Prospective Association of Unmet Mental Health Treatment Needs With Suicidal Behavior Among Combat-Deployed Soldiers
Abstract
Objective:
Military personnel frequently report discontinuing or not pursuing psychiatric treatment despite perceiving a need for services. This study aimed to examine how unmet need for treatment or support among U.S. Army soldiers relates to future suicidal ideation (SI) or suicide attempt (SA).
Methods:
Mental health treatment need and help seeking in the past 12 months were evaluated for soldiers (N=4,645) who subsequently deployed to Afghanistan. Weighted logistic regression models were used to examine the prospective association of predeployment treatment needs with SI and SA during and after deployment, with adjustment for potential confounders.
Results:
Compared with soldiers without predeployment treatment needs, those who reported not seeking help despite needing it had increased risk for SI during deployment (adjusted OR [AOR]=1.73), past-30-day SI at 2–3 months postdeployment (AOR=2.08), past-30-day SI at 8–9 months postdeployment (AOR=2.01), and SA through 8–9 months postdeployment (AOR=3.65). Soldiers who sought help and stopped treatment without improvement had elevated SI risk at 2–3 months postdeployment (AOR=2.35). Those who sought help and stopped after improving did not have increased SI risk during or 2–3 months after deployment but had elevated risks for SI (AOR=1.71) and SA (AOR=3.43) by 8–9 months postdeployment. Risks for all suicidality outcomes were also elevated among soldiers who reported receiving ongoing treatment before deployment.
Conclusions:
Unmet or ongoing needs for mental health treatment or support before deployment are associated with increased risk for suicidal behavior during and after deployment. Detecting and addressing treatment needs among soldiers before deployment may help prevent suicidality during deployment and reintegration periods.
HIGHLIGHTS
•
This study examined how unmet predeployment mental health treatment need relates to future suicidal ideation (SI) or suicide attempt (SA) among U.S. Army soldiers.
•
Soldiers reporting an unmet or ongoing treatment need before deployment to Afghanistan had elevated SI and SA risk during and through at least 8–9 months after deployment.
•
Soldiers reporting successfully met treatment needs before deployment did not have elevated SI risk through 2–3 months after deployment but displayed elevated SI and SA risk by 8–9 months postdeployment.
•
An exploratory analysis of soldiers reporting unmet treatment needs did not reveal a significant relationship between specific treatment barriers and future SI.
Although the suicide rate in the U.S. military has been historically below that of the civilian population, it has increased dramatically since 2002 (1). From 2013 to 2018, the incidence of suicide deaths increased from 18.5 to 24.8 per 100,000 service members and is now comparable to that of the civilian population, when adjusted for age and sex (1). Studies such as the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) (2) have begun elucidating risk factors for suicidal behavior among military personnel (3–5); however, the role of unmet need for mental health treatment or support (defined here as not receiving help for mental health problems despite perceiving a need for it) (6, 7) in subsequent suicide outcomes has yet to be investigated.
Understanding the potential impact of unmet need is important, given evidence that service members perceive numerous barriers to mental health treatment, particularly attitudinal barriers (e.g., wanting to solve problems by themselves) and structural barriers (e.g., treatment access issues) (8–15). Furthermore, soldiers with unmet needs may be especially vulnerable to mental health deterioration when confronted with stressors, such as those associated with deployment and postdeployment reintegration (16). In severe cases, such deterioration could lead to the onset of suicidal thoughts or a suicide attempt (SA) (17, 18).
The Army STARRS Pre-Post Deployment Study (PPDS) provides an opportunity to assess the association between predeployment treatment or support needs and future suicidal ideation (SI) and SA. The present analysis of PPDS data builds on evidence from previous cross-sectional investigations by evaluating the prospective association of unmet need with SI and SA, while adjusting for other risk factors, such as lifetime history of SI or SA and severity of deployment stress (19, 20). We hypothesized that an unmet need for mental health treatment or support before deployment would be associated with increased risk for SI and SA during and after deployment. We expected these effects to be more robust for perideployment outcomes than for more distal postdeployment outcomes. Finally, we explored relationships between specific treatment barriers and suicidality to determine whether soldiers’ reports of certain barriers may help identify those at particularly heightened risk.
