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  8.48, 0.0370 0.38, 0.9767
q. He/She experienced some type of perceived failure or humiliation, such as letting down those around him/her in some way
Past month versus Never29.242.4118.3(5.6, 60.1)3.4411.3(0.2, 530.6)
Lifetime versus Never13.479.932.2(1.0, 5.1)20.210.9(0.1, 5.7)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  25.00, <0.0001 1.58, 0.9767
r. Any other very stressful event
Past month versus Never24.386.025.3(2.2, 12.3)2.5611.4(0.1, 952.4)
Lifetime versus Never9.4710.940.9(0.4, 2.1)19.750.6(0.1, 3.7)
χ2 ${\chi }^{2}$, pfdr ${p}_{fdr}$ c  16.09, 0.0030 1.62, 0.9767
Notes: Bold values are statistically significant at p‐value ≤ 0.05. Table abbreviated due to space constraints. Results for excluded variables available upon request.
Abbreviations: FDR, false discovery rate; OR, odds ratio.
a
ORs statistics obtained from separate multivariate logistic regression models testing differences between cases and each control group.
b
Each predictor was adjusted for deployment status (never, previously) but not for each other.
c
p values have been corrected using false discovery rate (fdr).

Population attributable risk

The population attributable risk percent for suicide death associated with lifetime exposure to sexual assault or rape and lifetime exposure to the death of a close friend or relative by suicide was estimated to be 12.95% and 17.37% respectively (NOK) and 5.87% for lifetime exposure to sexual assault or rape (SUP).

