ABSTRACT
Benefit finding has been identified as a buffer of the combat exposure-PTSD symptom link in soldiers. However, benefit finding may have a limited buffering capacity on the combat-PTSD symptom link over the course of a soldier’s post-deployment recovery period. In the present study, soldiers returning from Operation Iraqi Freedom (OIF) were surveyed at two different time periods post-deployment: Time 1 was 4 months post-deployment (n = 1,510), and Time 2 was at 9 months post-deployment (n = 783). The surveys assessed benefit finding, PTSD symptoms, and combat exposure. Benefit finding was a successful buffer of the cross-sectional relationship between combat exposure and PTSD reexperiencing symptoms at Time 1, but not at Time 2. In addition, the benefit finding by combat interaction at time 1 revealed that greater benefit finding was associated with higher symptoms under high combat exposure at Time 2 after controlling for PTSD arousal symptoms at Time 1. The results of the present study indicate that benefit finding may have a buffering capacity in the immediate months following a combat deployment, but also indicates that more time than is allotted during the post-deployment adjustment period is needed to enable recovery from PTSD. Theoretical implications are discussed.
KEYWORDS: Combat stress, PTSD symptoms, military, benefit finding, posttraumatic growth
What is the public significance of this article?—Benefit finding is a positive psychological coping mechanism for moderating the combat PTSD symptom link in soldiers. However, benefit finding failed to buffer this link across the postdeployment period and may function as a limited buffer of combat-related PTSD symptoms during early postdeployment adjustment periods.
Military personnel who have recently returned from deployment face many challenges that make readjustment to the home environment difficult, such as coping with mental health problems related to combat exposure (Thomas et al., 2010). Moreover, prolonged military campaigns that require multiple rotations may need longer recovery time (MacGregor et al., 2012).
Despite these challenges military personnel often utilize cognitive coping strategies to manage the aftermath of war. One such strategy is to perceive how the stress of combat may be beneficial (Aldwin et al., 1994). This approach, known as benefit finding, is attitudinally equated to Nietzsche’s oft-quoted aphorism, “that which does not kill us makes us stronger,” and more recently to concepts such as adversarial growth, thriving, blessings, positive-by-products, positive adjustment, posttraumatic growth (PTG), positive adaptation, and psychological resilience (Linley & Joseph, 2004). Although a few studies have examined the buffering effects of benefit finding on the combat-PTSD symptom link (Aldwin et al., 1994; Wood et al., 2012a; Wood et al., 2012b), current theory suggests that benefit finding may buffer stressor–strain relationships at different times during the posttrauma recovery period (Helgeson et al., 2006; Zoellner & Maercker, 2006). Furthermore, evidence indicates that benefit finding may moderate or promote PTSD symptom clusters (reexperiencing, avoidance, and arousal) at different times during a recovery period (Helgeson et al., 2006; Zoellner & Maercker, 2006); thus, multi-time point examination of data may clarify the role of benefit finding on the combat exposure-PTSD symptom relationship. Currently, no studies have examined benefit finding as a moderator of the combat-PTSD link across the post-deployment dwell-time period. The current study seeks to fill this gap by examining the role of benefit finding as a coping mechanism to enable adjustment to the stress of postdeployment. Thus, we investigated the impact of benefit finding as a buffer/promoter of the combat – PTSD symptom link at different points during the post-deployment recovery period for active-duty military personnel.
In civilian and military samples, studies have identified benefit finding as a predictor of improved health outcomes over time (Tartaro et al., 2005). Additional investigations sought to clarify whether benefit finding functions as a coping mechanism to buffer the stressor-mental health outcome link; however, these studies have yielded conflicting results. In fact, a growing number of studies have found evidence both for and against benefit finding as a moderator of the stressor-health link in both cross-sectional (Siegel & Schrimshaw, 2007; Wood et al., 2012a) and longitudinal studies (Tennen et al., 1992).
