Skip to main content
NCBI home page
Military Psychology logoLink to Military Psychology
. 2023 Mar 15;36(4):403–409. doi: 10.1080/08995605.2023.2189861

The role of unit cohesion and perceived resilience in substance use disorder

Rachel N Ward a,✉, Alexander J Erickson a,b, Katie J Carlson a, Matthew M Yalch a
PMCID: PMC11197915  PMID: 38913766

ABSTRACT

Soldiers have high rates of substance use disorders (SUD), often in the aftermath of stressors experienced during military deployments. There are several factors that protect against SUD. For example, individual factors like perceived resilience and group factors such as unit cohesion may make someone less likely to abuse substances. However, there is little research on the differential influence of these resilience factors on SUD over and above deployment stressors. In this study, we examined the relative effects of perceived resilience, unit cohesion, and deployment stressors on SUD in a sample of 21,449 active duty and reserve soldiers from the U.S. Army (primarily White and male, mean age = 28.66, SD = 7.41) using structural equation modeling. We found that unit cohesion (ß = −.17) and perceived resilience (ß = −.16) had negative effects on SUD over and above deployment stressors. The study findings clarify research on resilience to SUD and have implications for addressing substance use in the military, specifically regarding the importance of building unit cohesion.

KEYWORDS: Unit cohesion, resilience, military, substance use disorder, army

What is the public significance of this article?—This study suggests that unit cohesion and perceived resilience reduce the risk of SUD after accounting for the effects of deployment stressors and factors such as age, gender, and length of time since last deployment. This highlights the possible buffering effects of unit cohesion and perceived resilience on the association between deployment stressors and SUD. These results further suggest that interventions focused on building unit cohesion may be useful to include in the ongoing efforts to reduce substance misuse in the military.

Substance use disorder (SUD) is common in the military and especially in the Army (Bray et al., 2010; Deployment Health Clinical Center, 2017), with an estimated 3% of all soldiers in 2016 meeting criteria for a substance or alcohol-related disorder (Deployment Health Clinical Center, 2017). The disordered use of alcohol, as well as tobacco, prescription, and illicit drug use, is common in the military (Meadows et al., 2018), though disordered use may be more pronounced when looking at younger servicemembers, who have higher rates of SUD compared to civilians (Teeters et al., 2017). Some of this is an aspect of military culture, which may encourage the use of substances (e.g., as a show of bravado and group bonding; Dworkin et al., 2018; Jones & Fear, 2011; Meadows et al., 2018). Soldiers may also use substances in response to specific stressors such as combat exposure (Bray et al., 2013; Larson et al., 2012; London et al., 2020) to alleviate emotional distress and enhance mood (Khantzian, 1985; Sinha, 2001). Of course, not all soldiers who experience stressors during deployment have SUD. This is in line with the self-medication hypothesis, which indicates that initial use of substances to cope following exposure to stressors is influenced by genetic and individual vulnerability factors (e.g., family history, personality traits, social influences) and maladaptive stress responses (e.g., sensitivity to stress, poor behavioral/cognitive coping; Khantzian, 1985; Sinha, 2001). For soldiers who are experiencing deployment-related stressors, such factors may include unit cohesion (individual vulnerability factor) and resilience (presence of adaptive/maladaptive stress response). Given the mixed consensus regarding the association between unit cohesion and SUD, as well as a lack of literature regarding how resilience may factor into this association, these factors warrant further investigation in the context of SUD.

The individual factor of resilience is the ability of a person to be resourceful and respond adaptively to stressful situations (Ward et al., 2021). Resilience plays a part in determining whether an individual’s stress response is maladaptive, increasing risk of SUD during military service (Bartone et al., 2017; Eid et al., 2011) and following military discharge (Bartone et al., 2015; Norman et al., 2014). In military research, resilience overlaps with hardiness, a combination of attitudes that allow an individual to adapt to a stressful situation and turn it into growth opportunities (Maddi, 2006). Hardiness is inversely related to alcohol misuse, such that hardiness and alcohol misuse are inversely associated (Bartone et al., 2015, 2017; Eid et al., 2011).