Multivariable models

The final NOK model predicting suicide death included the following: spouse or partner leaving them (OR = 8.5 [95% CI = 2.0, 35.8] χ2 = 9.79, p < 0.0075), military punishment4 (OR = 25.3 [95% CI = 3.1, 206.2] χ2 = 14.67, p < .0007), trouble with the police (OR = 6.3 [95% CI = 1.8, 22.0] χ2 = 8.93, p < 0.0115), and some type of perceived failure or humiliation (OR = 9.3 [95% CI = 2.4, 35.1] χ2 = 10.97, p < .0041).
The final SUP model predicting suicide death included the following: spouse or partner leaving them (OR = 14.5 [95% CI = 2.9, 72.26] χ2 = 14.39, p < 0.0008); received lower score than expected on performance report (OR = 0.03 [95% CI = 0.01, 0.14)] χ2 = 19.10, p < .0001), experienced perceived failure or humiliation (OR = 15.10 [95% CI = 4.07, 56.08] χ2 = 20.38, p < 0.0001), any other stressful event (OR = 3.89 [95% CI = 1.44, 10.54] χ2 = 7.15, p < 0.028), and history of lifetime classic mental health disorder from the administrative record (OR = 4.5 [95% CI = 2.2, 9.)] χ2 = 16.76, p < 0.0001). (Tables 3 and 4).
TABLE 3. Next‐of‐kin multivariable logistic regression model of suicide with lifetime mental health and recent stressors
CharacteristicsNext of kin
Controls (propensity)Controls (12‐month ideation)
N = 128N = 108
OR(95% CI)OR(95% CI)
I. Demographics
Deployment
Never versus Previous0.68(0.21, 2.25)0.85(0.13, 5.67)
Wald χ2 ${\chi }^{2}$, p‐value0.3899, 0.53230.0294, 0.864
Years active
5‐8′ versus 1‐4′0.69(0.21, 2.24)0.99(0.16, 5.94)
9+ versus 1‐4′0.55(0.17, 1.81)1.0(0.16, 6.25)
Wald χ2 ${\chi }^{2}$, p‐value0.9825, 0.61190.0003, 0.9999
II. Recent stressful events
Spouse or partner left them
Past month versus Never happened8.45(2.0, 35.78)2.62(0.27, 25.62)
Happened, but not in past month versus Never happened0.63(0.25, 1.6)0.8(0.18, 3.64)
Wald χ2 ${\chi }^{2}$, p‐value9.788, 0.00750.8803 0.6439
He/She received military punishment (e.g., Court Marshall, Article 15, Captain's Mass, Office Hours, Letter of reprimand, other)
Past month versus Never happened25.32(3.11, 206.16)2.7(0.28, 26.57)
Happened, but not in past month versus Never happened0.22(0.06, 0.78)0.46(0.06, 3.5)
Wald χ2 ${\chi }^{2}$, p‐value14.6682, 0.00071.4245, 0.4906
He/She had trouble with police
Past month versus Never happened5.11 (0.15, 169.56)1.01 (0.03, 36.79)
Happened, but not in past month versus Never happened6.3 (1.8, 22.03)2.58 (0.39, 16.91)
Wald χ2 ${\chi }^{2}$, p‐value8.9306, 0.01150.9844, 0.6113
He/She experienced some type of perceived failure or humiliation, such as letting down those around him/her in some way
Past month versus Never happened9.25(2.44, 35.10)3.61(0.38, 34.57)
Happened, but not in past month versus Never happened2.07(0.78, 5.51)1.75(0.32, 9.61)
Wald χ2 ${\chi }^{2}$, p‐value10.9739, 0.00411.3702, 0.504
III. Psychiatric disorder
Lifetime classic mental health disorder (Admin)
Yes versus no3.84 (1.46, 10.12)1.6 (0.32, 8.07)
Wald χ2 ${\chi }^{2}$, p‐value7.3933, 0.00650.3231, 0.5697
Notes: Bold values are statistically significant at p‐value ≤ 0.05. Multivariable Logistic regression model was constructed using predictors still significant at p ≤ 0.05 after FDR adjustment. The model was corrected with Firth's penalized likelihood method to help address small sample size bias.
Abbreviations: CI, Confidence Interval; OR, Odds Ratio.
TABLE 4. Supervisor multivariable logistic regression model of suicide with lifetime mental health and recent stressors
CharacteristicsSupervisor
Controls (propensity)Controls (12‐month ideation)
N = 80N = 73
OR(95% CI)OR(95% CI)
I. Demographics
Deployment
Never versus Previous2.13(0.87, 5.22)0.77(0.15, 3.92)
Wald χ2 ${\chi }^{2}$, p‐value2.723, 0.09890.0956, 0.7571
II. Recent stressful events
Spouse or partner left them
Past month versus Never happened14.48(2.9, 72.26)4.26(0.38, 47.32)
Happened, but not in past month versus Never happened3.39(1.39, 8.24)1.31(0.27, 6.29)
Wald χ2 ${\chi }^{2}$, p‐value14.3883, 0.00081.39, 0.4991
Received lower score than expected on performance report
Past month versus Never happened1.27(0.15, 10.57)0.23(0.01, 3.67)
Happened, but not in past month versus Never happened0.03(0.01, 0.14)0.08(0.01, 0.68)
Wald χ2 ${\chi }^{2}$, p‐value19.1003, <0.00016.0036, 0.0497
Experienced perceived failure/humiliation
Past month versus Never happened15.10(4.07, 56.08)3.42(0.43, 26.89)
Happened, but not in past month versus Never happened5.84(1.65, 20.61)1.33(0.21, 8.51)
Wald χ2 ${\chi }^{2}$, p‐value20.376, <0.00011.3809, 0.5013
Any other stressful event
Past month versus Never happened3.89(1.44, 10.54)4.42(0.41, 47.57)
Happened, but not in past month versus Never happened1.26(0.38, 4.21)0.57(0.09, 3.65)
Wald χ2 ${\chi }^{2}$, p‐value7.1521, 0.0281.9503, 0.3771
III. Psychiatric disorder
Lifetime classic mental health disorder (Admin)
Yes versus no4.47 (2.18,9.15)2.51(0.58, 10.81)
Wald χ2 ${\chi }^{2}$, p‐value16.7647, <0.00011.5251, 0.2169
Note: Bold values are statistically significant at p‐value ≤ 0.05. Multivariable Logistic regression model was constructed using predictors still significant at p ≤ 0.05 after FDR adjustment. The model was corrected with Firth's penalized likelihood method to help address small sample size bias.
Abbreviations: CI, Confidence Interval; OR, Odds Ratio.