Methods
Overview and Participants
The PPDS is a prospective, multiwave panel survey of three U.S. Army brigade combat teams (BCTs) (21). Baseline (T0) evaluation occurred 1–2 months before the BCTs deployed to Afghanistan in 2012 (average deployment=10 months), with follow-up assessments at 2–3 weeks (T1), 2–3 months (T2), and 8–9 months (T3) postdeployment. Soldiers provided written informed consent to participate, and the study was approved by the institutional review boards (IRBs) of the collaborating institutions, including the Uniformed Services University of the Health Sciences (the primary grantee) and the Institute for Social Research at the University of Michigan (the organization implementing all Army STARRS surveys). Further details regarding IRB approval and other PPDS methods are described elsewhere (2, 22, 23).
At the predeployment baseline, 9,949 soldiers were present for duty in the BCTs, with 8,558 completing the T0 survey and consenting to a linkage between their survey data and Army and U.S. Department of Defense administrative records. The sample for this study included soldiers who then deployed to Afghanistan and completed all follow-up assessments (N=4,645). Response propensity and poststratification weights that were developed to analyze data from this sample were applied in all multiwave data analyses (24).
Measures
Predeployment need for mental health treatment or support.
The T0 survey assessed respondents’ perceived need to “see a professional or go to a self-help or support group because of problems with [their] emotions, nerves, mental health, behavior, or substance use” during the preceding year. Participants were also asked yes-or-no questions assessing whether they sought resources such as physicians, clergy, and self-help groups. (A comprehensive list of treatment and support types is available in the online supplement to this article.) For participants who reported using and subsequently discontinuing at least one of these resources to address their problems, another item assessed the extent to which an improvement in the problem was an important reason for stopping. Responses to this item were coded to reflect endorsement of improvement as at least a “somewhat important” reason for discontinuation.
On the basis of these responses, we created a categorical variable for treatment or support need (0=did not perceive need for treatment or support in past year, 1=perceived a need for treatment or support and sought and remained in treatment or support at T0, 2=perceived a need for treatment or support and sought and discontinued all forms of treatment or support after improvement, 3=perceived a need for treatment or support and did not seek help, and 4=perceived a need for treatment or support and sought and discontinued all forms of treatment or support without improvement).
Suicidality outcomes.
The outcomes of SI during deployment, at T2, and at T3 were based on T2 and T3 survey responses. SI during deployment was defined as a response of at least “a little of the time” when asked about having “thoughts of killing yourself” or “wishing you were dead” anytime during the recent deployment. Analogous questions assessed SI in the 30 days before the T2 survey (SI at T2) and the T3 survey (SI at T3). A binary variable was created for each SI outcome (0=“none of the time” to both items and 1=at least “a little of the time” to either item).
SA during deployment was assessed at T2 and defined as an affirmative response to the question, “Did you make a suicide attempt (i.e., purposefully hurt yourself with at least some intention to die) at any time during your recent deployment?” Analogous questions assessed SA since returning from deployment (at T2) and since the last survey (at T3). Reports of SA during deployment (N=5) and within 2–3 months of returning from deployment (N=6) were rare, precluding us from fitting models of SA at these time points. Instead, we fit one model to evaluate the association of predeployment need for treatment or support with any SA during or after deployment, through T3. A binary variable was created for suicide attempt (0=no SA reported during or after deployment and 1=SA reported either during or after deployment).
Barriers to mental health treatment or support.
T0 respondents who reported not seeking treatment or support despite needing it were asked to rate the extent to which each of 13 barriers was an important reason they did not seek treatment or support. Responses were discretized, with “yes” corresponding to endorsing the reason as at least “somewhat important” for the respondent.
Deployment stress.
Sixteen T1 survey items assessed the frequency of stressful deployment experiences (e.g., combat patrols and unit deaths). Item-level data were recoded as binary responses (0=never or missing and 1=at least once), and a deployment stress score was derived by summing the positive responses (range 0–16) (25, 26).
