Factors associated with racial and ethnic disparities in chronic pain after acute traumatic injury.

BACKGROUND: Chronic pain represents a substantial health burden and source of disability following traumatic injury. This study investigates factors associated with racial and ethnic disparities in chronic pain. METHODS: Prospective, longitudinal, panel study. Seriously injured patients were recruited from two trauma centres in the Northeastern and Southwestern USA. Data from medical records and individual surveys were collected in-hospital, and at 3-month and 12-month postinjury from a balanced cohort of non-Hispanic black, non-Hispanic white and Hispanic patients. We used linear regression to estimate the associations between race and ethnicity and 3-month and 12-month pain severity outcomes. We grouped all available cohort data on factors that theoretically influence the emergence of chronic pain after injury into five temporally ordered clusters and entered each cluster sequentially into regression models. These included: participant race and ethnicity, other demographic characteristics, preinjury health characteristics, acute injury characteristics and postinjury treatment. RESULTS: 650 participants enrolled (Hispanic 25.6%; white 38.1%; black 33.4%). Black participants reported highest relative chronic pain severity. Injury-related factors at the time of acute hospitalisation (injury severity, mechanism, baseline pain and length of stay) were most strongly associated with racial and ethnic disparities in chronic pain outcomes. After controlling for all available explanatory factors, a substantial proportion of the racial and ethnic disparities in chronic pain outcomes remained. CONCLUSION: Racial and ethnic disparities in chronic pain outcomes may be most influenced by differences in the characteristics of acute injuries, when compared with demographic characteristics and postacute treatment in the year after hospitalisation.

Predictors of Long-Term Opioid Use After Hospitalization for Traumatic Injury in a Racially and Ethnically Diverse Population: A 12-Month Prospective Observational Study.

BACKGROUND: Long-term prescription opioid use is a significant risk factor for opioid morbidity and mortality, and severe traumatic injury is an important initiation point for prescription opioid use. This study examines predictors of long-term prescription opioid use among a racially and ethnically diverse population of patients hospitalized for traumatic injury. METHODS: Study participants (N= 650) from two urban Level I trauma centers were enrolled. Baseline information on demographics, injury characteristics, self-reported pre-injury substance use and mental health, and personality characteristics and attitudes was collected through interviews during the initial hospitalization. Patients were interviewed again at 3 months and 12 months and asked about prescription opioid use in the prior 7 days. Multivariable logistic regressions assessed participants' baseline characteristics associated with opioid use at one or more follow-up interviews. RESULTS: Pre-injury use of prescription painkillers had the strongest association with prescription opioid use at follow-up (adjusted odds ratio: 3.10; 95% confidence interval: 1.86-5.17). Older age, health insurance coverage at baseline, length of hospitalization, higher current pain level, pre-injury post-traumatic stress disorder symptoms, and discharge to a location other than home were also associated with significantly higher odds of prescription opioid use at follow-up. CONCLUSIONS: Providers could consider screening for past use of prescription pain relievers and post-traumatic stress disorder before hospital discharge to identify patients who might benefit from additional resources and support. However, providers should ensure that these patients' pain management needs are still being met and avoid abrupt discontinuation of prescription opioid use among those with a history of long-term use.

Changes in firearm mortality following the implementation of state laws regulating firearm access and use.

Although 39,000 individuals die annually from gunshots in the US, research examining the effects of laws designed to reduce these deaths has sometimes produced inconclusive or contradictory findings. We evaluated the effects on total firearm-related deaths of three classes of gun laws: child access prevention (CAP), right-to-carry (RTC), and stand your ground (SYG) laws. The analyses exploit changes in these state-level policies from 1970 to 2016, using Bayesian methods and a modeling approach that addresses several methodological limitations of prior gun policy evaluations. CAP laws showed the strongest evidence of an association with firearm-related death rate, with a probability of 0.97 that the death rate declined at 6 y after implementation. In contrast, the probability of being associated with an increase in firearm-related deaths was 0.87 for RTC laws and 0.77 for SYG laws. The joint effects of these laws indicate that the restrictive gun policy regime (having a CAP law without an RTC or SYG law) has a 0.98 probability of being associated with a reduction in firearm-related deaths relative to the permissive policy regime. This estimated effect corresponds to an 11% reduction in firearm-related deaths relative to the permissive legal regime. Our findings suggest that a small but meaningful decrease in firearm-related deaths may be associated with the implementation of more restrictive gun policies.