Risk score

The recent SLEs statistically significant at p < 05 after FDR adjustment in the univariable analyses used to create the risk score construct for NOK included: (1) spouse or partner left them; (2) serious betrayal by someone else close to him/her; (3) serious argument/breakup with close friend or family; (4) caused accident where someone else was hurt/property damaged; (5) didn't get promoted when they thought they should have been; (6) received military punishment; (7) had trouble with police; (8) arrested for non‐driving violation; (9) experienced perceived failure/humiliation; and (10) any other stressful event. Items used to create the risk score construct for SUP included: (1) spouse or partner left them; (2) received lower score than expected on performance report; (3) had trouble with police; (4) arrested for non‐driving violation; (5) experienced perceived failure/humiliation; and (6) other stressful event.
For NOK and SUP, standardized Chronbach Alpha = 0.809392 and 0.59307 respectively, suggesting the items are measuring one dimension. NOK and SUP models predicting suicide death among PS controls were high (OR = 8.3, [95% CI = 4.4, 15.8] χ2 = 42.04, p < 0.0001, AUC, 0.74 (0.7, 0.8); NOK) and (OR = 13.0 [95% CI = 6.7, 25.3] χ2 = 57.13, p < 0.0001, AUC, 0.76 (0.7, 0.8); SUP) and slightly higher among those who reported SI in the past year, suggesting a strong model fit (OR = 5.9, [95% CI = 1.5, 24.0] χ2 = 6.24, p = 0.0125, AUC, 0.73 (0.7, 0.8); NOK) and (OR = 8.6, [95% CI = 1.4, 51.5] χ2 = 5.49, p = 0.0191, AUC, 0.78 (0.7, 0.8); SUP) (Tables 5 and 6) and (Figure 1).
TABLE 5. Next‐of‐kin risk score logistic regression model for suicide
 Next‐of‐kin
Controls (propensity)Controls (12‐month ideation)
nWeighted %nWeighted %
Risk score: # Of at risk events
010684.258881.41
11611.411312.65
252.3843.79
311.9632.14
4‐‐00.00
5‐‐‐‐
6‐‐‐‐
7‐‐‐‐
8‐‐‐‐
9‐‐‐‐
10‐‐‐‐
Mean0.23 0.28 
Median0 0 
Mode0 0 
Q10 0 
Q30 0 
Minimum    
Maximum    
Std0.55 0.67 
Logistic Model with risk score + deployment + years active
 OR(95% CI)OR(95% CI)
Score construct (continuous var)2.739(1.9, 3.9)2.216(1.0, 4.5)
χ2 ${\chi }^{2}$, p‐value31.4322, <0.00013.78, 0.0517
AUC0.7545 (0.7, 0.8)0.7484 (0.7, 0.8)
Score construct (categorical var) 1+ versus 08.339(4.4, 15.8)5.923(1.5, 24.0)
χ2 ${\chi }^{2}$, p‐value42.0359, <0.00016.237, 0.0125
AUC0.7382 (0.7, 0.8)0.7267 (0.7, 0.8)
Note: Bold values are statistically significant at p‐value ≤ 0.05. Variables for constructing risk score construct included whether the soldier experienced (1) Spouse or partner left them, (2) Serious betrayal of someone close, (3) Serious argument/breakup with close friend or family member, (4) Caused accident where someone else was hurt/property damaged, (5) Didn't get promoted when they thought they should have been, (6) Received military punishment, (7) Had trouble with police, (8) Arrested for driving violations, (9) Experienced perceived failure/humiliation, (10) Any other stressful event within the past month. Deployment status (never, previously) and Years Active (1‐4′, 5‐8′, 9+) were controlled for in the model. The model was corrected with Firth's penalized likelihood method to help address small sample size bias.
Abbreviations: AUC, Area under the receiver operator characteristic curve; CI, Confidence Interval; OR, Odds Ratio.
TABLE 6. Supervisor risk score logistic regression model for suicide
 Supervisor
Controls (propensity)Controls (12‐month ideation)
nWeighted %nWeighted %
Risk score: # Of at risk events
07189.396688.41
146.1169.03
254.4912.56
3‐‐‐‐
4‐‐‐‐
5‐‐‐‐
6‐‐‐‐
Mean0.18 0.11 
Median0 0 
Mode0 0 
Q10 0 
Q30 0 
Minimum    
Maximum    
Std0.52 0.36 
Logistic model with risk score + deployment
 OR(95% CI)OR(95% CI)
Score construct (continuous var)4.7(2.9, 7.4)3.9(1.7, 14.0)
χ2 ${\chi }^{2}$, p‐value42.12, <0.00014.23, 0.0395
AUC0.7610 (0.7, 0.8)0.7754 (0.7, 0.8)
Score construct (categorical var) 1+ versus 013.0(6.7, 25.3)8.6(1.4, 51.5)
χ2 ${\chi }^{2}$, p‐value57.13, <0.00015.49, 0.0191
AUC0.7571 (0.7, 0.8)0.7825 (0.7, 0.8)
Note: Bold values are statistically significant at p‐value ≤ 0.05. Variables for constructing risk score construct included whether the soldier experienced (1) Spouse or partner left them, (2) Serious argument/breakup with other close friend or family member, (3) Had trouble with the police, (4) Arrested for non‐driving violation, (5) Experienced perceived failure/humiliation, (6) Any other stressful event within the past month. Deployment status (never, previously) was controlled for in the model. The model was corrected with Firth's penalized likelihood method to help address small sample size bias.
Abbreviations: AUC, Area under the receiver operator characteristic curve; CI, Confidence Interval; OR, Odds Ratio.
image
FIGURE 1. A. Stressful life events and suicide risk next‐of‐kin. B. Stressful life events and suicide risk supervisor