Data Analysis
Weight-adjusted logistic regression models were generated for each of the four outcomes: SI during deployment, 30-day SI at T2, 30-day SI at T3, and SA anytime during or after deployment, with predeployment treatment or support need as an explanatory variable. To address potential confounders, participants’ age, sex, marital status (never, previously, or currently married), race-ethnicity (Hispanic, non-Hispanic White, non-Hispanic Black, or other), education level (GED, high school diploma, or college degree), and deployment stress were incorporated into each model. For models of SI outcomes, predeployment lifetime SI was also included as a covariate. For the SA model, a three-level lifetime (T0) suicidality variable was used as a covariate (0=no lifetime SI or SA, 1=lifetime SI without SA, and 2=lifetime SA). For the treatment barrier analysis, Fisher’s exact tests were performed to assess the association of each of the 13 barriers with each SI outcome. A Bonferroni correction was applied by using α=0.05 to obtain a critical p<0.0038 for each of the 13 tests. All analyses were performed with Stata SE, version 17.
Results
Sample Characteristics at Predeployment Baseline
Most study participants in the sample were men (N=4,358, 94%), and the mean±SD age was 26.3±6.1 years. Fifty-five percent (N=2,561) of the participants were married, 36% (N=1,684) never married, and 8% (N=375) divorced, separated, or widowed. The sample was 63% (N=2,921) non-Hispanic White, 15% (N=702) Hispanic, 10% (N=451) non-Hispanic Black, 4% (N=173) Asian, 2% (N=70) Pacific Islander, 1% (N=49) American Indian, 4% (N=195) more than one race, and 1% (N=44) of other race-ethnicity. Overall, 6% (N=289) of participants had a GED, 72% (N=3,345) a high school diploma, and 21% (N=987) a college degree. The mean deployment stress score was 4.8±2.7. Lifetime SI without SA was reported by 449 (10%) soldiers and lifetime SA by 76 (2%) soldiers.
At predeployment, 3,621 (78%) reported no past-year need for mental health treatment or support, 217 (5%) reported ongoing treatment or support, 349 (8%) reported pursuing treatment or support and stopping all treatment after their problem improved, 235 (5%) reported not seeking treatment or support despite perceived need, and 167 (4%) reported pursuing treatment or support and stopping all treatment without improvement of their problem.
Among the 733 (16%) soldiers who sought help, 336 (46%) reported receiving treatment only from a medical or mental health professional (e.g., psychiatrist, other medical doctor, psychologist, counselor, or social worker) (21), 207 (28%) only from a support group or spiritual adviser, and 190 (26%) from both professional and nonprofessional sources.
Association of Predeployment Need for Treatment or Support With Suicidality Outcomes
Table 1 shows the number of soldiers reporting SI during deployment, past-30-day SI at T2, past-30-day SI at T3, and SA during or after deployment, stratified by predeployment need for treatment or support. (For stratification by the type of treatment or support reported, see the online supplement .)
| Reported SI | |||||
|---|---|---|---|---|---|
| Treatment or support group | N | % | AORb | 95% CI | p |
| SI during deployment (N=4,361c) | |||||
| No need for treatment or support reported (reference) | 216 | 6 | |||
| In ongoing treatment or received support at T0 | 28 | 14 | 1.78 | 1.13–2.79 | .014* |
| Stopped treatment or support after improvement | 25 | 7 | .83 | .51–1.36 | .458 |
| Perceived need, did not seek care | 34 | 15 | 1.73 | 1.02–2.93 | .043* |
| Stopped treatment or support without improvement | 20 | 13 | 1.54 | .94–2.55 | .087 |
| Total | 323 | 7 | |||
| 30-day SI at T2 (N=4,333c) | |||||
| No need for treatment or support reported (reference) | 70 | 2 | |||
| In ongoing treatment or received support at T0 | 14 | 7 | 2.51 | 1.18–5.34 | .018* |
| Stopped treatment or support after improvement | 17 | 5 | 1.67 | .74–3.77 | .213 |
| Perceived need, did not seek care | 16 | 7 | 2.08 | 1.18–3.67 | .013* |
