Social Support and Mental Health Outcomes Among ...

Military Psychology 2016, Vol. 28, No. 3, 000

In the public domain http://dx.doi.org/10.1037/mil0000114

Social Support and Mental Health Outcomes Among U.S. Army Special Operations Personnel Dale W. Russell, David M. Benedek, James A. Naifeh, Carol S. Fullerton, Nikki Benevides, and Robert J. Ursano

Cristel A. Russell American University

Uniformed Services University of the Health Sciences

Robert D. Forsten

John T. Cacciopo

United States Army War College

University of Chicago

Mental health disorders continue to plague service members and veterans; thus, new approaches are required to help address such outcomes. The identification of risk and resilience factors for these disorders in specific populations can better inform both treatment and prevention strategies. This study focuses on a unique population of U.S. Army Special Operations personnel to assess how specific avenues of social support and personal morale are related to mental health outcomes. The results indicate that, whereas personal morale and friend support reduce the relationship between combat experiences and posttraumatic stress disorder (PTSD), strong unit support exacerbates the negative effects of combat experiences in relation to PTSD. The study thus shows that although informal social support can lessen postdeployment mental health concerns, military populations with strong internal bonds may be at greater risk of PTSD because the support that they receive from fellow service members may heighten the traumatic impact of combat experiences. Keywords: military, mental health, social support, PTSD, Special Forces

Postdeployment mental health problems negatively impact operational readiness, strain limited health care resources, and impair interpersonal relationships with family and peers (Harrison, Satterwhite, & Ruday, 2010; Hoge,

Auchterlonie, & Milliken, 2006; Milliken, Auchterlonie, & Hoge, 2007). Such negative outcomes might be mitigated by better identifying modifiable risk and resilience factors that can aid the development of more effective policies as well as prevention and intervention programs (Iversen et al., 2008; Kilbourne, McCarthy, Post, Welsh, & Blow, 2007). Social support has been identified as a potential protective factor that is particularly relevant to military personnel and is a major component of the U.S. Army’s Comprehensive Soldier and Family Fitness program, which aims to improve physical and mental health outcomes, build resilience, and enhance the overall well-being of service members and their family members (McHugh, 2013). In contrast to many other risk and resilience factors, unit social support (e.g., peer and leadership relations) underpins military cultural values and may be modifiable through specific

Dale W. Russell, David M. Benedek, James A. Naifeh, Carol S. Fullerton, Nikki Benevides, and Robert J. Ursano, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences; Cristel A. Russell, Kogod School of Business, American University; Robert D. Forsten, United States Army War College; John T. Cacciopo, Department of Psychology, University of Chicago. The views expressed are those of the authors and do not reflect the official policy or position of the United States Government or the Department of Defense. Correspondence concerning this article should be addressed to Dale W. Russell, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814. E-mail: [email protected] 1

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military training programs or doctrinal adjustments (Gates, 2011). A service member’s military occupational specialty (e.g., an infantryman vs. a cook) is a potentially important factor affecting both social support and risk of mental health issues due to differences in selection criteria and likelihood of combat preparation training and exposure (Pitts et al., 2013; Pitts, Safer, & Russell, 2014). Although many studies have assessed a broad range of military occupational specialties, the extant literature is in want of studies that give specific focus to Special Operations personnel (Cronk, 2014; Dean & McNeil, 2012; Joint Special Operations University, 2014). Special Operations personnel represent approximately 67,000 members of the U.S. military (Joint Special Operations University, 2014) and are present in most military forces in the world. Special Operations personnel are an understudied occupational population that may exhibit unique risk and resilience profiles for mental health outcomes (Osório et al., 2013) due, for example, to the rigorous process used to select suitable candidates from the general active duty applicant pool, as well as intense training designed to enhance both mental and physical performance of those selected (U.S. Department of Defense, 2014). A multitude of countries are becoming more reliant on Special Operations personnel for both peace and military missions because they provide more economic, dynamic, and robust assets than do conventional forces to address contemporary issues, which tend to be shrouded in complexities (Ball, 2011; Svendsen, 2014). Special Operations units are known for high community spirit (or esprit de corps) and camaraderie, which underlies strong bonds of trust and interreliability (Gates, 2011). This spirit infuses all aspects of Special Operations units, from special forces per se, who directly engage in combat operations, to those in support of the forces (Marquis, 1997). Such stronger unit cohesion and informal social interactions suggest that they benefit from unique targeted forms of social support that help buffer the negative outcomes of combat-related stressors. To help address the need to better understand how social support mechanisms interplay with military health outcomes (Lehavot, Der-Martirosian, Simpson, Shipherd, & Washington, 2013), the current study examines whether perceived so-