DISCUSSION

There are two significant findings to emerge from this study. First, the combination of significant recent stressors predicted suicide death in those who reported suicide ideation in the past year. To our knowledge, this is the first time this finding has been reported and the evidence from this study suggests the combination of these recent stressors (e.g., relationship problems, military punishment, and the experience of perceived failure or humiliation) may contribute to the transition from ideation to action. Second, soldiers who experienced military punishment, spouse/relationship problems or perceived failure or humiliation in the month prior to death had significantly increased odds of suicide death. These findings persisted even after controlling for lifetime stressful events and lifetime classic mental health disorders from the administrative record. Each will be described below.
Our risk score models predict suicide death with accuracy and suggest the importance of a combination of stressful life events in the month prior to death. These findings were observed for both types of controls and, importantly, for controls who reported SI in the past year, suggesting that the combination of these recent events may contribute to the transition from ideation to action. Ideation‐to‐action theories of suicide emphasize the dynamic nature of suicidal behaviors and focus on the temporal dynamics of suicide risk. The fluid‐vulnerability theory—a diathesis‐stress model provides a framework for examining suicidal behaviors as a dynamic construct and may serve as a framework for the development of interventions for suicide prevention and aid clinicians in predicting one at high risk for a suicide. (24, 25) In the model, predisposition or baseline risk (e.g., prior suicide attempts, adverse childhood experiences, and genetic vulnerabilities) are exacerbated by environmental triggers (e.g., relationship problems, trauma, death of a loved one, financial stress, job loss) which leads to “the suicidal mode”, which consists of cognitive, behavioral, emotional and physiological domains that are actionable targets for intervention.
Our findings confirm the importance of relationship problems in the month prior to death even after controlling for a lifetime history of classic mental health disorders. The fact that NOK and SUP both reported spousal/significant other relationship problems suggests the importance of family/couple interventions as a target for suicide intervention and is consistent with our hypothesis and recent research highlighting the association between marital distress and suicidal ideation in active‐duty soldiers (26).
NOK reported receiving military punishment in the month prior to the soldier's death as a significant stressor, even after controlling for lifetime history of classic mental health disorder from the administrative record. SUP were not asked specifically about military punishment and thus could not collaborate this finding, but did point to the potential importance of poor work performance and suicidal behaviors. Prior research has reported the association between demotion and failure to be promoted and suicide death, but to our knowledge, this is the first time military punishment has been observed as a significant predictor of suicide death, as reported by informants. Recent research reported strong association between discharge characterization (e.g., honorable, “bad paper” or other than honorable, bad conduct, dishonorable, and uncharacterized) and homelessness among those separated from service (27). The importance of context is emphasized in recent research by Bryan, who described how one's quality of life, and environmental stressors may lead to suicide in the Cusp Catastrophe Model of Suicide (28).
Perceived humiliation and failure predicted suicide death as reported by informants, after controlling for lifetime classic mental health disorders from the administrative record. Humiliation, perceived burdensomeness, social defeat, and thwarted belongingness mediated the relationship between suicide crisis syndrome and past month suicide attempt and ideations in high risk psychiatric outpatients (29). Humiliation hypothesized as a state characteristic may interact with trait characteristics of increased vulnerability and lead to suicidal ideation, plan and attempts (30).
Our findings may be interpreted considering several limitations. Psychological autopsy studies are limited by bias related to the informant's knowledge of the status of cases and controls. Despite widely held preconceptions about the informant method of research, including recall bias, studies have shown informant data to be valid and reliable (31). The relatively small sample size limited the power to examine interactions. Stressful life events measures are associated with recall bias and intracategory variability (32). The response rates were low compared to surveys conducted in the general population, but they were high for multi‐informant interviews conducted in a military population (33, 34). We were not able to examine gender differences and this, with the high rates of interpersonal violence in females, may account for our lack of significant findings of lifetime interpersonal violence as a predictor of suicide death. Despite these limitations, our results may help inform suicide prevention and intervention efforts which target unique stressors that may significantly increase risk of suicide in the month prior to death, such as relationship problems, military punishment and perceived failure or humiliation.
Future studies need to be replicated in larger samples where gender differences can be examined, as recent research suggests gender differences in exposure to longstanding and severe life problems are associated with suicide risk (35). Furthermore, replication in a prospective cohort to predict suicide death will minimize recall bias and inform prevention efforts in this population. It will also be important for future research to examine the association of different types of military punishment (e.g., Article 15s, Court Marshall, Captain's Mass, Office Hours, Letter of reprimand) in service members to identify targets for intervention and suicide prevention for supervisors so they can provide resources and access to support the accused.