| Stopped treatment or support without improvement | 10 | 6 | 2.35 | 1.17–4.74 | .018* |
| Total | 127 | 3 | |||
| 30-day SI at T3 (N=4,278c) | |||||
| No need for treatment or support reported (reference) | 106 | 3 | |||
| In ongoing treatment or received support at T0 | 19 | 9 | 2.75 | 1.58–4.81 | .001* |
| Stopped treatment or support after improvement | 25 | 8 | 1.71 | 1.03–2.85 | .038* |
| Perceived need, did not seek care | 19 | 9 | 2.01 | 1.16–3.48 | .014* |
| Stopped treatment or support without improvement | 7 | 5 | 1.26 | .54–2.92 | .579 |
| Total | 176 | 4 | |||
| SA during or after deployment (N=4,374c) | |||||
|---|---|---|---|---|---|
| N | % | ||||
| No need for treatment or support need (reference) | 17 | <1 | |||
| In ongoing treatment or received support at T0 | 7 | 3 | 5.99 | 2.05–17.50 | .002* |
| Stopped treatment or support after improvement | 8 | 2 | 3.43 | 1.42–8.28 | .007* |
| Perceived need, did not seek care | 5 | 2 | 3.65 | 1.67–8.00 | .002* |
| Stopped treatment or support without improvement | 3 | 2 | 3.05 | .61–15.30 | .170 |
| Total | 40 | 1 | |||
a
T0, baseline (1–2 months predeployment); T2, 2–3 months postdeployment; T3, 8–9 months postdeployment. In each row, Ns and percentages correspond to the number and percentage of participants within each treatment group who reported SI or SA at that time point. Total Ns used as denominators varied by group and time point and are not shown.
b
Adjusted OR (AOR) for age, education level, sex, marital status, deployment stress, lifetime SI, and lifetime SA (for the model of SA during or after deployment).
c
Model Ns varied slightly at each time point because of small amounts of missing covariate and outcome data. Predeployment baseline Ns for each treatment or support group are listed in Results (Sample Characteristics at Predeployment Baseline section).
* p<0.05.
SI during deployment.
Compared with participants who did not report any need for mental health treatment or support before deployment (at T0), significantly greater odds of SI during deployment were found among participants who were still receiving treatment or support at T0 (AOR=1.78, 95% CI=1.13–2.79, p=0.014) or had not pursued treatment or support despite needing it (AOR=1.73, 95% CI=1.02–2.93, p=0.043). Participants who sought mental health treatment or support before deployment and stopped after their problem had improved, as well as those who stopped treatment or support without improvement, did not have significantly increased risks for SI during deployment, compared with those who did not report any need for mental health treatment or support before deployment.
SI at T2.
Significantly greater odds of past-30-day SI at 2–3 months postdeployment (T2) were observed among participants who at T0 were still receiving treatment or support (AOR=2.51, 95% CI=1.18–5.34, p=0.018), had not pursued treatment or support despite needing it (AOR=2.08, 95% CI=1.18–3.67, p=0.013), or had stopped treatment or support without improvement (AOR=2.35, 95% CI=1.17–4.74, p=0.018), compared with participants who did not report any need for mental health treatment or support before deployment. Those who sought mental health treatment or support before deployment and stopped after improvement of their problem did not have a significantly higher SI risk at T2 than those who reported no past-year need for mental health treatment or support.
SI at T3.
Significantly greater odds of past-30-day SI at 8–9 months postdeployment (T3) were observed among participants who at T0 were still receiving treatment or support (AOR=2.75, 95% CI=1.58–4.81, p=0.001), had stopped treatment or support after improvement (AOR=1.71, 95% CI=1.03–2.85, p=0.038), or had not pursued treatment or support despite needing it (AOR=2.01, 95% CI=1.16–3.48, p=0.014), compared with participants who did not report any need for mental health treatment or support before deployment. Those who reported stopping treatment or support without improvement had no significantly increased SI risk at T3.
SA during or after deployment.