Moving beyond the classic difference-in-differences model: a simulation study comparing statistical methods for estimating effectiveness of state-level policies.

BACKGROUND: Reliable evaluations of state-level policies are essential for identifying effective policies and informing policymakers' decisions. State-level policy evaluations commonly use a difference-in-differences (DID) study design; yet within this framework, statistical model specification varies notably across studies. More guidance is needed about which set of statistical models perform best when estimating how state-level policies affect outcomes. METHODS: Motivated by applied state-level opioid policy evaluations, we implemented an extensive simulation study to compare the statistical performance of multiple variations of the two-way fixed effect models traditionally used for DID under a range of simulation conditions. We also explored the performance of autoregressive (AR) and GEE models. We simulated policy effects on annual state-level opioid mortality rates and assessed statistical performance using various metrics, including directional bias, magnitude bias, and root mean squared error. We also reported Type I error rates and the rate of correctly rejecting the null hypothesis (e.g., power), given the prevalence of frequentist null hypothesis significance testing in the applied literature. RESULTS: Most linear models resulted in minimal bias. However, non-linear models and population-weighted versions of classic linear two-way fixed effect and linear GEE models yielded considerable bias (60 to 160%). Further, root mean square error was minimized by linear AR models when we examined crude mortality rates and by negative binomial models when we examined raw death counts. In the context of frequentist hypothesis testing, many models yielded high Type I error rates and very low rates of correctly rejecting the null hypothesis (< 10%), raising concerns of spurious conclusions about policy effectiveness in the opioid literature. When considering performance across models, the linear AR models were optimal in terms of directional bias, root mean squared error, Type I error, and correct rejection rates. CONCLUSIONS: The findings highlight notable limitations of commonly used statistical models for DID designs, which are widely used in opioid policy studies and in state policy evaluations more broadly. In contrast, the optimal model we identified--the AR model--is rarely used in state policy evaluation. We urge applied researchers to move beyond the classic DID paradigm and adopt use of AR models.

Impact on Nonfirearm Deaths of Firearm Laws Affecting Firearm Deaths: A Systematic Review and Meta-Analysis.

Background. There is debate whether policies that reduce firearm suicides or homicides are offset by increases in non-firearm-related deaths.Objectives. To assess the extent to which changes in firearm homicides and suicides following implementation of various gun laws affect nonfirearm homicides and suicides.Search Methods. We performed a literature search on 13 databases for studies published between 1995 and October 31, 2018 (PROSPERO CRD42019120105).Selection Criteria. We included studies if they (1) estimated an effect of 1 of 18 included classes of gun policy on firearm homicides or suicides, (2) included a control group or comparison group and evaluated time series data to establish that policies preceded their purported effects, and (3) provided estimated effects of the policy and inferential statistics for either total or nonfirearm homicides or suicides.Data Collection and Analysis. We extracted data from each study, including study timeframe, population, and statistical methods, as well as point estimates and inferential statistics for the effects of firearm policies on firearm deaths as well as either nonfirearm or overall deaths. We assessed quality at the estimate (study-policy-outcome) level by using prespecified criteria to evaluate the validity of inference and causal identification. For each estimate, we derived the mortality multiplier (i.e., the ratio of the policy's effect on total homicides or suicides; expressed as a change in the number of deaths) as a proportion of its effect on firearm homicides or suicides. Finally, we performed a meta-analysis to estimate overall mortality multipliers for suicide and homicide that account for both within- and between-study heterogeneity.Main Results. We identified 16 eligible studies (study timeframes spanning 1977-2015). All examined state-level policies in the United States, with most estimating effects of multiple policies, yielding 60 separate estimates of the mortality multiplier. From these, we estimated that a firearm law's effect on homicide, expressed as a change in the number of total homicide deaths, is 0.99 (95% confidence interval = 0.76, 1.22) times its effect on the number of firearm homicides. Thus, on average, changes in the number of firearm homicides caused by gun policies are neither offset nor compounded by second-order effects on nonfirearm homicides. There is insufficient evidence in the existing literature on suicide to indicate the extent to which the effects of gun policy changes on firearm suicides are offset or compounded by their effects on nonfirearm suicides.Authors' Conclusions. State gun policies that reduce firearm homicides are likely to reduce overall homicides in the state by approximately the same number. It is currently unknown whether the same holds for state gun policies that significantly reduce firearm suicides. The small number of studies meeting our inclusion criteria, issues of methodological quality within those studies, and the possibility of reporting bias are potential limitations of this review.Public Health Implications. Policies that reduce firearm homicides likely have large benefits for public health as there is little evidence to support a strong substitution effect between firearm and nonfirearm homicides at the population level. Further research is needed to determine whether policies that produce population-level reductions in firearm suicides will translate to overall declines in suicide rates.