cial support and personal morale are associated with symptoms of posttraumatic stress disorder (PTSD) and depression among elite U.S. Army Special Operations Command personnel. Social Support Social support consists of one’s overall social network (e.g., friends, family, work colleagues) and its associated functional outcomes (e.g., emotional support; Uchino, 2006). Social support, whether perceived or tangible, moderates behavioral and physiological stress response outcomes (Hobfoll, 2002; Iversen et al., 2008; Lazarus & Folkman, 1984; Schaefer, Coyne, & Lazarus, 1981; Uchino, 2006; Uchino, Cacioppo, & Kiecolt-Glaser, 1996). In general, higher levels of perceived social support are associated with both improved general health (Cohen, Doyle, Skoner, Rabin, & Gwaltney, 1997; Cohen & Wills, 1985) and improved mental health (Cruwys et al., 2014, 2013; Lehavot et al., 2013) outcomes. Social support has also been demonstrated to be a protective factor for PTSD and depression following a military deployment (Brewin, Andrews, & Valentine, 2000; Giacco, Matanov, & Priebe, 2013; Kilbourne et al., 2007; King, King, Fairbank, Keane, & Adams, 1998; Lehavot et al., 2013; Siebold, 2006; Pietrzak, Johnson, Goldstein, Malley, & Southwick, 2010), and its positive effects on negating PTSD risk appear to become stronger over time (Ozer, Best, Lipsey, & Weiss, 2003). Low levels of perceived social support may have a particularly strong negative effect on PTSD outcomes among military personnel compared to civilians (Brewin et al., 2000), with evidence suggesting that perceived social support is a stronger protective factor following a combat-related traumatic event compared to a noncombat-related traumatic event (Ozer et al., 2003). Despite the noted importance of social support in buffering against the impact of stressful environments or experiences (Cohen & Wills, 1985), surprisingly little research has distinguished between the different sources of social support and their impact on combat-related stress. Different sources of support are known to differentially affect the experience and management of stress; for instance, work-related stress is better buffered by support from coworkers or supervisors (i.e., work-related social

SOCIAL SUPPORT AND MENTAL HEALTH OUTCOMES

support; Fenlason & Beehr, 1994). Yet, these distinctions have not been explored in research on combat-related stress. In the military environment, job-related support is best captured in terms of unit-level social support, which is an important aspect of military culture and doctrine and underlies strong unit cohesion and morale (Britt, Adler, Bliese, & Moore, 2013; Griffith, 1989). A service member’s relationships with unit leadership and peers are core dimensions of unit cohesion (Griffith, 2002; Manning, 1991). Such cohesion reflects a group’s propensity to steadfastly work as a collective in order to achieve an objective (Carron & Brawley, 2000; Carron, Brawley, & Widmeyer, 1998). For military personnel, higher levels of perceived unit cohesion are associated with decreased noncombat-related PTSD symptoms and lower levels of general psychological distress (Brailey, Vasterling, Proctor, Constans, & Friedman, 2007; Halverson, Bliese, Moore, & Castro, 1995; Mulligan et al., 2010). Strong unit cohesion is also associated with greater wellbeing, work performance, perceptions of unit combat readiness, identification with one’s unit, general job satisfaction, and increased retention levels (Cota, Evans, Dion, Kilik, & Longman, 1995; Griffith, 2002; Halverson et al., 1995; Mullen & Copper, 1994; Oliver, Harman, Hoover, Hayes, & Pandhi, 1999). Because military members have shared experiences, unit-level support may be helpful in dealing with stress that has common causes, such as combat-related experiences. Indeed, Calhoun and Tedeschi (2004) found that those individuals who lived through similar traumatic experiences have more credibility, and their support can help others within the group or unit confront questions of meaning and incorporate new perspectives. Support external to the work environment, such as from family and friends, can also affect work-related stress. These cross-domain relations are well documented in industrial psychology (Ford, Heinen, & Langkamer, 2007); for instance, greater family support is associated with lower family work conflict (Adams, King, & King, 1996). In general, research on occupational stress has identified social support from outside work has less useful than work-related social support to deal with job-related stressors (Fenlason & Beehr, 1994). At the same time, however, excessive discussion of work-related