Significantly greater odds of SA (i.e., any attempt made during or after deployment) were observed among participants who at T0 were still receiving treatment or support (AOR=5.99, 95% CI=2.05–17.50, p=0.002), had stopped treatment or support after improvement (AOR=3.43, 95% CI=1.42–8.28, p=0.007), or had not pursued treatment or support despite needing it (AOR=3.65, 95% CI=1.67–8.00, p=0.002), compared with participants who did not report any need for mental health treatment or support before deployment. Those who stopped predeployment mental health treatment or support without improvement of their problem did not differ significantly in SA risk during or after deployment from those who reported no past-year need for mental health treatment or support.
Association of Specific Treatment Barriers With SI
In the exploratory subgroup analysis of respondents who reported not seeking treatment or support despite needing it, none of the associations between specific treatment barriers and SI outcomes were significant at p<0.0038 (Table 2). At an uncorrected p<0.05, thinking that treatment or support would not be helpful and worrying that it would harm one’s career were each significantly associated with SI during deployment and at T3. Inability to make an appointment was associated with SI during deployment, and high treatment cost was associated with SI at T3. “Other” reason was associated with SI during deployment and at T2. Given the low frequency (N=5) of SA reported in the subgroup, tests of association with SA were not conducted.
| SI during deployment (N=38)b | 30-day SI at T2 (N=18)b | 30-day SI at T3 (N=19)b | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Endorsed barrier | Did not endorse barrier | Endorsed barrier | Did not endorse barrier | Endorsed barrier | Did not endorse barrier | ||||||||||
| Treatment barrier | N | %c | N | %d | p | N | %c | N | %d | p | N | %c | N | %d | p |
| Problem is not severe | 18 | 15 | 20 | 19 | .478 | 9 | 7 | 9 | 9 | .808 | 10 | 9 | 9 | 9 | 1.000 |
| Talked to friends and relatives | 19 | 14 | 19 | 20 | .205 | 13 | 9 | 5 | 5 | .323 | 10 | 8 | 9 | 10 | .628 |
| Thought it would not help | 22 | 24 | 16 | 11 | .018 | 10 | 11 | 8 | 6 | .212 | 12 | 14 | 7 | 5 | .027 |
| Wanted to handle on my own | 29 | 17 | 9 | 15 | .841 | 15 | 9 | 3 | 5 | .415 | 17 | 11 | 2 | 3 | .109 |
| Transport or scheduling problem | 9 | 12 | 29 | 18 | .257 | 4 | 5 | 14 | 9 | .436 | 6 | 9 | 13 | 9 | 1.000 |
| High cost | 6 | 16 | 32 | 16 | 1.000 | 4 | 11 | 14 | 7 | .496 | 7 | 22 | 12 | 6 | .010 |
| Unsure whom to see | 11 | 18 | 27 | 16 | .686 | 6 | 10 | 12 | 7 | .576 | 6 | 11 | 13 | 8 | .417 |
| Could not get appointment | 7 | 35 | 31 | 15 | .028 | 4 | 20 | 14 | 7 | .059 | 2 | 13 | 17 | 8 | .634 |
| Feeling embarrassed | 10 | 21 | 18 | 13 | .105 | 8 | 9 | 10 | 7 | .806 | 10 | 12 | 9 | 7 | .224 |
| Worried would harm career | 23 | 22 | 15 | 12 | .032 | 10 | 10 | 8 | 6 | .332 | 13 | 14 | 6 | 5 | .028 |
| Leaders discouraged | 6 | 21 | 32 | 16 | .590 | 3 | 10 | 15 | 8 | .709 | 4 | 15 | 15 | 8 | .252 |
| Did not want Army to know | 10 | 16 | 28 | 17 | 1.000 | 6 | 10 | 12 | 7 | .582 | 7 | 13 | 12 | 7 | .270 |
| Other | 10 | 29 | 28 | 14 | .042 | 6 | 18 | 12 | 6 | .034 | 3 | 10 | 16 | 8 | .723 |
a
Separate Fisher’s exact tests were used to assess the association between each treatment barrier and each outcome. A Bonferroni correction was applied by using α=0.05 to obtain a threshold of p<0.0038 for each of the 13 barriers. Endorsement indicates that a participant reported the barrier was at least a “somewhat important” reason they did not seek treatment. T2, 2–3 months postdeployment; T3, 8–9 months postdeployment.
b
Number of participants at each time point who reported SI.
c
Percentage of participants who endorsed the treatment barrier and reported SI at each time point; denominators (omitted) were the total N of participants at each time point who had endorsed the corresponding treatment barrier.
d
Percentage of participants who did not endorse the treatment barrier but reported SI at each time point; denominators (omitted) were the total number of participants at each time point who had not endorsed the corresponding treatment barrier.