Siegel and Schrimshaw (2007) examined benefit finding as a moderator of the relationships among stressors (AIDS symptoms and social conflict) and distress outcomes (anxiety and depression) in 138 women living with HIV/AIDS-related symptoms. Their findings revealed that benefit finding was a successful buffer of AIDS symptoms on distress outcomes in women with high distress. However, benefit finding failed to reduce distress related to social conflict. The authors concluded that benefit finding possesses stress-buffering properties that may be specific to the severity of the stressor.
Wood et al. (2012b) identified benefit finding as a buffer of the combat-PTSD symptom link but only under conditions of supportive officer leadership in a cross-sectional sample of soldiers 4 months following their last deployment. Thus, benefit finding may be a more effective buffer of stress when other coping resources are available. Lastly, Helgeson et al. (2006) examined the relationships of benefit finding to psychological and physical health in a meta-analysis of 87 cross-sectional studies. Benefit finding predicted less depression, more positive well-being, and more intrusive and avoidant thoughts about the stressor. However, the authors noted that inconsistencies in benefit finding as a predictor of improved health may be driven by misinterpretation of intrusive and avoidant thoughts as a marker of distress rather than a cognitive process to understand traumatic events (Krans et al., 2009). Thus, PTSD symptom clusters (reexperiencing, avoidance, and arousal) may be affected by benefit finding and have different recovery trajectories over time.
These conflicting findings may be explained by a combination of stressor level, stressor frequency, and recovery time. For example, models of post-traumatic growth and benefit finding indicate that stressors of high impact are essential for the generation of growth. Folkman (2008) described the function of meaning-focused constructs, like benefit finding and PTG, as a product derived from suffering. This meaning-focused coping approach draws on one’s beliefs, values, and existential goals to motivate and sustain coping and well-being. Thus, motivation derived from meaning may restore energy to reengage problems through sustaining cognitive strategies, replenishing coping efforts, and restoring self-confidence. Benefit finding and PTG represent a form of meaning-based coping that may provide individuals with positive energy for coping with life demands.
Benefit finding and PTG are similar meaning making constructs that perform slightly different cognitive adaptation functions. Although meta-analysis and review articles have grouped both benefit finding and PTG together as similar meaning making constructs (Helgeson et al., 2006; Linley & Joseph, 2004), recent literature has highlighted important differences. Benefit finding and PTG are correlated but considered independent constructs that predict different outcomes (Mols et al., 2009). In the study by Mols et al. (2009), PTG predicted variance in life satisfaction while benefit finding did not. Liu et al. (2021) examined benefit finding and PTG prevalence in cancer patients to find broad overlap such that 66% reported moderate-high benefit finding and of those, 20.5% reported moderate-high PTG. Tomich and Helgeson (2006) examined benefit finding over the postcancer recovery period and identified that personal control was a predictor of later benefit finding but only under cases of full remission. In cases of cancer reemergence, personal control predicted a decrease in benefit finding. Liu et al. (2021) similarly found a decrease in the perceived level of benefits following cancer recurrence but found no change in the level of PTG in cancer patients experiencing recurrence. Thus, benefit finding, as a cognitive adaptation strategy, may fail in cases of persistent or recurrent stressor experiences. This notion is supported by Wood et al. (2012a) who identified that benefit-finding diminishes as a buffer of the combat stress-PTSD symptom link in soldiers deployed for a longer time when compared to those deploy for shorter time periods. Thus, benefit finding appears to play a foundational role as an initial coping mechanism to facilitate cognitive adaptation to stress upon which growth may emerge.
The level of stress may function as a mechanism to release energy for cognitive adaptation and coping. Tedeschi et al. (2007) postulated that in order for growth to be derived from challenges, an individual must first undergo sufficient stress to create a reexamination of beliefs, such that one should experience a shattering of his or her “assumptive world.” From this reexamination, individuals may find meaning from their suffering, and regain the perception of control (Affleck & Tennen, 1996). However, the cognitions necessary to drive PTG may be conditional to significant stressors. For example, Gilbert et al. (2004) study examined how individuals manage differing levels of suffering over time. Gilbert et al. theorized that intense hedonic states create the release of psychological energy to abate them, while mild stressors persist. Participants reported that the more they disliked someone who had hurt them (i.e., a transgressor) the longer dislike would last. Participants also predicted that their dislike for the transgressor, who hurt them a-lot, would last longer than for one who hurt them a little. Despite participants’ predictions the opposite occurred.