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problems within the workplace context can increase negative outcomes as well as positive outcomes (Haggard, Robert, & Rose, 2010). For instance, excessive discussion of work-related stressors within the work context may increase rumination, the tendency to perseverate on stressors and other self-related negative thoughts (Nolen-Hoeksema & Davis, 1999). Despite evidence suggesting that social support is related to positive mental health outcomes among service members, prior research has been mixed regarding the relative role of work-related and peer- and family-related social support. Additionally, the degree to which specific occupational subpopulations within the military perceive and respond to differing social support mechanisms (e.g., unit-level support vs. family-level support) has not been examined (Smith, Benight, & Cieslak, 2013). Such knowledge could assist health care providers, commanders, and policymakers in better incorporating key facets of social support in training and across the continuum of comprehensive behavioral health care and well-being development (Kilbourne et al., 2007; Price, Gros, Strachan, Ruggiero, & Acierno, 2013). Morale Morale is a complex construct affected by dynamic physical and mental conditions, which makes it difficult to operationalize (Sanford & Holt, 1943); however, in its basic form, morale has been defined as “a character of the will in reference to a particular undertaking . . . a measure of one’s disposition to give one’s self to the objective in hand” (Hocking, 1941, p. 303). In a military environment, morale can be considered a reflection of service members’ level of enthusiasm, energy, and motivation to fulfill their mission objectives (Britt & Dickinson, 2006; North Atlantic Treaty Organization [NATO], 2008). Maintaining high personal morale enables service members to better cope with stressful situations (Brailey, Vasterling, Proctor, Constans, & Friedman, 2007); it lowers general stress levels as well as reduces the impact of combat experiences (CEs) on posttraumatic stress outcomes (Britt et al., 2013; NATO, 2008). Similarly, promoting high unit morale improves unit cohesion and personal morale (Maguen & Litz, 2006), which in turn increases operational effectiveness and perceptions of so-

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cial support among unit members (Gal, 1986; Griffith, 2002; Manning, 1991; Motowidlo & Borman, 1978; Strachan, 2006) and further serves to reduce negative mental health outcomes, including PTSD (Jones et al., 2012).

Respondents were also informed that they could skip any questions that make them uncomfortable and withdraw from the study at any time. Those wishing to participate in the study were required to sign an informed consent form that was maintained separately from the surveys.

Current Study Measures The current study examined perceptions of social support (friends, family, and unit support) and personal morale among active duty U.S. Army Special Operations personnel. It was hypothesized that higher levels of social support and personal morale would (a) independently be associated with lower severity of PTSD and depressive symptoms after controlling for demographic characteristics and CEs and (b) moderate (reduce) the impact of CEs on those outcomes. Method Participants After obtaining approval from the Uniformed Services University and Fort Bragg Institutional Review Boards, active duty U.S. Army Special Operations personnel stationed at Fort Bragg, home of the U.S. Army’s Special Operations and airborne forces, were recruited between 2009 and 2011. A noninvasive recruitment table (i.e., potential respondents approached the table on their own initiative) was set up in the lobby of areas where Special Operations personnel routinely passed when coming and going from their work areas. Respondents who exhibited interest in the recruitment table were briefed about the purpose of the study and invited to complete an anonymous self-report survey. Respondents were informed that participation was voluntary and that their command would not be informed about their participation or provided any respondent data. To maximize participation and confidentiality, we deidentified surveys with a sequential number (e.g., SOC123) that provided anonymity but allowed data linkage; the sequential numbers cannot be traced back to individual respondents. Respondents were informed that should they feel distressed while completing the survey, they should seek help through the resources available locally and a card containing the contact information for these resources was provided.

Combat experiences. CEs were assessed using a 27-item version of the validated Combat Exposure Scale (CES), which covers a broad range of potentially traumatic deploymentrelated events (e.g., being attacked or ambushed; Britt et al., 2013; Hoge et al., 2004). Respondents indicated whether they experienced each event while on an operational deployment. Positively endorsed events were summed to create a total CES score. For the current sample, the CES demonstrated strong internal consistency (␣ ⫽ .96). A high score on this scale signals that respondents had encountered multiple traumatic events during deployment, whereas a low score reflects fewer exposures to combat-related stressors. Mental health. PTSD symptom severity was assessed with the PTSD Checklist— Civilian version (PCL–C; Weathers, Litz, Herman, Huska, & Keane, 1993). Although a military version of the PCL–C exists, the civilian version was chosen to capture PTSD symptoms related to both military and nonmilitary traumatic events. The PCL–C comprises 17 items representing diagnostic criteria according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM–IV–TR; American Psychiatric Association, 2000) for the three PTSD symptom clusters (reexperiencing, avoidance, hyperarousal). Respondents rated each item on a 5-point scale ranging from 1 (not at all) to 5 (extremely) according to how much they had been bothered by that problem in the past month. Items were summed to create scores for total PTSD symptom severity and each PTSD symptom cluster. For the current sample, the PCL–C demonstrated strong internal consistency (␣ ⫽ .94). Severity of depressive symptoms was assessed with the Primary Care Evaluation of Mental Health Disorders Patient Health Questionnaire–9 (PHQ-9; Kroenke & Spitzer, 2002), which corresponds to DSM–IV–TR criteria for major depressive disorder. Respondents indi-