There are also interpersonal factors associated with lower risk of SUD. Perhaps, the most important from a military perspective is unit cohesion, the ability of a group to perform actions toward a shared goal (Britt et al., 2013). One study found that unit cohesion is positively associated with post-deployment alcohol misuse in US Marines (Breslau et al., 2016). This may reflect a general culture within the military that encourages alcohol use to assist in group bonding, reduce stress, and raise morale (Dworkin et al., 2018; Jones & Fear, 2011). In contrast, another study found high pre-deployment unit cohesion associated with reduced likelihood of post-deployment SUD in Army servicemembers (Anderson et al., 2019). However, this effect was only present for soldiers who exhibited SUD pre-deployment (Anderson et al., 2019). Although the aforementioned studies found effects of unit cohesion on SUD generally, there is also evidence that no association between unit cohesion and SUD exists (Avery & McDevitt-Murphy, 2014). Even less clear is how unit cohesion might be associated with SUD relative both to individual resilience and to deployment stressors.

Present study

In this study, we examined the relative effects of individual resilience, unit cohesion, and deployment stressors on SUD to clarify the mixed findings regarding the relationship between unit cohesion and SUD while also exploring how resilience and deployment stressors affect SUD. These results could also inform resilience-building programs in the military, which aim to use factors such as unit cohesion and individual resilience to buffer against negative mental health outcomes like SUD. We hypothesized that resilience and unit cohesion would have negative influences on SUD and that deployment stressors would have a positive influence on SUD.

Methods

Participants and procedure

Participants included in the study were 21,449 active duty and reserve soldiers from the U.S. Army who were enrolled in the Army Study to Assess Risk and Resilience in Servicemembers (STARRS) and who completed the All Army Survey (AAS; for study details, see Kessler et al., 2013a; Ursano et al., 2018). Data was collected between 2011 and 2013 via cross-sectional sampling of all active duty personnel exclusive of those who were entering basic training. Sampling was conducted every quarter and was stratified to be representative of all soldiers stationed either in the continental U.S. or outside of the continental U.S. but not in a combat theater. Assessments were self-administered. The sample was majority White and male with a mean age of 28.66 years (SD = 7.41, range = 18–61; see, Tables 1 and 2). All participants provided informed consent and study procedures received approval from the human subjects committees of the collaborating organizations (Kessler et al., 2013a). Approval for secondary data analysis was from the Palo Alto University Institutional Review Board.

Table 1.

Descriptive statistics.

  n (%)
Gender  
 Men 18,790 (88%)
 Women 2504 (12%)
Race  
 White 14,212 (66%)
 Black/African American 3253 (15%)
 American Indian/Alaskan Native 385 (2%)
 Asian 868 (4%)
 Pacific Islander 375 (2%)
 Other 2356 (11%)
Active Duty Status  
 Active Duty 17,605 (82%)
 National Guard/Reserve 1202 (6%)
Education  
 GED or equivalent 1315 (6%)
 High School Diploma 6716 (31%)
 Some Post-high School No Degree 5904 (28%)
 Technical School Degree 1336 (6%)
 2-year Associate Degree 2174 (10%)
 4-year College Degree 2766 (13%)
 Graduate/Professional Study 1050 (5%)
Open in a new tab

Table 2.

Distribution of gender by race.

  Male Female
White 12,839 (68%) 1315 (53%)
Black/African American 2586 (14%) 651 (26%)
American Indian/Alaskan Native 324 (2%) 58 (2%)
Asian 761 (4%) 101 (4%)
Pacific Islander 313 (2%) 60 (2%)
Other 1967 (10%) 319 (13%)
Open in a new tab

Measures

SUD

SUD was measured using 12-items from the Composite International Diagnostic Interview Screening Scales (Kessler & Üstün, 2004), which assessed the quantity and frequency of participants’ alcohol use, illicit drug use, and prescription drug misuse (four items for substance abuse, eight for substance dependence if participants indicated any substance use). The questions assessed areas such as withdrawal symptoms, interpersonal and social role difficulties because of substance use, and concerns about substance use. Participants rated the frequency of specific symptoms over the past 30 days before interview on a 5-point scale ranging from none of the time to all or almost all of the time. The original research team assessed the overall substance use using the same questions (e.g., “How often in the past 30 days did you have any of the following problems because of your use of alcohol or drugs?”) Participants were then classified based on DSM-IV criteria for alcohol or drug abuse or dependence diagnoses as either meeting criteria (1) or not meeting criteria (0) for a SUD (Kessler et al., 2013b). A small proportion of the sample (4%) met criteria for a probable SUD.