Thus, benefit finding may function as a temporary mechanism designed to mask novel stressors and generate quick meaningful interpretations to return to pre-stress baseline, while growth may emerge under conditions of severe trauma in which an individual allocates energy in the form of cognitive frameworks to abate them. Zoellner and Maercker (2006) argued that when attempts to cope with stress fail to be effective, some level of positive illusion or self-deception may help maintain the perception of having control over stress reactions. They described this theoretical approach as the Janus-faced model of posttraumatic growth, after the Roman God Janus, depicted as having two opposing faces. In theory, the two opposing views are utilized at the same time in response to the same traumatic situation. The palliative side (positive illusions, self-deception and or avoidance) would increase based upon the level of stress and decrease over time, while the other, more constructive side (healthy adjustment), would increase as time allowed for more integrated processing of experiences and utilization of coping resources.
Zoellner and Maercker’s time dimension may apply to military personnel during their post-deployment recovery period. For example, military personnel return home with few military obligations, i.e., low training requirements, more leave time, and greater access to activities and freedoms not had during the previous deployment. Military personnel emerging from this “romantic period” must readjust to family and military roles which may exacerbate stress and lead to a heightened level of mental health problem rates at 3 to 4 months post-deployment (Bliese et al., 2007). During this period, PTSD symptoms surface in relation to previous combat experiences (Bliese et al., 2007) whereas in later post-deployment periods (around 12 months post-deployment) such reactions and symptoms may reoccur (Thomas et al., 2010).
This study evaluated a series of hypotheses to examine persistence in stress buffering capacity of benefit finding on the combat-PTSD symptom link over the course of a soldier’s post-deployment recovery period. The first series of hypotheses (1, 2, and 3) in this study addressed the conflicting theories focused on stress level, stress recurrence, and postdeployment recovery time. According to Tedeschi et al., the buffering effects of benefit finding on the combat – PTSD symptom link emerge after high stress periods while Helgeson, Reynolds, and Tomich (2006) and Liu et al. (2021) indicated that recurrent stressors would lower the effect of benefit finding. We sought to examine if persistent recurrent stressors, i.e., those found during postdeployment recovery, would limit the buffering effect of benefit finding in later phases of the postdeployment period:
H1: Benefit finding will buffer combat exposure-PTSD link cross-sectionally 4 months following return from a combat deployment (Time 1).
H2: Benefit finding will not significantly buffer the combat exposure-PTSD symptoms link at 9 months postdeployment (Time 2).
H3: Benefit finding at Time 1 will not significantly buffer the combat exposure – PTSD symptoms at Time 2 link after controlling for PTSD symptoms at Time 1.
An additional series of questions were asked to explore when and how stress may influence benefit finding on combat-PTSD symptom cluster (reexperiencing, avoidance, and arousal) trajectories. Zoellner and Maercker (2006) proposed that PTG may influence PTSD symptom cluster trajectories during the recovery process; thus, the avoidant or palliative side of benefit finding may increase when stress is high at 3–4 months postdeployment. In contrast, PTSD symptom trajectories in military populations tend to recover in different phases. For example, Solomon et al. (2009) reported that arousal was predictive of later reexperiencing and avoidance but not visa-versa in war veterans. Thus, arousal symptoms may function as a marker to enable benefit finding as a mechanism for cognitive processing of the stressor event to enable better adjustment over time (Helgeson et al., 2006; Krans et al., 2009). Thus, we also examined whether benefit finding functions to buffer and or amplify of combat – PTSD symptom clusters over Time 1 and Time 2 of a soldier’s postdeployment recovery period. The persistent stressors experienced during Time 2 may be related to a decline in the effectiveness of benefit finding (Tomich and Helgeson, 2006; Liu et al., 2021).
More specifically, does benefit finding moderate the combat-PTSD symptom clusters (reexperiencing, avoidance, and arousal) cross-sectionally at Time 1 and again at Time 2? Does benefit finding at Time 1 moderate the combat exposure-PTSD symptom clusters link at Time 2 after controlling for PTSD symptom clusters at Time 1?