cated on a 4-point scale ranging from 0 (not at all) to 3 (nearly every day) how much they had been bothered by each symptom in the past 2 weeks. Items were summed to create a total score that was then used in the analyses. For the current sample, the PHQ-9 demonstrated strong internal consistency (␣ ⫽ .88). Social support. Prior research has relied on either global measures of social support or structural measures of social support. Global measures capture perceived support emerging from a range of sources, from coworkers, neighbors, relatives, and close friends to institutional memberships (for a review, see Cohen & Wills, 1985), whereas structural measures assess more specific sources, for instance whether one is in an intimate relationship, the presence of others in the same household, or a quantitative count of social connections. Global measures, which have been shown to be more predictive of stress-related buffering, were preferred here. Respondents completed a four-item measure in which they were asked to “rate the degree of emotional and practical support” they receive from different sources (friends, family, supervisors, coworkers) using a 4-point Likert-type scale ranging from 0 (none) to 4 (a great deal). The single-item measures of perceived family and friend support were included as separate variables in all analyses, whereas the two items assessing supervisor and coworker support were examined both individually and as a combined (averaged) measure of perceived “unit” support (␣ ⫽ .88). Each social support measure was treated as a continuous variable, ranging from low (0) to high (4). Morale. Perceptions of personal morale were assessed using an established single-item measure that asked respondents to rate “your personal morale” on a 5-point scale ranging from 1 (very low) to 5 (very high; Office of the Surgeon Multi-National Force-Iraq and Office of the Surgeon General United States Army Medical Command, 2008). This measure was also treated as a continuous variable. Analytic Approach The dependent variables, PTSD symptom severity and depression, were examined using linear regression in two steps. In Model 1, only main effects of CEs, personal morale, and the social support variables (i.e., unit,

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friends, and family) were included, along with demographic covariates (age, gender, education, and marital status). In Model 2, the main effects as well as the two-way interactions were included to allow an assessment of increases in variance explained between Models 1 and 2. The interaction terms were computed using cross-products of the number of CEs and each of the personal morale, unit support, friends’ support, and family support variables in order to assess the potential moderating effect of these variables on the relationships between CEs and mental health outcomes. In this study, and in line with the extant literature, PTSD and depressive symptoms were correlated at .74 (see Table 1). Given that the support and morale variables were correlated (see Table 1), individual regression models were also run with each support variable (and interaction with CEs) on its own to isolate the effects of each on the dependent variable and ensure that their impact on the dependent variable was accurately represented in the full model presented in Table 2. These individual models revealed beta coefficients of the same valence and order as the results from the complete model; hence, for ease of reporting, the full model findings are described in the next section, and the results for individual models are discussed as relevant. SPSS Version 22.0 was used for all analyses. Results Sample Demographics The current study includes self-report data from only respondents who indicated having experienced at least one operational combat deployment (n ⫽ 537). The majority of the respondents were White (72.1%), male (88.1%), and married (65.4%). The sample’s rank distribution was as follows: 23.8% junior enlisted (E1–E4), 35% noncommissioned officers (E5– E6), 19.2% senior noncommissioned officers (E7–E9), and 21.6% commissioned officers. Although dependent on voluntary participation, the sample provides a large range of military occupational specialties (MOSs; 102 different MOSs), reflecting the diversity of specialties within the Special Operations community (Marquis, 1997); 48.4% of the participants held a Special Forces MOS, and the re-

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Table 1 Mean, Standard Deviations and Correlations between Social Support Variables, Mental Health Outcomes, Age and Combat Experiences Variable 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.

Personal morale Family support Friends support Unit support Coworkers support Supervisors support PHQ-9 PCL–C total PCL–C intrusion PCL–C avoidance PCL–C hyperarousal Combat experiences Age

Measure range

M (SD)

2

3

4

7

8

12

13

1–5 0–4 0–4 0–4 0–4 0–4 9–35 16–85 5–25 7–35 5–25 0–24 18–57

3.69 (1.00) 3.50 (.87) 3.20 (.98) 2.76 (1.06) 2.82 (1.06) 2.70 (1.18) 12.84 (4.93) 28.27 (12.41) 7.87 (3.77) 11.29 (5.57) 9.08 (4.38) 2.26 (5.01) 30.90 (7.34)

.34ⴱ

.37ⴱ .56ⴱ

.47ⴱ .40ⴱ .59ⴱ

⫺.53ⴱ ⫺.27ⴱ ⫺.35ⴱ ⫺.38ⴱ ⫺.36ⴱ ⫺.37ⴱ

⫺.44ⴱ ⫺.19ⴱ ⫺.28ⴱ ⫺.30ⴱ ⫺.28ⴱ ⫺.28ⴱ .74ⴱ

⫺.02 .07 .11ⴱ .10ⴱ .12ⴱ .07 .03 .10ⴱ .12ⴱ .05 .11ⴱ

.13ⴱ .01 .11ⴱ .16ⴱ .16ⴱ .15ⴱ ⫺.13ⴱ ⫺.08 ⫺.08 ⫺.11ⴱ ⫺.04 ⫺.01

Note. PHQ-9 ⫽ Primary Care Evaluation of Mental Health Disorders Patient Health Questionnaire–9; PCL–C ⫽ PTSD Checklist—Civilian version. ⴱ p ⬍ .05.