Deployment stressors

Deployment stressors were measured using nine self-report items from the Deployment Risk and Resilience Inventory (DRRI; King et al., 2006), which assessed stressors common in deployments to war zones and other hazardous environments (e.g., combat experiences, exposure to death/destruction, physical and sexual assault, bullying). Participants rated how much they experienced each stressor during all their deployments on a 5-point scale, indicating the frequency with which a stressor was experienced (zero, one, two-four, five-nine, or ten or more times). We used a mean score of all DRRI items to represent the average frequency of deployment stressors endorsed (M = 1.03, SD = .73, range = 0–4; α = .99).

Perceived resilience

Perceived resilience was measured using five items from the Hurricane Katrina Community Advisory Group questionnaire (Hurricane Katrina Community Advisory Group, 2006), which assessed participants’ ability to handle stress in the following ways: “Keep calm and think of the right thing to do in a crisis,” “Manage stress,” “Try new approaches if old ones don’t work,” “Get along with people when you have to,” and “Keep your sense of humor in tense situations.” Participants rated their ability to use the behavior described in each item on a 5-point scale ranging from poor to excellent with the following prompt: “People differ a lot in how well they handle stress. How would you rate your ability to handle stress in each of the following ways?” We obtained a latent measurement of perceived resilience, for which the confirmatory factor analysis (CFA, using robust maximum likelihood [MLR] estimation) for which converged with adequate fit (CFI = .99, TLI = .94, SRMR = .03, RMSEA = .10).

Unit cohesion

Unit cohesion was measured using five items from the 2007–2009 Joint Mental Health Advisory Team 7 questionnaire (Joint Mental Health Advisory Team 7, 2011): “I can rely on other members of my unit for help if I need it,” “I can open up and talk to my first line leaders if I need help,” “I respect the Non-Commissioned Officers in my unit,” “I respect the Officers in my unit,” and “My leaders take a personal interest in the well-being of all the Soldiers in my unit.” Participants rated their level of agreement with each item on a 5-point scale ranging from strongly disagree to strongly agree. We obtained a latent measurement of unit cohesion, for which the CFA (MLR estimation) converged with adequate fit (CFI = .96, TFI = .93, SRMR = .03, RMSEA = .10).

Data analysis

We tested study hypotheses using a structural equation model (SEM) in Mplus (v 8.6; Muthén & Muthén, 1998–2017), which we regressed SUD on deployment stressors, perceived resilience, and unit cohesion. Perceived resilience and unit cohesion were included as latent constructs to ensure that the selected items were measuring the respective constructs. We estimated the model using weighted least squares with mean and variance adjusted (WLSMV) for SEM estimation of a dichotomous outcome variable and evaluated model fit using conventional indices (root mean square error of approximation (RMSEA), standardized root mean squared residual (SRMR), comparative fix index (CFI), Tucker-Lewis index (TLI); for review, see Kenny, 2015). As customary in cross-sectional SEM within Mplus, all means for latent variables were set to zero. For variable correlations, see, Table 3.

Table 3.

Variable correlations.

  1 2 3 4 5 6 7 8 9 10 11 12
1. Rely on members of unit -                      
2. Respect noncommissioned officers .98 -                    
3. Respect commissioned officers .97 .98 -                  
4. Leaders take interest in well-being .97 .98 .98 -                
5. Open up and talk to leader .98 .98 .98 .98 -              
6. Keep calm/think of right thing to do .73 .72 .71 .72 .72 -            
7. Manage stress .73 .72 .72 .72 .72 .99 -          
8. Try new approaches .72 .71 .71 .71 .72 .98 .98 -        
9. Get along with people .72 .71 .71 .71 .72 .98 .98 .98 -      
10. Keep sense of humor .73 .72 .71 .72 .72 .98 .98 .98 .98 -    
11. Deployment Stressors −.06 −.06 −.06 −.06 −.06 −.07 −.07 −.07 −.07 −.07 -  
12. 30-Day SUD −.06 −.06 −.06 −.06 −.06 −.05 −.06 −.06 −.06 −.05 −.06 -
Open in a new tab

All correlations are significant at p < .05.