Method
Participants and procedure
Active-duty soldiers from five maneuver squadrons of a Cavalry Regiment were invited to participate in the current study of post-deployment adjustment. Participation involved completing a paper and pencil survey in-garrison 4 months and 9 months following a 15-month deployment to Iraq in 2007–2008. Surveys were anonymous, so a unique code was created by participants to match their responses over the two time periods. The survey took approximately 30-minutes to complete and confidentiality was ensured through the use of individual envelopes. Soldiers were briefed on the purpose and procedure of the study after which 95% of soldiers consented at Time 1 (1,762 of 1,850) and 93% at Time 2 (1,104 of 1,185). Procedures and consent for this data collection were like those used in other survey-based studies with active-duty soldiers (e.g., Thomas et al., 2010). This study was approved by the Institutional Review Board of the Walter Reed Army Institute of Research.
Given that the study was conducted at the regiment level, individual soldiers were not contacted. Soldiers who were unavailable on the day of the follow-up survey because of relocation, military schools, or other duty requirements were not included in the follow-up, resulting in a relatively low follow-up rate typical of such studies (e.g., Adler et al., 2009). In the case of this Regiment, many of the soldiers who had deployed had already been transferred to other locations at 9 months post-deployment. Therefore, soldiers surveyed at time 2 comprised soldiers that had deployed with the regiment and soldiers that had transferred in following its return. Additionally, the deployment cycle that normally allows soldiers 12 months at home between deployments did not appear in effect as soldiers were not preparing for deployment when surveyed at 9 months postdeployment. Of those who agreed to participate, only those that had a combat deployment (n = 1,510 at Time 1; n = 783 at Time 2) and provided a matching code to link their survey responses (n = 388) were included in the matched group. Demographic characteristics of the matched group (n = 388), Time 1 (n = 1,510), and Time 2 populations (n = 783) are provided in Table 1.
Table 1.
Sample demographic variables with and without matched participants.
| Matched (n = 388) |
|||||
|---|---|---|---|---|---|
|
n (% of sample) |
|||||
| 4 Months (n = 1,510) n (% of sample) | 9 Months (n = 783) n (% of sample) | Time 1(4 months) | Time 2(9 months) | ||
| Age | 18–19 | 16 (1%) | 3 (<1%) | 9 (2%) | - |
| 20–24 | 599 (40%) | 307 (40%) | 172 (45%) | - | |
| 25–29 | 484 (32%) | 258 (33%) | 118 (31%) | - | |
| 30–39 | 336 (23%) | 173 (22%) | 76 (20%) | - | |
| 40-Older | 55 (4%) | 30 (4%) | 11 (3%) | - | |
| Gender | Female | 31 (2%) | 15 (2%) | 9 (2%) | - |
| Male | 1443 (98%) | 753 (98%) | 373 (98%) | - | |
| Education | Some high school | 17 (1%) | 9 (1%) | 5 (1%) | - |
| High school diploma | 743 (50%) | 395 (51%) | 203 (52%) | - | |
| Some college | 540 (36%) | 289 (37%) | 133 (34%) | - | |
| Bachelor’s degree | 174 (12%) | 76 (10%) | 45 (12%) | - | |
| Graduate degree | 25 (2%) | 4 (1%) | 2 (1%) | - | |
| Rank | Jr. enlisted (E1-E4) | 601 (41%) | 308 (41%) | 178 (47%) | - |
| NCOs (E5-E9) | 718 (49%) | 398 (53%) | 172 (45%) | - | |
| Warrant/officers (01–06) |
152 (10%) | 52 (7%) | 31 (8%) | - | |
| Multiple deployments | First | 846 (56%) | 468 (60%) | 252 (65%) | - |
| Two or more | 663 (44%) | 311 (40%) | 135 (35%) | - | |
| Unit type | Combat arms | 1354 (91%) | 704 (92%) | 354 (92%) | - |
| Combat service | 133 (9%) | 65 (8%) | 31 (8%) | - | |
| PTSD cutoff | 191 (13%) | 115 (15%) | 51 (13%) | 42 (11%) | |
Populations 4 and 9 months included matched participants.