mainder held support specialties (e.g., chemical, biological radiological, and nuclear specialists). Mean comparisons on the key independent variables showed that Special Forces and support MOSs did not differ in any of the measures of social support or on levels of personal morale, ts(523) ⬍ 1.33, p ⬎ .05. The means of all independent and dependent variables, as well as correlations, are presented in Table 1. A total of 8.6% of respondents met the criterion for PTSD diagnosis (PCL–C score of 50 or above), which is lower than that for the general military population (Hoge, Riviere, Wilk, Herrell, & Weathers, 2014). Age was negatively correlated with the severity of depressive symptoms and PTSD avoidance symptoms but positively correlated with personal morale and the friends and unit support measures. Table 2 reports means of all independent and dependent variables by gender, marital status, ethnicity, education, and rank, as well as t tests and analyses of variance assessing gender, marital status, ethnicity, education, and rank differences. No systematic differences emerged on the basis of these demographic covariates, except in terms of rank and education levels, as noted in Table 2. These differences are discussed further later. The absence of gender differences in PTSD levels despite lower CEs is noteworthy and may be attributed to greater incidence of lifetime noncombat related trauma. For instance, a significantly greater proportion

of women in the sample (34.5% of women vs. 3% of men), ␹2(1) ⫽ 84.03, p ⬍ .05, reported having experienced or having witnessed sexual assault at one point during their life, that is, not necessarily during their military service. The primary PTSD and depression analyses (reported in the next section) controlled for the following background variables: Special Forces versus support MOSs (coded as 0/1), education, gender, age, and marital status. PTSD Results Table 3 reports all the beta coefficients for the main effect models and the interactive models, and the significant moderating effects are depicted visually in Figures 1–3, which reflect main effects and interactions. The interaction models indicate that the relationship between CEs and PTSD was moderated by several of the social support variables as well as by personal morale, at times in a counterintuitive direction. In the full model, family support had no main or interactive effect on PTSD symptom severity, although this may have been because scores on the measure were positively skewed (mean of 3.5 on a 4-point scale). Personal morale reduced the relationship between CEs and PTSD symptom severity: When the interaction term was added in Model 2, the main effect of personal morale was not significant, but the interaction term was; in other


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Table 2 Differences in Combat Experiences, Mental Health Outcomes and Social Support Variables by Key Demographic Variables Characteristic Gender Male (88.1%) Female (11.8%) t test Education ⱕ HS diploma (21.8%) Some college or 2-year degree (48.0%) ⱖ Bachelor’s degree (30.2%) F test Ranka E1–E4 (23.8%) E5–E6 (35.0%) E7–E9 (19.2%) Officers (21.6%) F test Marital status Single (34.6%) Married (65.4%) t test Race White (72.1%) Black (15.9%) Other (Native, Asian; 12%) F test Ethnicity Hispanic (20.3%) Non-Hispanic (79.7%) t test