With Small Power, Comes Great Responsibility: Lessons Learned from an Evaluation of Veteran and Military Mental Health Public Awareness Campaigns.

This study was conducted to determine the feasibility of conducting a cost-benefit evaluation of federally-funded media campaigns encouraging mental health help-seeking among United States military personnel and veterans. To calculate the necessary sample size for the evaluation, we obtained campaign costs, and determined the number of treatment seekers needed for the campaign to break even with its cost and the associated population change that an evaluation would need to detect. The sample size needed for an evaluation with 80% power was greater than the total population of U.S. military personnel and veterans. Given that the necessary sample size exceeds the population to be sampled, an appropriately powered outcome evaluation is not feasible. Other programs that would be cost effective with extremely small effect sizes should not be subject to underpowered and thus inaccurate empirical outcome evaluation.

Geographic and Demographic Differences in the Proportion of Individuals Living in Households With a Firearm, 1990-2018.

Importance: Measures of the proportion of individuals living in households with a firearm (HFR), over time, across states, and by demographic groups are needed to evaluate disparities in firearm violence and the effects of firearm policies. Objective: To estimate HFR across states, years, and demographic groups in the US. Design, Setting, and Participants: In this survey study, substate HFR totals from 1990 to 2018 were estimated using bayesian multilevel regression with poststratification to analyze survey data on HFR from the Behavioral Risk Factor Surveillance System and the General Social Survey. HFR was estimated for 16 substate demographic groups defined by gender, race, marital status, and urbanicity in each state and year. Exposures: Survey responses indicating household firearm ownership were analyzed and compared with a common proxy for firearm ownership, the fraction of suicides completed with a firearm (FSS). Main Outcome and Measure: HFR, FSS, and their correlations and differences. Results: Among US adults in 2018, HFR was significantly higher among married, nonurban, non-Hispanic White and American Indian male individuals (65.0%; 95% credible interval [CI], 61.5%-68.7%) compared with their unmarried, urban, female counterparts from other racial and ethnic groups (7.3%; 95% CIs, 6.0%-9.2%). Marginal HFR rates for larger demographic groups also revealed important differences, with racial minority groups and urban dwellers having less than half the HFR of either White and American Indian (39.5%; 95% CI, 37.4%-42.9% vs 17.2%; 95% CI, 15.5%-19.9%) or nonurban populations (46.0%; 95% CI, 43.8%-49.5% vs 23.1%; 95% CI, 21.3%-26.2%). Population growth among groups less likely to own firearms, rather than changes in ownership within demographic groups, explains 30% of the 7 percentage point decline in HFR nationally from 1990 to 2018. Comparing HFR estimates with FSS revealed the expected high overall correlation across states (r = 0.84), but scaled FSS differed from HFR by as many as 20 percentage points for some states and demographic groups. Conclusions and Relevance: This survey study of HFR providing detailed, publicly available HFR estimates highlights key disparities among individuals in households with firearms across states and demographic groups; it also identifies potential biases in the use of FSS as a proxy for firearm ownership rates. These findings are essential for researchers, policymakers, and public health experts looking to address geographic and demographic disparities in firearm violence.

Household Firearm Ownership and Firearm Mortality.