Time 1 participants, who responded at time 1 and time 2, were compared to participants who responded at time 1 only on study variables and demographic characteristics. Nonparametric chi-square and t-tests (for BF, PTSD, and combat exposure) revealed no differences between the Time 1 population and matched group on the following variables: gender, education, unit-type, combat exposure, benefit finding, or PTSD symptoms. However, differences were found for age, χ2 (4, n = 1510) = 13.61, p < .01, rank χ2 (2, n = 1471) = 8.14, p < .05, and number of deployments χ2 (1, n =1509) = 16.83, p < .01, such that those who were older, higher rank, and had more deployments were more likely to not be available for participation at the second follow-up. These differences were expected as senior leaders are more likely to transfer to a new assignment following a deployment (and those who are more senior in rank are also older with more military experience). Rank and age were highly correlated (Spearman’s rho = .49), so rank was used as a proxy for age, and only rank and multiple deployments were used as demographic controls in subsequent analyses. The covariates used at Time 1 were also used in Wood et al. (2012b). However, that paper did not examine the buffering effects of benefit finding on separate PTSD subscales.
Measures
Benefit finding
The 5-item benefit finding measure used in the present study was based on the Britt et al. (2001) measure for peacekeeping operations with new items added to address benefits in a combat environment (Adler et al., 2011). This measure included items assessing perceived changes in appreciation (“I appreciate the little things in life more,”), meaning (“I am able to find meaning in what happened during my deployment”), having gained a sense of accomplishment (“What I did during the deployment helped me improve life for Iraqis/Afghans,” “I feel pride in my accomplishments during my most recent deployment”), and viewing past experiences as helpful (“The recent deployment has had a positive effect on my life”). Exploratory factor analysis of the scale at time 1 supported a 1-dimensional factor structure accounting for 51% of the variance with all items loading on the single factor (range .48 to .74). Results were similar for time 2 (1 factor accounted for 54% of the variance, factor loadings ranged from .48 to .81). Participants were asked to indicate how much they agreed or disagreed with the statements and responded on a 5-point Likert scale: 1 = strongly disagree to 5 = strongly agree. Cronbach’s α for the Time 1 scale was .81 and .82 for the Time 2.
Combat exposure
Soldier combat exposure was assessed using 34 items scale that has been used in previous studies evaluating the effects of combat (Thomas et al., 2010). Soldiers were asked to answer “did you experience any of the following during this deployment:” with example items including “being attacked or ambushed,” “engaging in hand-to-hand combat,” and “handling or uncovering human remains.” The level of exposure was assessed on a 5-point equal distribution scale of 1 (never) to 5 (ten or more times). Because weighted values of combat exposure items may not be equal (i.e., 5 rocket exposure may not equate to the stress level of 1 hand to hand combat incident) a more conservative estimate of combat stress was used. Items were dichotomized into no/yes exposure groups of 1 (no) and 2–5 (yes) and summed into the combat experience scale for analytical purposes (Thomas et al., 2010). The internal consistency of this dichotomous measure was high at Time 1 and Time 2 (ͺ92-93; Kuder-Richardson 20; Raju, 1982).
PTSD symptoms
PTSD symptoms were assessed using the 17-item, DSM-IV version of the Post-Traumatic Stress Disorder Checklist (PCL; Weathers et al., 1993). Participants rated symptoms in the last month using a five-point Likert scale: 1 (not at all) to 5 (extremely) and were averaged into an overall scale of PTSD symptoms, as well as subscalses for reexperiencing, avoidance, and arousal. Cronbach’s alpha for PTSD was .94 at Time 1 and .95 at Time 2, for reexperiencing at Time 1 the alpha was .91 and .91 at Time 2, for avoidance the Time 1 alpha was .89 and .90 at Time 2, and for arousal the Time 1 alpha was .88 and .89 at Time 2.