Combat experiences

Depression

PTSD

Personal morale

Unit support

Friend support

Family support

12.31 5.06 5.96ⴱ

12.63 14.40 2.59ⴱ

27.90 30.45 ns

3.72 3.43 2.05ⴱ

2.79 2.50 ns

3.23 3.02 ns

3.52 3.32 ns

10.20 11.39 12.72 ns

13.60 13.10 11.80 4.26ⴱ

30.54 29.23 25.52 5.25ⴱ

3.42 3.70 3.83 4.18ⴱ

2.54 2.80 2.78 ns

3.12 3.24 3.23 ns

3.51 3.48 3.62 ns

5.04 11.27 16.64 13.52 35.61ⴱ

14.40 13.16 12.10 11.46 6.60ⴱ

30.88 29.53 28.02 24.67 4.65ⴱ

3.44 3.61 3.79 3.92 4.03ⴱ

2.46 2.64 3.15 2.80 6.58ⴱ

3.05 3.09 3.49 3.33 4.20ⴱ

3.44 3.46 3.61 3.67 ns

12.52 9.66 3.53ⴱ

13.61 12.47 2.48ⴱ

29.24 27.65 ns

3.47 3.80 3.46ⴱ

2.69 2.78 ns

3.13 3.24 ns

3.40 3.54 ns

13.05 7.38 8.14 5.74ⴱ

12.83 13.42 12.79 ns

28.33 29.56 28.64 ns

3.70 3.58 3.64 ns

2.80 2.70 2.72 ns

3.18 3.12 3.29 ns

3.54 3.47 3.49 ns

9.65 12.19 5.19ⴱ

12.22 13.04 ns

28.32 28.69 ns

3.69 3.69 ns

2.70 2.71 ns

3.18 3.21 ns

3.49 3.53 ns

Note. PTSD ⫽ posttraumatic stress disorder; HS ⫽ high school; ns ⫽ nonsignificant. a E1–E4 ⫽ junior enlisted; E5–E6 ⫽ noncommissioned officers; E7–E9 ⫽ senior noncommissioned officers; Officers ⫽ commissioned officers. ⴱ p ⬍ .05.

words, the hypothesis that personal morale moderates the relationship between CEs and PTSD was supported. However, there was no direct effect of personal morale on PTSD when this interaction was accounted for. As depicted in Figure 1, personal morale moderated the relationship between CEs and PTSD; specifically, when personal morale was high, CEs were not related to PTSD, whereas when personal morale was low, CEs had a strong positive relationship with PTSD. Support from friends had a similar buffering effect. As shown in Figure 2, the greater degree of perceived support from one’s friends was linked to lower levels of overall PTSD (main effect), and it reduced the relationship between CEs and PTSD (interaction).

Unit support also affected PTSD symptom levels; however, its impact on the relationship between CEs and PTSD was different from that from personal morale or friends’ support. Specifically, the moderating role of unit support was such that greater levels of unit support were linked to more positive relationships between CEs and PTSD. This suggests, counterintuitively, that the more individuals felt that their unit was supportive, the more CEs were related to their level of PTSD. To investigate this finding further, we also ran regressions with the two items constituting the unit support scale assessed separately to establish the independent roles of the scale’s components (coworker and supervisor support). These post hoc regressions indicated that, even though the interaction terms were not significant, the same

Total

47.26 (5.24)ⴱⴱ .946 (.314)ⴱⴱ .939 (1.070) ⫺.919 (1.07) ⫺3.43 (.980)ⴱⴱ ⫺1.85 (.99) .254 (.073)ⴱ ⫺.013 (.091) ⫺.159 (.086) ⫺.184 (.069)ⴱⴱ

52.47 (4.17)ⴱ .420 (.071)ⴱⴱ .419 (.742) ⫺2.27 (.709)ⴱⴱ ⫺.899 (.644) ⫺3.77 (.644)ⴱⴱ

␤ (␴)

.293

.271

Adj R2

Intrusion

12.65 (1.74) .236 (.104)ⴱ .080 (.356) ⫺.113 (.355) ⫺1.00 (.326)ⴱⴱ ⫺.419 (.329) .071 (.024)ⴱ ⫺.003 (.031) ⫺.043 (.029) ⫺.050 (.023)ⴱ

13.64 (1.375) .135 (.023)ⴱ ⫺.057 (.245) ⫺.434 (.234) ⫺.311 (.212) ⫺.869 (.199)ⴱⴱ

␤ (␴)

.202

.191

Adj R2

Avoidance ␤ (␴)

19.92 (2.34)ⴱ .386 (.140)ⴱ .621 (.479) 456(.477) ⫺1.332 (.477)ⴱ ⫺1.105 (.443)ⴱ .098 (.033)ⴱ ⫺.026 (.041) ⫺.063 (.039) ⫺.073 (.031)ⴱ

22.27 (1.85)ⴱ .129 (.032)ⴱ .233 (.330) ⫺.922(.315)ⴱ ⫺.354 (.286) ⫺1.801 (.269)ⴱ

PTSD

.259

.245

Adj R2

14.69 (1.92)ⴱ .343 (.115)ⴱ .239 (.391) ⫺.350 (.390) ⫺1.105 (.358)ⴱ ⫺.330 (.362) .089 (.027)ⴱ .621 (.479) ⫺.456(.477)ⴱ ⫺.076 (.025)ⴱ

16.656 (1.528)ⴱ .157 (.026)ⴱ .243 (.273) .918 (.260)ⴱ ⫺.234 (.236) ⫺1.10 (.221)ⴱ .256

.230

Adj R2

Hyperarousal ␤ (␴)

Depression

22.998 (1.97)ⴱ .259 (.118)ⴱ .480 (.405) ⫺.736 (.396) ⫺.889 (.365)ⴱ ⫺1.499 (.374)ⴱ .029 (.027) ⫺.016 (.034) ⫺.013 (.032) ⫺.047 (.026)

25.08 (1.546)ⴱ .065 (.025)ⴱ .249 (.268) ⫺.785 (.264)ⴱ ⫺.611 (.239)ⴱ ⫺2.046 (.226)ⴱ

␤ (␴)

.342

.341

Adj R2

Note. PTSD was measured with the PTSD Checklist—Civilian version, and depression was measured with the Primary Care Evaluation of Mental Health Disorders Patient Health Questionnaire–9. Special Forces (support 0/1), education, gender, age, and marital status were controlled for in all analyses. PTSD ⫽ posttraumatic stress disorder; Adj ⫽ adjusted; CEs ⫽ combat experiences. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01.