Discussion
This study examined the association between predeployment need for mental health treatment or support and subsequent SI and SA among U.S. Army soldiers. We found that soldiers preparing to deploy to Afghanistan who were either in ongoing treatment or support or who had not sought help despite needing it exhibited an elevated SI risk during and through at least 8–9 months after deployment. Additionally, soldiers who discontinued treatment or support without improvement exhibited an elevated SI risk 2–3 months after deployment. Together, these findings suggest that unmet or ongoing treatment or support needs at predeployment are associated with increased SI risk during deployment and reintegration.
On the other hand, soldiers who sought treatment or support and stopped after an improvement of their problem did not display elevated SI risk during or 2–3 months after deployment. Although the analysis did not evaluate the effects of specific types of treatment and support, this finding is consistent with evidence that interventions such as cognitive-behavioral therapy have beneficial effects on suicidal thoughts and behaviors, lasting several months after completion of treatment (27). Furthermore, in contrast with our finding of increased SI risk among soldiers with unmet or ongoing predeployment need for treatment or support, the lack of increased SI among those who indicated that their predeployment treatment or support needs had been met suggests that successfully addressing needs before deployment may mitigate SI risk among soldiers who perceive a need for treatment or support (at least through 2–3 months postdeployment).
By 8–9 months postdeployment, however, SI risk was elevated in the group of participants who stopped treatment or support after improvement of their problem, whereas no significant increase in risk was apparent at that time point for those who had stopped predeployment treatment or support without improvement of their problem. This counterintuitive finding may relate to the roughly 20-month interval between the assessment of need for treatment or support and the T3 outcome. Perhaps intervening events (e.g., life stressors or new treatments) affected outcomes at T3 more than did predeployment factors such as the perceived success of predeployment treatment or support.
We observed a significantly elevated risk for SA during or after deployment among those who reported ongoing treatment or support before deployment, stopping treatment or support after improvement, or not seeking help despite needing it, but not among those who reported stopping treatment or support without improvement. Given that all but 11 reported SAs occurred after the T2 survey, the pooled SA outcome variable primarily reflected attempts made >1 year after baseline, which, similar to the T3 SI outcome, might have been influenced more by recent events (e.g., stressors, new treatments) than by predeployment treatment or support. Furthermore, given the rarity of SA, CIs for adjusted odds of SA were large, and the study may have been underpowered to detect effects across all groups with a need for treatment or support (particularly in subgroups with small samples). This caveat could also apply to the interpretation of nonsignificant effects from the SI models, because suicidal thoughts were also relatively infrequent. The corollary is that statistically significant effects were robust; “significantly elevated odds” reflected increases in the odds of SI outcomes by up to 2.75 and in the odds of SA by between 3.43 and 5.99.
In the analysis of treatment barriers reported by soldiers who did not seek help for their problems despite needing it, no individual barrier was found to be associated with SI outcomes at the Bonferroni-corrected probability level. The Bonferroni correction is a conservative procedure to reduce type I error and may thereby increase the risk for type II error (28). When using an uncorrected α=0.05, we found that two attitudinal barriers (thinking treatment would not be helpful and worrying treatment would harm one’s career) were each significantly associated with SI during deployment and at the T3 follow-up and that two structural barriers (cost and inability to make an appointment) were each associated with SI at one time point each. Although cost as a barrier is surprising, given participants’ access to TRICARE, it is possible that career-related concerns about receiving mental health treatment encouraged some soldiers to seek care from civilian sources.
It is possible that significant associations between treatment barriers and suicidality outcomes would be detected with increased statistical power (e.g., using a larger sample or validated scales assessing attitudinal or structural barriers rather than single-item ratings). A better understanding of how treatment barriers relate to mental health outcomes might help identify soldiers with treatment or support needs who are at a particularly heightened risk for SI or SA. Future research should also aim to identify effective strategies for reducing barriers to care in the active duty population.