Data analysis
A series of multiple regression analyses were conducted to test the hypothesized interaction effects. Prior to the multiple regression analyses, all continuous variables were mean centered, as outlined by Cohen et al. (2003), and demographic variables were dummy coded. The demographic covariates (rank and multiple deployments) and the outcome variables (Time 1 and 2 PTSD symptoms) were excluded from the mean centering procedure. Hierarchical regression models were conducted according to the guidelines of Baron and Kenny (1986); R squares (R2) and delta R squares (ΔR2) were used to assess effects sizes. Three separate analyses were conducted, two cross-sectional analyses, Time 1 and Time 2, and one across the two time points, using participants who responded at both time points (matched participants), to identify moderating effects of benefit finding on the combat PTSD symptoms link. Each model included demographic covariates (rank and multiple deployments) in Step 1, the stressor (combat exposure) in Step 2, the moderator (benefit finding) in Step 3, and the combat exposure X benefit finding interaction in Step 4. The longitudinal model of PTSD symptoms at 4 and 9 months also included Time 1 PTSD symptoms in Step 1 predicting PTSD symptoms at Time 2. F tests were used to determine significant change in steps. Simple slope tests were used to determine if the gradient of the combat exposure-PTSD symptoms slope was significantly different from zero for significant interactions.
Results
Bivariate associations among the measured variables1
Table 2 provides the correlations between the measured variables for the cross-sectional (4-month, 9-month) and matched groups. Combat experiences were positively correlated with benefit finding at Time 1 (4 months), but not at Time 2 (9 months) or in the matched group. Replicating past research, combat exposure was positively associated with PTSD symptoms at both time periods, and benefit finding was associated with fewer PTSD symptoms at both time periods. Furthermore, benefit finding at Time 1 was associated with fewer symptoms of PTSD at Time 2.
Table 2.
Time 1, time 2, and matched sample means, standard deviations, and Pearson correlation coefficients.
| M | (SD) | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Combat exposure time 1 | 14.00 | 7.65 | - | ||||||||||
| 2 | Benefit finding time 1 | 3.36 | 0.75 | 0.07** | - | |||||||||
| 3 | PTSD symptoms time 1 | 1.85 | 0.84 | 0.38*** | −0.24*** | - | ||||||||
| 4 | Reexperiencing time 1 | 1.69 | 0.87 | 0.39*** | −0.15*** | 0.88*** | - | |||||||
| 5 | Avoidance time 1 | 1.72 | 0.86 | 0.30*** | −0.27*** | 0.93*** | 0.73*** | - | ||||||
| 6 | Arousal time 1 | 2.19 | 1.09 | 0.35*** | −0.22*** | 0.90*** | 0.69*** | 0.74*** | - | |||||
| 7 | Combat exposure time 2 | 14.75 | 7.72 | 0.90*** | 0.09 | 0.33*** | 0.37*** | 0.26*** | 0.27*** | - | ||||
| 8 | Benefit finding time 2 | 3.61 | 0.97 | 0.06* | 0.61*** | −0.10*** | −0.03 | −0.13*** | −0.09*** | 0.04 | - | |||
| 9 | PTSD symptoms time 2 | 1.86 | 0.87 | 0.30*** | −0.16** | 0.74*** | 0.65*** | 0.69*** | 0.66*** | 0.34*** | −0.21*** | - | ||
| 10 | Reexperiencing time 2 | 1.70 | 0.88 | 0.34*** | −0.05 | 0.65*** | 0.70*** | 0.57*** | 0.53*** | 0.36*** | −0.10** | 0.88*** | - | |
| 11 | Avoidance time 2 | 1.76 | 0.90 | 0.25*** | −0.20*** | 0.70*** | 0.58*** | 0.71*** | 0.59*** | 0.30*** | −0.25*** | 0.94*** | 0.74*** | - |
| 12 |
Arousal time 2 |
2.16 |
1.11 |
0.24*** |
−0.17*** |
0.66*** |