Results

The SEM demonstrated adequate fit overall (CFI = .95, TLI = .93, RMSEA = .04, SRMR = .03; see, Figure 1). Perceived resilience and unit cohesion were moderately correlated with each other. (ß = −.35). Perceived resilience (ß = .03) and unit cohesion (ß = −.03) were minimally associated with deployment stressors. Both unit cohesion (ß = −.16) and perceived resilience (ß = −.17) had small negative effects, and deployment stressors (ß = .16) had a small positive effect on SUD.

Figure 1.

Figure 1.

Open in a new tab

Structural model of unit cohesion, resilience, and 30-day SUD.

Note. Standardized factor loadings are shown, with 95% confidence intervals in parentheses.

Post hoc analyses

We conducted a post hoc analysis after exploration of the initial model results controlling for the inclusion of potentially confounding factors associated with SUD in military personnel, namely age, gender, and length of time since last deployment. Participants reported the number of months since they returned from their most recent deployment (0–3 months [7%], 4–6 months [10%], 7–12 months [10%], 1–2 years [13%], 3–4 years [5%], 5+ years [3%]). As only a subset of participants were asked to report the number of months since their return from their most recent deployment, this post hoc analyses was conducted on a smaller sample (n = 10,079). The model demonstrated adequate fit (CFI = .90, TLI = .88, RMSEA = .05, SRMR = .10; see, Figure 2). In examining the included covariates, both age (ß = −.15) and months since last deployment (ß = .10) had significant effects on SUD. Unit cohesion (ß = −.15), perceived resilience (ß = −.18), and deployment stressors (ß = .13) continued to have small, significant effects on SUD.

Figure 2.

Figure 2.

Open in a new tab

Structural model of unit cohesion, resilience, and 30-day SUD accounting for confounding factors.

Note. Standardized factor loadings are shown, with 95% confidence intervals in parentheses.

Discussion

In this study, we examined the relative effects of deployment stressors, perceived resilience, and unit cohesion on SUD. We found that perceived resilience and unit cohesion were associated with lower risk of SUD over and above the effects of deployment stressors. These findings clarify the role of unit cohesion and SUD vis-à-vis other risk and resilience factors. Results also suggest directions for future research on and interventions targeting substance misuse in the military given the focus of existing resilience-building programs in the military on reducing the risk of deleterious mental health outcomes such as SUD using factors by increasing resilience factors.

The effects of unit cohesion and perceived resilience on the risk of SUD after accounting for their association suggests that both factors provide related but distinct contributions in reducing soldiers’ risk of SUD. That these associations remained after accounting for the effects of deployment stressors and factors such as age, gender, and length of time since last deployment further strengthens these findings. Future research should expand on this research by examining if there are possible buffering effects of unit cohesion and perceived resilience on the association between deployment stressors and SUD.

Results further suggest that building unit cohesion may be useful to include in the Army’s ongoing efforts to reduce substance use (Larson et al., 2012), as well as for camaraderie for its own sake. Future research should examine how well this works in practice given that unit cohesion is modifiable. That cohesion is also associated with soldiers’ individual perceived resilience may also suggest that more cohesive units make soldiers more resilient on an individual level, although it is also possible that more resilient soldiers tend to make for more cohesive units. For example, engaging the unit in activities that require them to work together (e.g., increasing unit cohesion), while promoting the use of healthy coping strategies as an alternative to maladaptive coping strategies like substance misuse and deemphasizing the role of alcohol or other substances during recreational/leisure activity, could augment existing programs. As existing programs for building resilience do not tend to focus on increasing unit cohesion (Meredith et al., 2011), future research should explore whether the incorporation of unit cohesion into these resilience-building programs, alongside promoting the use of healthy, more adaptive coping mechanisms over using substances to cope, reduces rates of substance misuse and SUD within the military.