As alluded to previously, one limitation of this study was that, aside from deployment stressors, our models did not capture effects of potentially impactful events occurring after baseline, such as nondeployment stressors or subsequent treatments. Another limitation was that, although our models accounted for the effects of previous SI and SA on subsequent suicidality, they did not account for psychiatric diagnoses that may be risk factors for suicidality among service members (29–32). Soldiers in ongoing treatment or support at predeployment baseline may have had the most significant needs or most severe mental disorders, which could explain why adjusted odds of SI and SA tended to be greatest in this group. Similarly, perceived improvement of problems after treatment or support may have differed depending on the type or severity of the predeployment disorder. Although it was beyond the scope of this investigation, it will be important for future studies to determine whether the effects of need for treatment or support on suicidality are mediated by specific mental disorders or comorbid conditions.
Furthermore, this study defined mental health treatment and support broadly, to include both care from mental health professionals and support from other sources (e.g., self-help groups). The type and severity of perceived need for mental health treatment or support were not assessed, nor was the quality or intensity of the help received. The study instead relied on self-reported improvement of mental health problems after treatment or support as an indicator of needs being successfully met. Additionally, this study relied on self-reports of treatment or support needs, help seeking, SI, and SA, all of which may be affected by underreporting (5, 33, 34). Finally, the study findings may not generalize to members of other military service branches or to personnel deployed to other settings (e.g., peacekeeping missions).
Conclusions
In this study, we found an elevated risk for SI during and after deployment among service members who reported an ongoing or unmet need for mental health treatment or support before deployment. Soldiers who reported that they sought help for mental health problems and stopped treatment after improving did not exhibit increased SI risk during or 2–3 months after deployment. Together, these results suggest that addressing treatment needs in the months leading up to deployment may help prevent SI during deployment and reintegration. More work is needed to determine whether specific barriers to treatment exacerbate the adverse effects of unmet need for mental health treatment or support among soldiers. Future studies examining the impact of treatment and support needs on future SI and SA should evaluate whether its effects are mediated through specific mental disorders and should consider the effects of factors more proximal to suicidality outcomes, such as new stressors or recent treatment.
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Information & Authors
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Published In
History
Received: 4 May 2022
Revision received: 31 July 2022
Revision received: 18 December 2022
Accepted: 30 December 2022
Published online: 6 March 2023
Published in print: August 01, 2023
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Competing Interests
Dr. Kessler has served as a consultant for Cambridge Health Alliance, Canandaigua VA Medical Center, Holmusk, Partners Healthcare, Inc., RallyPoint Networks, Inc., and Sage Therapeutics; he has stock options in Cerebral, Inc., Mirah, Prepare Your Mind, and Roga Sciences. Dr. Stein has received consulting income from Acadia Pharmaceuticals, Aptinyx, atai Life Sciences, BigHealth, Bionomics, BioXcel Therapeutics, Boehringer Ingelheim, Clexio, Eisai, EmpowerPharm, Engrail Therapeutics, Janssen, Jazz Pharmaceuticals, NeuroTrauma Sciences, PureTech Health, Sumitomo Pharma, and Roche/Genentech; has stock options in Oxeia Biopharmaceuticals and EpiVario; and has been paid for his editorial work on Depression and Anxiety, Biological Psychiatry, and UpToDate. The other authors report no financial relationships with commercial interests.
Funding Information
Data collection for this study was sponsored by the U.S. Department of the Army and funded under cooperative agreement number U01 MH-087981 with the U.S. Department of Health and Human Services (HHS) and NIMH.The contents are solely the responsibility of the authors and do not necessarily represent the views of the HHS, NIMH, U.S. Department of the Army, or U.S. Department of Defense.This research was based on public use data from the Army Study to Assess Risk and Resilience in Servicemembers. The data are available from the Inter-University Consortium for Political and Social Research at the University of Michigan (https://doi.org/10.3886/ICPSR35197.v7).
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