0.52*** |
0.57*** |
0.66*** |
0.27*** |
−0.21*** |
0.91*** |
0.70*** |
0.77*** |
| |
|
M |
(SD) |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
20 |
21 |
22 |
23 |
| 13 | Matched combat exposure time 1 | 13.74 | 7.65 | - | ||||||||||
| 14 | Matched benefit finding time 1 | 3.36 | 0.74 | 0.09 | - | |||||||||
| 15 | Matched PTSD symptoms time 1 | 1.88 | 0.84 | 0.36*** | −0.29*** | - | ||||||||
| 16 | Matched reexperiencing time 1 | 1.71 | 0.86 | 0.39*** | −0.15** | 0.85*** | - | |||||||
| 17 | Matched avoidance time 1 | 1.76 | 0.86 | 0.30*** | −0.32*** | 0.93*** | 0.70*** | - | ||||||
| 18 | Matched arousal time 1 | 2.23 | 1.12 | 0.30*** | −0.27*** | 0.90*** | 0.65*** | 0.75*** | - | |||||
| 19 | Matched combat exposure time 2 | 14.63 | 7.76 | 0.90*** | 0.09 | 0.33*** | 0.37*** | 0.26*** | 0.27*** | - | ||||
| 20 | Matched benefit finding time 2 | 3.34 | 0.73 | 0.08 | 0.70*** | −0.24*** | −0.11* | −0.26*** | −0.26*** | 0.07 | - | |||
| 21 | Matched PTSD symptoms time 2 | 1.65 | 0.81 | 0.30*** | −0.16** | 0.74*** | 0.65*** | 0.69*** | 0.66*** | 0.31*** | −0.21*** | - | ||
| 22 | Matched reexperiencing time 2 | 1.62 | 0.83 | 0.34*** | −0.05 | 0.65*** | 0.70*** | 0.57*** | 0.53*** | 0.35*** | −0.08 | 0.86*** | - | |
| 23 | Matched avoidance time 2 | 1.71 | 0.83 | 0.25*** | −0.20*** | 0.70*** | 0.58*** | 0.71*** | 0.59*** | 0.26*** | −0.25*** | 0.94*** | 0.73*** | - |
| 24 | Matched arousal time 2 | 2.08 | 1.07 | 0.24*** | −0.17*** | 0.66*** | 0.52*** | 0.57*** | 0.66*** | 0.25*** | −0.21*** | 0.91*** | 0.66*** | 0.78*** |
Multiple regressions examining combat exposure and benefit finding as predictors of PTSD symptoms at Time 1
Hierarchical regression models are provided in Tables 3–5. Table 3 includes Time 1 PTSD symptoms and subscales (reexperiencing, avoidance, and arousal) regressed on Time 1 combat exposure, benefit finding, and demographics covariates. In Step 4 a significant increase in model variance was accounted for in the benefit finding (.3%) by combat exposure interaction, β = −.05, t(1456) = −2.28, p < .05. Simple slopes revealed that benefit finding was negatively associated with PTSD symptoms for high combat exposure, β = −.31, t(1456) = −9.02, p < .01, and low combat exposure, β = −.20, t(1456) = −5.97, p < .01, indicating a steeper decline in PTSD symptoms under conditions of high combat and high benefit finding (Time 1).2
Table 3.
Hierarchical multiple regression predicting PTSD symptoms and PTSD symptom subscales (reexperiencing, avoidance, and arousal) among postdeployed soldiers (N = 1,510) at Time 1.
| PTSD Symptoms Time 1 | Reexperiencing Time 1 | Avoidance Time 1 | Arousal Time 1 | |
|---|---|---|---|---|
| Step 1. Demographics | ||||
| Rank NCO | −.19** | −.14* | −.19** | −.16** |
| Rank Warrant/Officer | −.53*** | −.36*** | −.39*** | −.69*** |
| Multiple Deployments | .16* | .09 | .15* | .17** |
| R2 | .02*** | .01** | .01*** | .01** |
| Step 2. Predictor | ||||
| Combat Exposure | .37*** | .38*** | .30*** | .33*** |
| R2 | .16*** | .16*** | .10*** | .10*** |
| ΔR2 | .14*** | .15*** | .09*** | .09*** |
| Step 3. Moderator | ||||
| Benefit Finding | −.25*** | −.17*** | −.28*** | −.21*** |
| R2 | .22*** | .18*** | .17*** | .18*** |
| ΔR2 | .06*** | .02*** | .07*** | .07*** |
| Step 4. Interaction | ||||
| Combat X Benefit Finding | −.05* | −.09*** | −.04 | −.02 |
| R2 | .22*** | .19*** | .18 | .18 |
| ΔR2 | .003* | .01*** | .002 | .002 |
Note: NCO = Noncommissioned Officer; Beta values are listed in each column.