Implications

The study identified several recent stressors that increased the odds of suicide death and how these recent stressors contributed to suicide risk, especially the transition from ideation to completed suicide, after adjusting for lifetime mental disorders. The dynamic and heterogeneous nature of suicide necessitate the need to tailor treatment to the individual. For example, new smartphone applications with just‐in‐time interventions that are adaptive to internal states and external contexts are recommended (36).

Footnotes

The Army STARRS Team consists of Co‐Principal Investigators: Robert J. Ursano, MD (Uniformed Services University) and Murray B. Stein, MD, MPH (University of California San Diego and VA San Diego Healthcare System).
Site Principal Investigators: James Wagner, PhD (University of Michigan) and Ronald C. Kessler, PhD (Harvard Medical School).
Army scientific consultant/liaison: Kenneth Cox, MD, MPH (Office of the Assistant Secretary of the Army (Manpower and Reserve Affairs))
Other team members: Pablo A. Aliaga, MA (Uniformed Services University); David M. Benedek, MD (Uniformed Services University); Laura Campbell‐Sills, PhD (University of California San Diego); Carol S. Fullerton, PhD (Uniformed Services University); Nancy Gebler, MA (University of Michigan); Meredith House, BA (University of Michigan); Paul E. Hurwitz, MPH (Uniformed Services University); Sonia Jain, PhD (University of California San Diego); Tzu‐Cheg Kao, PhD (Uniformed Services University); Lisa Lewandowski‐Romps, PhD (University of Michigan); Alex Luedtke, PhD (University of Washington and Fred Hutchinson Cancer Research Center); Holly Herberman Mash, PhD (Uniformed Services University); James A. Naifeh, PhD (Uniformed Services University); Matthew K. Nock, PhD (Harvard University); Victor Puac‐Polanco, MD, DrPH (Harvard Medical School); Nancy A. Sampson, BA (Harvard Medical School); and Alan M. Zaslavsky, PhD (Harvard Medical School).
Army STARRS was sponsored by the Department of the Army and funded under cooperative agreement number U01MH087981 with the U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Mental Health (NIH/NIMH). Subsequently, STARRS‐LS was sponsored and funded by the Department of Defense (USUHS grant numbers HU00011520004 and HU0001202003). The grants were administered by the Henry M. Jackson Foundation for the Advancement of Military Medicine Inc. (HJF). The contents are solely the responsibility of the authors and do not necessarily represent the views of the Department of Health and Human Services, NIMH, the Department of the Army, Department of Defense or HJF.
1
HADS is an integrated administrative data file containing key elements from 38 different Army and DOD data systems for over 1.6 million soldiers (Regular Army, Army Reserve, and National Guard) on active duty during calendar years 2004–2009.
2
Levin's Formula is only applicable for binary variables; therefore, PARP could only be calculated for the lifetime stressors.
3
Due to space constraints only the recent stressors significant in past month, compared to never were included in the text and not those stressors significant in the soldier's lifetime, but not in the past month.
4
Due to space constraints only the significant past month recent stressors were included in the text and not those stressors that happened, but not in the past month.