This study has several limitations which also suggest direction for future research. First, measures of study constructs were relatively brief. Although this was likely due to the constraints of implementing a large-scale study (Fisher et al., 2016), it reduced variance in and thus likely explanatory power of predictors, potentially underrepresenting the size of findings. Our measurement of SUD in particular was further limited in that it concerned the disordered use of substances in general rather than specific types of substances (e.g., alcohol, marijuana, opiates). This may be problematic because stressors, perceived resilience, and unit cohesion may influence the use of different substances in different ways (Khantzian, 1985). Military career information, such as rank, military occupational specialty, years in service, and detailed deployment history, could not be controlled for because these variables were not available for public use to preserve soldier privacy. Self-report bias or response bias may have also influenced the results and led to under-reporting. However, as 4% of our sample met criteria for probable SUD and approximately 3% of soldiers were estimated to meet criteria for SUD in a different study (Deployment Health Clinical Center, 2017), any bias appears to be consistent across surveys. Finally, the cross-sectional design of this study prevented causal interpretation and directionality of results. Future research should address these limitations by using more robust measurement of study constructs, doing so within a longitudinal design. Future research should also explore how unit cohesion differentially affects substance misuse (e.g., behaviors related to problematic substance use) versus disordered substance use (i.e., substance use that meets criteria for a disorder) and whether these associations change based on the type of substance used.

In this study, we clarified the association between perceived resilience, unit cohesion, deployment stressors, and SUD. This could inform existing resilience-building programs that aim to reduce the risk of negative mental health outcomes such as SUD, suggesting that improving unit cohesion is important in supporting individual resilience and reducing the risk of SUD. Future research can expand on these findings, with hopes of eventually alleviating one of the most enduring mental health problems in the military.

Funding Statement

This work was supported by the Foundation for the National Institutes of Health [U01MH87981].

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

This publication is based on public use data from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). The data are available from the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan (http://doi.org/10.3889/ICPSR35197.v2). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the views of the Army STARRS investigators, funders, Department of the Army, or Department of Defense.