Model 1 main effects Constant CEs Family support Friend support Unit support Personal morale Model 2 main effects and interactions Constant CEs Family support Friend support Unit support Personal morale CEs ⫻ Unit Support CEs ⫻ Family Support CEs ⫻ Friend Support CEs ⫻ Personal Morale

Model effects and interactions

Table 3 Regression Coefficients for PTSD and Depression Model Outcomes

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PT SD S ymptom Severity


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Low Personal Morale High Personal Morale

Figure 1. Interaction of combat experiences (CE) and personal morale on posttraumatic stress disorder (PTSD) symptom severity. This slope analysis visually represents PTSD symptom severity means plotted for values of ⫺1 and ⫹1 standard deviation from the mean of the independent variable.

PTSD Symptom Severity

pattern emerged, with positive beta coefficients for the interaction terms. To further investigate these dynamics, we ran the same multivariate regressions on each of the PCL–C subscales (i.e., intrusion, avoidance, and hyperarousal). These analyses indicated that these moderating effects occurred for each PTSD symptom cluster; for instance, in relation to friends’ support, the main effect in Model 1 masked an interaction effect, which was revealed in Model 2: Friends’ support reduced the relationships between CEs and PTSD, and this was specifically driven by its reduction of the

relationship between CEs and the hyperarousal dimension of the PCL–C measure. Depression Results The regressions of depression symptom severity revealed that it, too, was directly and negatively linked to CEs (see Table 2). In addition, depression was lower when Special Operations personnel perceived high levels of friend support, unit support, and personal morale. The individual regression model with only family support, CE, and their interaction

Low Friend Support High Friend Support

Figure 2. Interaction of combat experiences (CE) and friend support on posttraumatic stress disorder (PTSD) symptom severity. This slope analysis visually represents PTSD symptom severity means plotted for values of ⫺1 and ⫹1 standard deviation from the mean of the independent variable.

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PTSD Symptopm Severity

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Low Unit support High Unit support

Figure 3. Interaction of combat experiences (CE) and unit support on posttraumatic stress disorder (PTSD) symptom severity. This slope analysis visually represents PTSD symptom severity means plotted for values of ⫺1 and ⫹1 standard deviation from the mean of the independent variable.

revealed a main (negative) effect of family support that was qualified by a marginally significant (also negative) interaction with CE (p ⫽ .06); hence, it appears that family support was a particularly important buffer for depression in general (main effect) but also a buffer for the impact of traumatic experiences on depression symptoms (interaction). The absence of other significant interactions in the full model suggests that other kinds of support and personal morale did not moderate the impact of CEs on depression, unlike what was found with PTSD. Discussion This study found that social support from friends and personal morale were related to lesser negative mental health outcomes of depression and PTSD among Special Operations personnel. The secondary analyses in this study suggest that the relationship between friend support and PTSD is in fact indirect: As with having high personal morale, perceptions of high support from friends is linked to a lesser relationship between potentially traumatic CEs and PTSD levels. In the case of personal morale, the moderating effect was such that, when morale was high, CEs were not significantly related to PTSD. The study therefore indicates that informal (i.e., noninstitutionalized or professional care) forms of social support, especially from friends, are important to Special Operations personnel

who have experienced potentially traumatic combat events during their deployments. Interestingly, in contrast to the buffering effect of friend support, higher levels of unit support appear to exacerbate the negative effects of CEs in relation to PTSD outcomes: For those who perceived strong unit support, the relationship between CEs and PTSD was of greater magnitude than for those who perceived lower levels of unit support (the slope is higher, as seen in Figure 1). The positive correlations between CEs and support from both friends and coworkers (i.e., fellow soldiers; see Table 1) suggest that CEs and camaraderie are inherently related: It may be that Special Operations personnel with strong perceived unit support spend more time reminiscing about their military experiences or about specific combat events with their peers, thus reinitiating the potentially traumatic stress response and symptoms they developed during deployment, resulting in higher intrusive thoughts (a PCL–C domain) and therefore higher PCL–C scores. The correlational nature of the data does not allow causality to be assessed here, but future research should further explore this potential explanation. Theoretical Implications By highlighting the importance of informal types of social support, especially from friend networks, the study contributes to a growing body of research on the role of friend and family