Importance: Causal associations between household firearm ownership rates (HFRs) and firearm mortality rates are not well understood. Objective: To assess the population-level temporal sequencing of firearm death rates and HFRs. Design, Setting, and Participants: This cohort study used autoregressive cross-lagged models to analyze HFRs, firearm suicide rates, and firearm homicide rates in the US from 1990 to 2018. The suicide analyses included 16 demographic subgroups of adults, defined by study year, state, sex, race and ethnicity, marital status, and urbanicity. The homicide analyses consisted of adult subgroups living in urban or rural areas. Data analysis was conducted from March to December 2023. Exposures: Firearm mortality rates and HFRs. Main Outcomes and Measures: Firearm homicide and suicide rates with HFRs as the exposure, and HFR with mortality as the exposure. Results: A total of 10 416 observations of 16 demographic subgroups by state and 2-year periods were included in the suicide analyses, while 1302 observations from 2 demographic subgroups by state and 2-year period were included in the homicide analysis. At baseline, the mean (SD) rate per 100 000 population across strata was 7.46 (7.21) for firearm suicides and 3.32 (2.13) for firearm homicides. The mean (SD) baseline HFR was 36.9% (20.2%) for firearm suicides and 36.9% (14.8%) for firearm homicides. Higher HFR preceded increases in suicide rates: demographic strata with equal firearm suicide rates but which differ by 18.6 percentage points on HFR (1 SD) would be expected to have firearm suicide rates that diverged by 0.19 (95% CI, 0.15-0.23) deaths per 100 000 population per period. With these differences accumulated over 8 years, firearm suicide rates in subgroups with the highest decile HFR would be expected to have 1.93 (95% CI, 1.64-2.36) more suicides per 100 000 population than strata with lowest decile HFR, a difference of 25.7% of the overall firearm suicide rate in 2018 and 2019. Firearm suicide rates had a smaller magnitude of association with subsequent changes in HFR: strata with equal HFRs but which differ by 1 SD in firearm suicide rates had minimal subsequent change in HFRs (-0.02 [95% CI, -0.04 to 0.01] percentage points). A 1-SD difference in HFRs was associated with little difference in next-period overall firearm homicides rates (0.03 [95% CI, -0.02 to 0.08] per 100 000 population), but a 1-SD difference in homicide rates was associated with a decrease in HFR (-0.09 [95% CI, -0.16 to -0.04] percentage points). Conclusions and Relevance: This cohort study found an association between high HFRs and subsequent increases in rates of firearm suicide. In contrast, higher firearm homicide rates preceded decreases in HFRs. By demonstrating the temporal sequencing of firearm ownership and mortality, this study may help to rule out some theories of why gun ownership and firearm mortality are associated at the population level.

Relationships of State Alcohol Policy Environments With Homicides and Suicides.

INTRODUCTION: Alcohol use is involved in a large proportion of homicides and suicides each year in the U.S., but there is limited evidence on how policies targeting alcohol influence violence in the U.S. CONTEXT: Extant studies generally focus on individual policies in isolation of each other. This study examines the impacts of changes in states' alcohol policy restrictions on overall homicide and suicide rates and firearm-related homicide and suicide rates using a holistic measure of states' alcohol policy environments. METHODS: Using a composite measure of state-level alcohol policies (Alcohol Policy Scale) and data from the National Vital Statistics System from 2002 to 2018, this study applied a Bayesian time series model to estimate the impacts of alcohol policy changes on overall and firearm-involved homicide and suicide rates. The analysis was performed in 2023 and 2024. RESULTS: A 1 SD change in the Alcohol Policy Scale was associated with a 6% decline in homicide rates both overall (incident rate ratio=0.94; 95% credible interval = 0.89, 1.00) and for firearm homicides specifically (incident rate ratio=0.94, 95% CI=0.88, 1.01). There was no clear association of alcohol policy with suicides. The model predicts that a nationwide increase in alcohol restrictions equivalent to a shift from the 25th to 75th percentile of the scale's distribution would result in almost 1,200 fewer homicides annually. CONCLUSIONS: Increases in the restrictiveness of state-level alcohol policies are associated with reductions in homicides. More restrictive alcohol policy environments may offer an opportunity to reduce homicides.

State Policies Regulating Firearms and Changes in Firearm Mortality.

