Sample Characteristics and RDS Estimates of the Target Population
presents both the sample characteristics and the target population estimates calculated using RDSAT. The two sets of estimates quite often differed. High school graduates were underrepresented by 13% and unemployed and currently not in school veterans were under-represented by 18%. On the other hand, veterans who are currently enrolled in a degree program are overrepresented by 13% and those with higher income are over-represented by 11%. There are also differences between the two sets among items describing military experience: members of the reserves/guards were overrepresented by 12% (at the expense of Active Duty service members) and veterans who received General discharge were underrepresented by 8%.
Sample characteristics (N = 269) and RDS estimates of the target population
Most of the target population were male (88%), Black (70%), aged 19–29 (51%), only 5% were college graduates, more than half (53%) were unemployed and were not attending school, and only 20% had higher income. Most veterans were not living with a partner (87%), only 8% of them were married, and another 6% were cohabiting with an intimate partner, even though overall 26% of veterans were having an intimate relationship. Twenty-five percent of the target population was homeless after their return to civilian life.
With regard to the military history and experience, the majority served in the army (64%), were in Active Duty (90%), last served in Iraq (75%), and deployed only once (59%). Forty-five percent received honorable discharge. Six percent received other than honorable discharge (which included Bad Conduct and Dishonorable Discharge). also describes a range of combat experiences: feeling danger of being killed (62%), being under attack (68%), shooting at enemy (39%), killing enemy combatant (34%), and killing a noncombatant (8%). Nine percent were injured in combat and 20% were on disability at the time of the interview.
RDS Estimated Prevalence of Substance Use Across the Military-Veteran Life Course
shows the RDS estimated rates of substance use over the military/veteran life course, that is, before joining the military, in the military (excluding the last deployment), during the last deployment, and in the past 30 days. All three measures related to alcohol use (i.e., any alcohol, binge drinking, and heavy drinking) reveal the same pattern over time: compared to the time before joining the military, alcohol consumption increased in the military, then substantially decreased during the last deployment, and returned to the premilitary service levels after the separation from military. Cigarette smoking also substantially increased after joining the military, but in contrast to alcohol, the upward trend of smoking continued also during the last deployment and reached the peak in the past 30 days. The trajectory of marijuana use declined sharply on entering the military and continued the decline further while deployed. After separation, marijuana use increased but not to the level prior to military service. A similar, though much flatter, profile can be seen in the use of powder cocaine. Finally, whereas heroin use was uncommon over the life course, the illicit use of painkillers increased in every period.
RDS estimates of recreational substance use over the military/veteran life course
Estimated Prevalence Rates of Substance Use and Mental Health Problems
describes the prevalence of substance use and mental health problems in the target population. As shown in the table, the rate of AUD was 10% higher than the rate of DUD (28% vs. 18%). But since the rate of SUD (i.e., AUD or DUD or both) is only about 4% higher than the rate of AUD, it indicates that the majority of veterans with DUD (15%) also had AUD. The prevalence of PTSD, TBI, and MDD were each about 20%. However, not the same people were affected by these disorders: in fact, just 5% were affected by all three. The largest comorbidity group was between PTSD and MDD (11%), followed by PTSD and TBI (9%), and TBI and MDD (8%). Thirty-six percent of the sample suffered from any combination of these three mental disorders. The prevalence of the co-occurring SUD and mental health disorders was 18%. Finally, 48% of veterans met the criteria for either SUD or some other mental health disorder.
Substance use and mental health problems prevalence rates (RDS estimates)
Covariates of Substance Use and Mental Health Disorders Among Veterans
presents results of seven logistic regression analyses with individual as well as combined substance use or mental health disorders as dependent variables. The three groups of covariates that were tested included four demographic, three reintegration, and four military variables. Starting with AUD, the table shows that White veterans were six times more likely and Hispanics were four times more likely to have AUD than Black veterans. Higher level of education was related to lower prevalence of AUD: compared to veterans who did not continue studies after high school, those who had some college were only 30% as likely to have an AUD and those with the college degree were just 10% as likely to have an alcohol disorder.
Covariates of substance use and mental health disorders (logistic regression)
With regard to DUD, none of the covariates emerged as being significantly related to this disorder. This may be related to the fact that only a small number of veterans had DUD. However, when DUD was combined with AUD (see the SUD column), in addition to race/ethnicity and education that show a very similar pattern of results as discussed above in connection with AUD, a robust relationship with marital status was found. As opposed to married veterans, single veterans were 3.5 times more likely to have substance-use-related problems, whereas divorced, separated, and widowed veterans were up to six times more likely to have substance-use-related problems. Surprisingly, in contrast to marriage, cohabitation does not appear to be a protective factor against substance abuse. Cohabiting veterans were almost eight times more likely to have substance-use-related problems than married veterans.