Supplementary Material

File (rcp21054-sup-0001-suppl-data.pdf)
Supplementary Material S1
File (rcp21054-sup-0002-suppl-data.pdf)
Supplementary Material S2
File (rcp21054-sup-0003-table_s3.docx)
Supplementary Material S3

REFERENCES

1.
World Health Organization . Suicide fact sheet 2021. Available from: https://www.who.int/news‐room/fact‐sheets/detail/suicide
Google Scholar
2.
Department of Defense Suicide Prevention Office . The DOD annual suicide report calendar year 2020. Sept 03, 2021. Contract No.: F‐71A76FD.
Google Scholar
3.
Ramchand R, Acosta J, Burns RM, Jaycox LH, Pernin CG. The war within: preventing suicide in the U.S. military. Rand Health Q. 2011;1(1):2.
Google Scholar
4.
Armed Forces Surveillance Center . Deaths by suicide while on active duty, active and reserve components. U.S. Armed Forces, 1998‐2011; 2012.
Google Scholar
5.
Chu C, Stanley IH, Marx BP, King AJ, Vogt D, Gildea SM, et al. Associations of vulnerability to stressful life events with suicide attempts after active duty among high‐risk soldiers: results from the Study to Assess Risk and Resilience in Servicemembers‐longitudinal study (STARRS‐LS). Psychol Med. 2022:1–11. https://doi.org/10.1017/s0033291722000915
Google Scholar
6.
Blais RK, Monteith LL. Suicide ideation in female survivors of military sexual trauma: the trauma source matters. Suicide Life‐Threat Behav. 2019;49(3):643–52. https://doi.org/10.1111/sltb.12464
Google Scholar
7.
Monteith LL, Holliday R, Schneider AL, Forster JE, Bahraini NH. Identifying factors associated with suicidal ideation and suicide attempts following military sexual trauma. J Affect Disord. 2019;252:300–9. https://doi.org/10.1016/j.jad.2019.04.038
Google Scholar
8.
Naifeh JA, Ursano RJ, Kessler RC, Zaslavsky AM, Nock MK, Dempsey CL, et al. Transition to suicide attempt from recent suicide ideation in U.S. Army soldiers: results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). Depress Anxiety. 2019;36(5):412–22. https://doi.org/10.1002/da.22870
Google Scholar
9.
Department of Veterans Affairs . National strategy for preventing veteran suicide 2018–2028; 2018.
Google Scholar
10.
Bryan CJ, Rudd MD. Life stressors, emotional distress, and trauma‐related thoughts occurring in the 24 h preceding active duty U.S. soldiers' suicide attempts. J Psychiatr Res. 2012;46(7):843–8. https://doi.org/10.1016/j.jpsychires.2012.03.012
Google Scholar
11.
Logan J, Skopp NA, Karch D, Reger MA, Gahm GA. Characteristics of suicides among US army active duty personnel in 17 US states from 2005 to 2007. Am J Publ Health. 2012;102((Suppl 1)):S40–4. https://doi.org/10.2105/ajph.2011.300481
Google Scholar
12.
Nock MK, Deming CA, Fullerton CS, Gilman SE, Goldenberg M, Kessler RC, et al. Suicide among soldiers: a review of psychosocial risk and protective factors. Psychiatry. 2013;76(2):97–125. https://doi.org/10.1521/psyc.2013.76.2.97
Google Scholar
13.
Nock MK, Dempsey CL, Aliaga PA, Brent DA, Heeringa SG, Kessler RC, et al. Psychological autopsy study comparing suicide decedents, suicide ideators, and propensity score matched controls: results from the study to assess risk and resilience in service members (Army STARRS). Psychol Med. 2017;47(15):2663–74. https://doi.org/10.1017/s0033291717001179
Google Scholar
14.
Kessler RC, Colpe LJ, Fullerton CS, Gebler N, Naifeh JA, Nock MK, et al. Design of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). Int J Methods Psychiatr Res. 2013;22(4):267–75. https://doi.org/10.1002/mpr.1401
Google Scholar
15.
Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70(1):41–55. https://doi.org/10.1093/biomet/70.1.41
Google Scholar
16.
Ursano RJ, Colpe LJ, Heeringa SG, Kessler RC, Schoenbaum M, Stein MB, et al. The Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). Psychiatry. 2014;77(2):107–19. https://doi.org/10.1521/psyc.2014.77.2.107
Google Scholar
17.
Brugha TS, Cragg D. The list of threatening experiences: the reliability and validity of a brief life events questionnaire. Acta Psychiatr Scand. 1990;82(1):77–81. https://doi.org/10.1111/j.1600-0447.1990.tb01360.x
Google Scholar
18.
Bray RM. Department of defense survey of health related behaviors among active duty military personnel: a component of the defense lifestyle assessment program. DIANE Publishing Company; 2009.