Importance: Despite high social and public health costs of firearm violence in the United States, the effects of many policies designed to reduce firearm mortality remain uncertain. Objective: To estimate the individual and joint effect sizes of state firearm policies on firearm-related mortality. Design, Setting, and Participants: In this comparative effectiveness study, bayesian methods were used to model panel data of annual, state-level mortality rates (1979-2019) for all US firearm decedents, with analyses conducted in October 2023. Exposures: Six classes of firearms policies: background checks, minimum age, waiting periods, child access, concealed carry, and stand-your-ground laws. Main Outcome and Measures: Primary outcomes (total firearm deaths, firearm homicide deaths, and firearm suicide deaths) were assessed using the National Vital Statistics System. Bayesian estimation was used to estimate the partial association of changes in firearms policies with subsequent changes in firearm mortality. Results: The estimated effect sizes of individual policies 5 or more years after implementation were generally small in magnitude and had considerable uncertainty. The policy class with the highest probability of reducing firearm deaths was child-access prevention laws, estimated to reduce overall firearm mortality by 6% (80% credible interval [CrI], -2% to -9%). The policy class with the highest probability of increasing firearm deaths was stand-your-ground laws, estimated to increase firearm homicides by 6% (80% CrI, 0% to 13% increase). Estimates of association of implementing multiple firearm restrictions with subsequent changes in firearm mortality yielded larger effect sizes. Moving from the most permissive to most restrictive set of firearm policies was associated with an estimated 20% reduction in firearm deaths (80% CrI, 10% to 28% reduction), with a 0.99 probability of any reductions in firearm death rates. Conclusions and Relevance: In this comparative effectiveness study of state firearm policies, the joint effect estimates of combinations of firearm laws were calculated, showing that restrictive firearm policies were associated with substantial reductions in firearm mortality. Although policymakers would benefit from knowing the effects of individual policies, the estimated changes in firearm mortality following implementation of individual policies were often small and uncertain.

Effects of restricting alcohol sales on fatal violence: Evidence from Sunday sales bans.

INTRODUCTION: Homicides and suicides are the second- and third-leading causes of death among young people (aged 10-24) in the US. While a substantial share of these deaths involve alcohol, evidence is needed on whether specific alcohol policies, such as day-based sales restrictions, help prevent these deaths. METHODS: We constructed total and firearm-related homicide and suicide counts by state, year, and day-of-week from the Multiple Cause of Death Micro-data 1990-2019. Repeals of Sunday bans were taken from the Alcohol Policy Information System. Two-way fixed effects Poisson models with standard errors clustered at state-level and population offset control for state, year and day-of-the-week fixed effects and state time-varying covariates. RESULTS: Repealing Sunday bans is associated with an increase in homicides (IRR=1.125; 95% confidence interval [CI]:1.02-1.24) and firearm homicides (IRR=1.17; 95% CI:1.03-1.33). Analyses by day-of-the-week show significant associations with homicides not only on Sundays, but also other days, consistent with delays in death. There was no significant relationship for suicides. CONCLUSION: Restricting alcohol availability may prove a useful policy tool to reduce homicides, given that day-based restrictions are associated with changes in deaths rather than only shifting across days-of-the-week.

Gender Differences in Health Among U.S. Service Members: Unwanted Gender-Based Experiences as an Explanatory Factor.

Women serving in the U.S. military are more likely to report mental health problems than men, including symptoms of depression and posttraumatic stress disorder (PTSD). Women also experience much higher rates of sexual harassment, gender discrimination, and sexual assault than men. This study examines how unwanted gender-based experiences among military service members relate to differences in health. The authors find that, once experiences of gender discrimination, sexual harassment, and sexual assault are accounted for, gender differences in health are largely attenuated. That is, the vulnerability to physical and mental health problems among female service members appears to be highly correlated with these unwanted gender-based experiences. The results highlight the possible health benefits of improved prevention of gender discrimination, sexual harassment, and sexual assault, and they indicate the need to address the mental and physical health of service members exposed to these types of experiences.

Sexual Assault Experiences in the Active-Component Army: Variation by Year, Gender, Sexual Orientation, and Installation Risk Level.

To better understand the circumstances surrounding sexual assault in the Army, RAND Arroyo Center researchers created descriptions of active-component soldiers' most serious sexual assault experiences using data from the 2016 and 2018 Workplace and Gender Relations Survey of Active Duty Members. In this study, researchers describe the most common types of behaviors that occurred, characteristics of alleged perpetrators, and times and places in which the experiences occurred. They also explore differences by gender, sexual orientation, and installation risk level. Nearly 90 percent of victims believed that the assault was committed for a sexual reason, and more than half indicated that the assault was meant to be abusive or humiliating. The typical perpetrator of victims' most serious sexual assault experiences was a male enlisted member of the military acting alone. Perpetrators were most often a military peer of the victim; perpetrators who were strangers to the victim were uncommon; and assaults by spouses, significant others, or family members were comparatively rare. Approximately two-thirds of victims' most serious experience of sexual assault occurred at a military installation. The authors found substantial differences by gender, especially in terms of the types of sexual assault behaviors victims experienced and in terms of the setting in which victims were sexually assaulted. The authors also found some evidence suggesting that sexual minorities-that is, individuals who identify with a sexual orientation other than heterosexual-may experience more-violent sexual assaults and more assaults that are meant to abuse, humiliate, haze, or bully, especially among men.