References

  1. Anderson, L., Campbell-Sills, L., Ursano, R. J., Kessler, R. C., Sun, X., Heeringa, S. G., Nock, M. K., Bliese, P. D., Gonzalez, O. I., Wynn, G. H., Jain, S., & Stein, M. B. (2019). Prospective associations of perceived unit cohesion with postdeployment mental health outcomes. Depression and Anxiety, 36(6), 511–521. 10.1002/da.22884 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Avery, M., & McDevitt-Murphy, M. (2014). Impact of combat and social support on PTSD and alcohol consumption in OEF/OIF veterans. Military Behavioral Health, 2(2), 217–223. 10.1080/21635781.2014.891433 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bartone, P. T., Eid, J., Hystad, S. W., Jocoy, K., Laberg, J. C., & Johnsen, B. H. (2015). Psychological hardiness and avoidance coping are related to risky alcohol use in returning combat veterans. Military Behavioral Health, 3(4), 274–282. 10.1080/21635781.2015.1085931 [DOI] [Google Scholar]
  4. Bartone, P. T., Johnsen, B. H., Eid, J., Hystad, S. W., & Laberg, J. C. (2017). Hardiness, avoidance coping, and alcohol consumption in war veterans: A moderated-mediation study. Stress and Health, 33(5), 498–507. 10.1002/smi.2734 [DOI] [PubMed] [Google Scholar]
  5. Bray, R. M., Brown, J. M., & Williams, J. (2013). Trends in binge and heavy drinking, alcohol-related problems, and combat exposure in the U.S. Military. Substance Use & Misuse, 48(10), 799–810. 10.3109/10826084.2013.796990 [DOI] [PubMed] [Google Scholar]
  6. Bray, R. M., Pemberton, M. R., Lane, M. E., Hourani, L. L., Mattiko, M. J., & Babeu, L. A. (2010). Substance use and mental health trends among U.S. military active duty personnel: Key findings from the 2008 DoD health behavior survey. Military Medicine, 175(6), 390–399. 10.7205/MILMED-D-09-00132 [DOI] [PubMed] [Google Scholar]
  7. Breslau, J., Setodji, C. M., & Vaughan, C. A. (2016). Is cohesion within military units associated with post-deployment behavioral and mental health outcomes? Journal of Affective Disorders, 198, 102–107. 10.1016/j.jad.2016.03.053 [DOI] [PubMed] [Google Scholar]
  8. Britt, T. W., Sinclair, R. R., & McFadden, A. C. (2013). Introduction: The meaning and importance of military resilience. In Sinclair R. R. & Britt T. W. (Eds.), Building psychological resilience in military personnel: Theory and practice (Vols. 2013-03064-001, pp. 3–17). American Psychological Association. 10.1037/14190-001 [DOI] [Google Scholar]
  9. Deployment Health Clinical Center . (2017). Mental health care utilization by active duty service members in the military health system, fiscal years 2005–2015.
  10. Dworkin, E. R., Bergman, H. E., Walton, T. O., Walker, D. D., & Kaysen, D. L. (2018). Co-occurring post-traumatic stress disorder and alcohol use disorder in U.S. Military and veteran populations. Alcohol Research: Current Reviews, 39(2), 161–169. https://pubmed.ncbi.nlm.nih.gov/31198655/ [PMC free article] [PubMed] [Google Scholar]
  11. Eid, J., Brevik, J. I., Hystad, S. W., & Bartone, P. T. (2011). Evaluation of psychological hardiness and coping style as risk/resilience factors for health risk behaviour. Joint Medical Command. https://apps.dtic.mil/docs/citations/ADA582921 [Google Scholar]
  12. Fisher, G. G., Matthews, R. A., & Gibbons, A. M. (2016). Developing and investigating the use of single-item measures in organizational research. Journal of Occupational Health Psychology, 21(1), 3–23. 10.1037/a0039139 [DOI] [PubMed] [Google Scholar]
  13. Hurricane Katrina Community Advisory Group . (2006). Baseline interview for the Hurricane Katrina Community Advisory Group. www.hurricanekatrina.med.harvard.edu/surveyinstruments.php
  14. Joint Mental Health Advisory Team 7 (J-MHAT 7) . (2011). Operation Enduring Freedom 2010 Afghanistan.
  15. Jones, E., & Fear, N. T. (2011). Alcohol use and misuse within the military: A review. International Review of Psychiatry, 23(2), 166–172. 10.3109/09540261.2010.550868 [DOI] [PubMed] [Google Scholar]
  16. Kenny, D. A. (2015). Measuring model fit. http://www.davidakenny.net/cm/fit.htm