Google Scholar
19.
Heeringa SG, Gebler N, Colpe LJ, Fullerton CS, Hwang I, Kessler RC, et al. Field procedures in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS): army STARRS field procedures. Int J Methods Psychiatr Res. 2013;22(4):276–87. https://doi.org/10.1002/mpr.1400
Google Scholar
20.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol. 1995;57(1):289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Google Scholar
21.
R Core Team: a language and environment for statistical computing. R Foundation for Statistical Computing. 2022. Available from: https://www.R‐project.org/
Google Scholar
22.
SAS Institute Inc . SAS (Version 9.4). 2018. Computer Software. https://www.sas.com
Google Scholar
23.
Lin C.‐K, Chen S.‐T. Estimation and application of population attributable fraction in ecological studies. Environ Health. 2019;18(1):52. https://doi.org/10.1186/s12940-019-0492-4
Google Scholar
24.
Bryan CJ, Butner JE, May AM, Rugo KF, Harris J, Oakey DN, et al. Nonlinear change processes and the emergence of suicidal behavior: a conceptual model based on the fluid vulnerability theory of suicide. New Ideas Psychol. 2020;57:100758. https://doi.org/10.1016/j.newideapsych.2019.100758
Google Scholar
25.
Rugo‐Cook KF, Kerig PK, Crowell SE, Bryan CJ. Fluid vulnerability theory as a framework for understanding the association between posttraumatic stress disorder and suicide: a narrative review. J Trauma Stress. 2021;34(6):1080–98. https://doi.org/10.1002/jts.22782
Google Scholar
26.
Whisman MA, Salinger JM, Labrecque LT, Gilmour AL, Snyder DK. Couples in arms: marital distress, psychopathology, and suicidal ideation in active‐duty army personnel. J Abnorm Psychol. 2020;129(3):248–55. https://doi.org/10.1037/abn0000492
Google Scholar
27.
Naifeh JA, Capaldi VF, Chu C, King AJ, Koh KA, Marx BP, et al. Prospective associations of military discharge characterization with post‐active duty suicide attempts and homelessness: results from the Study to Assess Risk and Resilience in Servicemembers‐Longitudinal Study (STARRS‐LS). Mil Med. 2022.
Google Scholar
28.
Bryan CJ. Rethinking suicide: why prevention fails and how we can do better. Oxford University Press. 2022 Nov. 01, 2021.
Google Scholar
29.
Cohen LJ, Gorman B, Briggs J, Jeon ME, Ginsburg T, Galynker I. The suicidal narrative and its relationship to the suicide crisis syndrome and recent suicidal behavior. Suicide Life‐Threat Behav. 2019;49(2):413–22. https://doi.org/10.1111/sltb.12439
Google Scholar
30.
Pia T, Galynker I, Schuck A, Sinclair C, Ying G, Calati R. Perfectionism and prospective near‐term suicidal thoughts and behaviors: the mediation of fear of humiliation and suicide crisis syndrome. Int J Environ Res Publ Health. 2020;17(4):1424. https://doi.org/10.3390/ijerph17041424
Google Scholar
31.
Conner KR, Beautrais AL, Brent DA, Conwell Y, Phillips MR, Schneider B. The next generation of psychological autopsy studies. Suicide Life‐Threatening Behav. 2011;41(6):594–613. https://doi.org/10.1111/j.1943-278x.2011.00057.x
Google Scholar
32.
Dohrenwend BP. Inventorying stressful life events as risk factors for psychopathology: toward resolution of the problem of intracategory variability. psychological. Psychol Bulletin. 2006;132(4):477–95. https://doi.org/10.1037/0033-2909.132.3.477
Google Scholar
33.
Cavanagh JT, Carson AJ, Sharpe M, Lawrie SM. Psychological autopsy studies of suicide: a systematic review. Psychol Med. 2003;33(3):395–405. https://doi.org/10.1017/s0033291702006943
Google Scholar
34.
Conner KR, Beautrais AL, Brent DA, Conwell Y, Phillips MR, Schneider B. The next generation of psychological autopsy studies: part 2. Interview procedures. Suicide Life‐Threat Behav. 2012;42(1):86–103. https://doi.org/10.1111/j.1943-278x.2011.00073.x
Google Scholar
35.
Seguin M, Beauchamp G, Notredame CE. Adversity over the life course: a comparison between women and men who died by suicide. Front Psychiatr. 2021;12(1249):682637. https://doi.org/10.3389/fpsyt.2021.682637
Google Scholar
36.
Coppersmith DDL, Dempsey W, Kleiman EM, Bentley KH, Murphy SA, Nock MK. Just‐in‐Time adaptive interventions for suicide prevention: promise, challenges, and future directions. Psychiatry. 2022;85(4):1–17. https://doi.org/10.1080/00332747.2022.2092828
Google Scholar