Racial and ethnic differences in the effects of state firearm laws: a systematic review subgroup analysis.

BACKGROUND: Despite growing evidence about how state-level firearm regulations affect overall rates of injury and death, little is known about whether potential harms or benefits of firearm laws are evenly distributed across demographic subgroups. In this systematic review, we synthesized available evidence on the extent to which firearm policies produce differential effects by race and ethnicity on injury, recreational or defensive gun use, and gun ownership or purchasing behaviors. MAIN BODY: We searched 13 databases for English-language studies published between 1995 and February 28, 2023 that estimated a relationship between firearm policy in the USA and one of eight outcomes, included a comparison group, evaluated time series data, and provided estimated policy effects differentiated by race or ethnicity. We used pre-specified criteria to evaluate the quality of inference and causal effect identification. By policy and outcome, we compared policy effects across studies and across racial/ethnic groups using two different ways to express effect sizes: incidence rate ratios (IRRs) and rate differences. Of 182 studies that used quasi-experimental methods to evaluate firearm policy effects, only 15 estimated policy effects differentiated by race or ethnicity. These 15 eligible studies provided 57 separate policy effect comparisons across race/ethnicity, 51 of which evaluated interpersonal violence. In IRR terms, there was little consistent evidence that policies produced significantly different effects for different racial/ethnic groups. However, because of different baseline homicide rates, similar relative effects for some policies (e.g., universal background checks) translated into significantly greater absolute differences in homicide rates among Black compared to white victims. CONCLUSIONS: The current literature does not support strong conclusions about whether state firearm policies differentially benefit or harm particular racial/ethnic groups. This largely reflects limited attention to these questions in the literature and challenges with detecting such effects given existing data availability and statistical power. Findings also emphasize the need for additional rigorous research that adopts a more explicit focus on testing for racial differences in firearm policy effects and that assesses the quality of race/ethnicity information in firearm injury and crime datasets.

Development of a Brief Version of the Dissociative Symptoms Scale and the Reliability and Validity of DSS-B Scores in Diverse Clinical and Community Samples.

The Dissociative Symptoms Scale (DSS) was developed to assess moderately severe types of dissociation (depersonalization, derealization, gaps in awareness and memory, and dissociative reexperiencing) that would be relevant to a range of clinical populations, including those experiencing trauma-related dissociation. The current study used data from 10 ethnically and racially diverse clinical and community samples (N = 3,879) to develop a brief version of the DSS (DSS-B). Item information curves were examined to identify items with the most precision in measuring above average levels of the latent trait within each subscale. Analyses revealed that the DSS-B preserved the factor structure and content domains of the full scale, and its scores had strong reliability and validity that were comparable to those of scores on the full measure. DSS-B scores showed high levels of measurement invariance across ethnoracial groups. Results indicate that DSS-B scores are reliable and valid in the populations studied.

Symptoms of Depression and Posttraumatic Stress Disorder as Predictors of Separation from the U.S. Military.

Populations affected by psychological distress are at risk of adverse career outcomes. The authors use data from the 2014 RAND Military Workplace Study and administrative personnel records of 17,502 U.S. military service members from 2014 to 2016 to evaluate the relationship between self-reported symptoms of depression and posttraumatic stress disorder (PTSD) in the U.S. military and subsequent service member separation rates. The authors find that self-reported symptoms of depression and PTSD were significantly associated with the odds of service member separation from the U.S. military. The odds that service members with symptoms suggestive of depressive disorders would separate from the military within the next 28 months were 2.62 times greater than the odds of service members with no symptoms of depression (95-percent confidence interval [CI] = 2.12, 3.22). Also, the odds that service members who reported symptoms of PTSD would separate from the military were 2.14 times greater than the odds of service members with no such symptoms (CI = 1.82, 2.51). The study's findings suggest that depression and PTSD symptoms, including subclinical symptoms, are related to subsequent separation from the military. Addressing mental-health needs could reduce negative employment outcomes that are costly for both the military and individual service members.