  17. Kessler, R. C., Colpe, L. J., Fullerton, C. S., Gebler, N., Naifeh, J. A., Nock, M. K., Sampson, N. A., Schoenbaum, M., Zaslavsky, A. M., Stein, M. B., Ursano, R. J., & Heeringa, S. G. (2013a). Design of the army study to assess risk and resilience in servicemembers (Army STARRS). International Journal of Methods in Psychiatric Research, 22(4), 267–275. 10.1002/mpr.1401 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kessler, R. C., Santiago, P. N., Colpe, L. J., Dempsey, C. L., First, M. B., Heeringa, S. G., Stein, M. B., Fullerton, C. S., Gruber, M. J., Naifeh, J. A., Nock, M. K., Sampson, N. A., Schoenbaum, M., Zaslavsky, A. M., & Ursano, R. J. (2013b). Clinical reappraisal of the composite international diagnostic interview screening scales (CIDI-SC) in the army study to assess risk and resilience in servicemembers (Army STARRS). International Journal of Methods in Psychiatric Research, 22(4), 303–321. 10.1002/mpr.1398 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kessler, R. C., & Üstün, T. B. (2004). The world mental health (WMH) survey initiative version of the world health organization (WHO) composite international diagnostic interview (CIDI). International Journal of Methods in Psychiatric Research, 13(2), 93–121. 10.1002/mpr.168 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Khantzian, E. J. (1985). The self-medication hypothesis of addictive disorders: Focus on heroin and cocaine dependence. The American Journal of Psychiatry, 142(11), 1259–1264. 10.1176/ajp.142.11.1259 [DOI] [PubMed] [Google Scholar]
  21. King, L. A., King, D. W., Vogt, D. S., Knight, J., & Samper, R. E. (2006). Deployment Risk and Resilience Inventory: A collection of measures for studying deployment-related experiences of military personnel and veterans. Military Psychology, 18(2), 89–120. 10.1207/s15327876mp1802_1 [DOI] [Google Scholar]
  22. Larson, M. J., Wooten, N. R., Adams, R. S., & Merrick, E. L. (2012). Military combat deployments and substance use: Review and future directions. Journal of Social Work Practice in the Addictions, 12(1), 6–27. 10.1080/1533256X.2012.647586 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. London, A. S., Wilmoth, J. M., Oliver, W. J., & Hausauer, J. A. (2020). The influence of military service experiences on current and daily drinking. Substance Use & Misuse, 55(8), 1288–1299. 10.1080/10826084.2020.1735438 [DOI] [PubMed] [Google Scholar]
  24. Maddi, S. R. (2006). Hardiness: The courage to grow from stresses. The Journal of Positive Psychology, 1(3), 160–168. 10.1080/17439760600619609 [DOI] [Google Scholar]
  25. Meadows, S. O., Engel, C. C., Collins, R. L., Beckman, R. L., Cefalu, M., Hawes-Dawson, J., Waymouth, M., Kress, A. M., Sontag-Padilla, L., Ramchand, R., & Williams, K. M. (2018). 2015 health related behaviors survey (HBRS): Mental and emotional health among U.S. active-duty service members. RAND Corporation. 10.7249/RB9955.3 [DOI] [Google Scholar]
  26. Meredith, L. S., Sherbourne, C. D., Gaillot, S. J., Hansell, L., Ritschard, H. V., Parker, A. M., & Wrenn, G. (2011). Promoting psychological resilience in the U.S. military. Rand Health Quarterly, 1(2), 2. [PMC free article] [PubMed] [Google Scholar]
  27. Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus user’s guide (8th ed.). Muthén & Muthén. [Google Scholar]
  28. Norman, S. B., Schmied, E., & Larson, G. E. (2014). Predictors of continued problem drinking and substance use following military discharge. Journal of Studies on Alcohol and Drugs, 75(4), 557–566. 10.15288/jsad.2014.75.557 [DOI] [PubMed] [Google Scholar]
  29. Sinha, R. (2001). How does stress increase risk of drug abuse and relapse? Psychopharmacology, 158(4), 343–359. 10.1007/s002130100917 [DOI] [PubMed] [Google Scholar]
  30. Teeters, J. B., Lancaster, C. L., Brown, D. G., & Back, S. E. (2017). Substance use disorders in military veterans: Prevalence and treatment challenges. Substance Abuse and Rehabilitation, 8, 69–77. 10.2147/SAR.S116720 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Ursano, R. J., Stein, M. B., Kessler, R. C., & Heeringa, S. G. (2018). Army study to assess risk and resilience in servicemembers (STARRS) (ICPSR35197-v2). Inter-university Consortium for Political and Social Research [distributor]. 10.3886/ICPSR35197.v7. [DOI] [Google Scholar]
  32. Ward, R. N., Brady, A. J., Jazdzewski, R., & Yalch, M. (2021). Stress, resilience, and coping. In Pradhan R. & Kumar U. (Eds.), Emotion, wellbeing and resilience: Theoretical perspectives and practical applications (pp. 3–14). Apple Academic. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

This publication is based on public use data from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). The data are available from the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan (http://doi.org/10.3889/ICPSR35197.v2). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the views of the Army STARRS investigators, funders, Department of the Army, or Department of Defense.

Articles from Military Psychology are provided here courtesy of Division of Military Psychology of the American Psychological Association and Taylor & Francis

RESOURCES