The only gender difference observed was in the likelihood of meeting the PTSD criteria: women were almost three times more likely than men to screen positive for PTSD. Another significant covariate of PTSD is the number of deployments: whereas being deployed twice increased the risk of developing PTSD only slightly, veterans with three and more deployments had five times higher likelihood of having PTSD compared to those who deployed just once.
The largest number of significant covariates emerged for TBI. Compared to Black veterans, all other racial categories were more likely to meet criteria for TBI; specifically, Hispanic veterans were almost twice as likely to sustain TBI, followed by veterans of “other” race/ethnicity (OR=2.6), and White veterans who were over three times more likely to meet the TBI screening criteria. Veterans with a college degree had 10 times smaller likelihood of having TBI, which perhaps suggests that these veterans did not have as much combat exposure as those with lower educational status. As shown in the table, TBI was also related to employment—veterans with a job had only 10% likelihood of meeting TBI criteria. Clearly, in this case, a reverse causation can be inferred, since those who did not sustain brain injury are much more likely to be employed. On the other hand, we are unsure how to interpret the finding that veterans enrolled in a degree program were 2.4 times more likely to have TBI than those not currently in school or holding a job.
In the group of military-service-related variables, members of the Army from among all military branches had the highest likelihood of a probable TBI. Marines were only half as likely to meet TBI criteria, and the Navy and Air Force (combined with Coast Guard) had even smaller odds of sustaining a TBI. Similarly to what was seen for PTSD, veterans with three or more deployments were four times more likely to meet criteria for TBI.
With regard to MDD, Black veterans were the least likely to be depressed; in contrast, Hispanics appeared to have more than four times higher likelihood of meeting the screening criteria for MDD. Depression was also related to age—with higher age the likelihood for being depressed grew larger—and to education; the lower the education, the higher the odds of being depressed.
Finally, AMH disorder was significantly related to race/ethnicity, employment and/or study, and military component. As before, Black veterans were the least likely to develop a disorder, whereas veterans of other race/ethnicity (a group consisting of just 11 respondents) were the most susceptible to having some type of mental health issue. Following the pattern seen in the analysis of TBI, employed veterans were only 30% as likely to have any type of mental health concern, while those who were studying and not working appear to be more susceptible. Reservists and members of the National Guard were only half as likely to be diagnosed with a mental health disorder.
Estimated Prevalence of Met and Unmet Treatment Needs
depicts the RDS estimated rates of met and unmet treatment needs for SUDs and other mental health conditions among veterans. Note that in addition to the RDS percentage values shown within the bars in the figure, relative percentages of unmet treatment need are placed under each category label. These numbers are the subgroup percentages expressing the proportion of unmet treatment need among all those with a specific condition (the estimated prevalence rate of each condition is shown by the height of each bar).
Estimates of met and unmet treatment need for SUD and mental health disorders among veterans (numbers below the category labels show the relative percentage of unmet need).
The figure shows that 4% of all veterans received treatment for AUD, while 24% of veterans had their AUD treatment need unmet. In other words, 84% of all veterans with AUD did not receive treatment they needed. In contrast, the estimated rate of treated DUD amounts to more than a half of all veterans with DUD. The third bar shows that 13% of veterans received treatment for at least one of their alcohol/drug disorders and 19% of veterans had none of their treatment needs met. This latter group represents 60% of veterans with an SUD.
Next, the figure shows that the prevalence rates for PTSD, TBI, and depression were very similar, around 19%–21%, although the treatment rates for these conditions vastly differed. Almost two thirds of veterans with PTSD received treatment while the remaining 35% did not. This represents the highest treatment rate for any given condition. In sharp contrast, 91% of all those who screened positive for TBI did not have their treatment need met. RDS estimated that of all veterans, only 2% received treatment for TBI, which represents just 9% of veterans with the condition. Even though the RDS estimated prevalence rate of MDD is virtually identical with the rate of PTSD, the proportion of treated to untreated depressed veterans was exactly the opposite of what was seen for PTSD.
Finally, combining all three disorders illustrates that almost 36% of all veterans manifested one or more of these mental health conditions. Almost 15% of all veterans received some treatment but over 20% of veterans received no treatment. This number translates to 58% unmet treatment need rate for any of the three mental health concerns. This proportion of unmet need appears to be almost the same as the one for SUD. Thus, for both groups of disorders, only about 40% of veterans in need received some form of treatment.