Information & Authors

Information

Published In

Go to Psychiatric Research and Clinical Practice
Psychiatric Research and Clinical Practice
Volume 5 • Number 1 • Spring 2023
Pages: 24 - 36

History

Received: 14 October 2022
Accepted: 1 November 2022
Published online: 13 January 2023
Published in print: Spring 2023

Authors

Details

Catherine L. Dempsey, Ph.D., MPH https://orcid.org/0000-0002-5712-6590
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
David M. Benedek, M.D.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
Kelly L. Zuromski, Ph.D.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
Matthew K. Nock, Ph.D.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
David A. Brent, M.D.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
Jingning Ao, MPH.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
Matthew W. Georg, MPH.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
Katy Haller, MSPH.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
Pablo A. Aliaga, M.S.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
Steven G. Heeringa, PhD.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
Ronald C. Kessler, Ph.D.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
Murray B. Stein, M.D., MPH.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author
Robert J. Ursano, M.D.
Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD (C. L. Dempsey, D. M. Benedek, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga, R. J. Ursano); Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD (C. L. Dempsey, J. Ao, M. W. Georg, K. Haller, P. A. Aliaga); Department of Psychology, Harvard University, Cambridge, MA (K. L. Zuromski, M. K. Nock); Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA (D. A. Brent); Institute for Social Research, University of Michigan, Ann Arbor, MI (S. G. Heeringa); Department of Health Care Policy, Harvard Medical School, Cambridge, MA (R. C. Kessler); Department of Psychiatry and Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA (M. B. Stein); VA San Diego Healthcare System, San Diego, CA (M. B. Stein)
View all articles by this author

Notes

Send correspondence to Dr. Dempsey ([email protected])

Funding Information

Henry M. Jackson Foundation for the Advancement of Military Medicine Inc
Department of Health and Human Services, NIMH: U01MH087981
U.S. Department of Defense: HU00011520004, HU0001202003

Metrics & Citations

Metrics

Citations

Export Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format
Citation style
Style
Copy to clipboard
Tips for downloading citations

View Options

View options

PDF/EPUB

View PDF/EPUB

Login options

Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.

Personal login Institutional Login Open Athens login

Not a subscriber?

Subscribe Now / Learn More

PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.

Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).

Media

Figures

Other

Tables

Share

Share

Share article link

Share

×

As described within the American Psychiatric Association (APA)'s Privacy Policy and Terms of Use, this website utilizes cookies, including for the purpose of offering an optimal online experience and services tailored to your preferences. Please read the entire Privacy Policy and Terms of Use. By closing this message, browsing this website, continuing the navigation, or otherwise continuing to use the APA's websites, you confirm that you understand and accept the terms of the Privacy Policy and Terms of Use, including the utilization of cookies.