networks in palliating work-related stress. In parallel, the study offers novel and perhaps counterintuitive insights into the potentially negative effects of seeking and getting support for work-related stressors within the work environment. These findings are consistent with the rumination process identified in previous research (Nolen-Hoeksema & Davis, 1999), whereby excessive sharing of work-related stressors within the work context is detrimental to mental health. This finding is especially important within the military context, because it signals that strong camaraderie and shared experiences among soldiers could exacerbate combat-related stressors instead of being beneficial, as some prior research would have suggested (Tedeschi & Calhoun, 2004; Tedeschi, Calhoun, & Cann, 2007). These findings also provide a basis for extending the surprisingly scant research on the relative importance of social support emanating from family or friends versus from the workplace. Although it is understood that research on social support should always consider the range of sources available to those facing stressors (Cohen & Wills, 1985; Ford et al., 2007), these findings point to the need for further exploration of cross-domain sources of support (e.g., family support for work-related stressors and workbased support for family-related stressors). Practical and Policy Implications Despite numerous formal programs that aim to prevent postdeployment mental health concerns and care for those service members who do experience them, one in six service members are still burdened by such issues, and many do not seek formal care (Hoge, 2011). Reducing the burden of postdeployment mental health concerns may require a paradigm shift from strictly traditional treatment models to ones that promote more flexible and informal support (Kudler, 2007). Although there may be a multitude of social support sources available to service members (e.g., friends, family, professional care), not all of these sources are actively sought out or are equally efficacious in improving outcomes (Overdale & Gardner, 2012; Schnurr, Lunney, & Sengupta, 2004). It is not always possible to identify those in need of social support, nor is it always feasible to guide individuals into specific social support contexts

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(Hoge & Castro, 2012); therefore, building an organizational culture that encourages more informal social support could prove extremely important, especially when considering that service members are neither seeking nor fully utilizing the more formal forms of social support (Vogt, 2011). Finally, it is important for policymakers and treatment providers to better understand the specific types of social support that veterans are receiving and the varying effects on outcome that these supports may contribute in order to better provide comprehensive care (Kilbourne et al., 2007; Lehavot et al., 2013). This study’s findings suggest that programs aimed at increasing morale and that encourage friend support (i.e., with people outside of the unit) may improve mental health outcomes among highly operational service members with considerable CEs. Although unit-level support may also be important, it appears that it does not necessarily predict better PTSD outcomes in this population. It is possible that the absence of a unitlevel buffer in this study is related to a shared stigma that precludes help seeking from supervisors and fellow soldiers. Limitations and Future Research A primary limitation to the current study is that the findings are based on cross-sectional data, precluding determinations about causality. It is unclear, for example, whether low levels of perceived social support and personal morale lead to subsequent increases in PTSD or depressive symptoms, whether increased psychological distress reduces perceptions of support and morale, or whether there is a reciprocal relationship between distress and perceptions of social support and morale. Longitudinal research will help clarify the relationships among these variables. In addition, the recruitment procedures and the voluntary nature of study participation reflect a convenience sample, which may carry an inherent participation bias. Indeed, it is possible that those with greater mental health problems elected not to participate. Future research could address this limitation by employing more systematic measurement of the entire military population. As in previous research, the association between mental health problems and social support was examined in relation to perceived and not actual support. Although using such global measures of social

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support is consistent with those in previous research, it should be supplemented in the future by more direct measures of social support, through observations or diaries of social interactions (Cohen & Wills, 1985). Notwithstanding the absence of systematic differences between Special Forces and support MOSs in any of the social support measures, the covariate capturing the difference between these two groups was significantly related to the final health outcomes. Hence, despite many similarities in perceptions of social support and in how it interacts with combat and deployment-related stressors in affecting overall health outcomes, there may be other differences between how these communities rely on social support mechanisms. Further research on the Special Forces community should explore additional distinctions in the experiences of serving in a support function versus in the Special Forces per se in how the sense of community develops and evolves and ultimately contributes to resilience. Qualitative measures of social support would also allow a better understanding of the actual nature and content of the social interactions to establish the exact mechanism for why and how social support buffers the mental health impact of combat-related stressors. If the association is driven primarily by perceptions of social support, then interventions based on objective elements of social support (e.g., number of friends within one’s unit, amount of time spent with other service members, or a supervisor’s leadership style) may be warranted. A more refined assessment of the different dimensions of the complex constructs investigated in this study may provide useful information about how interventions might be tailored to reduce risk and enhance resilience. Conclusion Countries around the world are increasing their reliance on Special Operations personnel in a widening variety of roles across the military spectrum (Svendsen, 2014). As such, more efforts are warranted to better understand the risk and protective factors unique to this force’s readiness. This research suggests that military leaders may need to consider implementing targeted social support programs to help mitigate mental health outcomes.

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