***p < .001; **p < .01.
Table 4.
Hierarchical multiple regression predicting PTSD symptoms and PTSD symptom subscales (reexperiencing, avoidance, and arousal) among postdeployed soldiers (N = 783) at Time 2.
| PTSD Symptoms Time 2 | Reexperiencing Time 2 | Avoidance Time 2 | Arousal Time 2 | |
|---|---|---|---|---|
| Step 1. Demographics | ||||
| Rank NCO | −.15 | −.11 | −.18* | −.11 |
| Rank Warrant/Officer | −.60** | −.54*** | −.51*** | −.60*** |
| Multiple Deployments | .16 | .05 | .20* | .18* |
| R2 | .02*** | .02** | .02** | .02** |
| Step 2. Predictor | ||||
| Combat Exposure | .34*** | .36*** | .31*** | .27*** |
| R2 | .14*** | .14*** | .12*** | .09*** |
| ΔR2 | .11*** | .12*** | .10*** | .07*** |
| Step 3. Moderator | ||||
| Benefit Finding | −.23*** | −.11* | −.28*** | −.22*** |
| R2 | .17*** | .15*** | .16*** | .13*** |
| ΔR2 | .03*** | .01* | .05*** | .03*** |
| Step 4. Interaction | ||||
| Combat X Benefit Finding | .00 | .00 | −.02 | .03 |
| R2 | .17*** | .15*** | .16*** | .13*** |
| ΔR2 | .000 | .00 | .000 | .000 |
Note: NCO = Noncommissioned Officer; Beta values are listed in each column.
***p < .001; **p < .01.
Table 5.
Hierarchical multiple regression predicting PTSD symptom and PTSD symptom subscales (reexperiencing, avoidance, and arousal) at Time 2 after controlling for the respective Time 1 variables: Time 1 PTSD, Time 1 reexperiencing, Time 1 avoidance, Time 1 arousal among postdeployed soldiers (N = 388).
| PTSD Symptoms Time 2 | Reexperiencing Time 2 | Avoidance Time 2 | Arousal Time 2 | |
|---|---|---|---|---|
| Step 1. Demographics | ||||
| Time 1: PTSD | Re-exp | Avo | Aro | .74*** | .65*** | .65*** | .62*** |
| Rank NCO | .03 | .07 | −.00 | .01 |
| Rank Warrant/Officer | .01 | .08 | −.06 | .05 |
| Multiple Deployments | −.03 | −.11 | −.01 | .03 |
| R2 | .54*** | .48*** | .49*** | .43*** |
| Step 2. Predictor | ||||
| Combat Exposure | .03 | .06 | .04 | .05 |
| R2 | .54*** | .48*** | .49*** | .43*** |
| ΔR2 | .00 | .00 | .00 | .00 |
| Step 3. Moderator | ||||
| Benefit Finding | .05 | .06 | .02 | .00 |
| R2 | .54*** | .49*** | .49*** | .43*** |
| ΔR2 | .00 | .00 | .00 | .00 |
| Step 4. Interaction | ||||
| Combat X Benefit Finding | .05 | .03 | .02 | .07* |
| R2 | .54*** | .49*** | .49*** | .44*** |
| ΔR2 | .00 | .00 | .00 | .01* |
Note: NCO = Noncommissioned Officer; Beta values are listed in each column.
***p < .001; **p < .01.
For the outcome reexperiencing,in Step 4 a significant increase in model variance (.7%) was accounted for by the benefit finding by combat interaction β = −.09, t(1456) = −3.62, p < .01. Figure 1 simple slopes revealed that the level of benefit finding was negatively associated with reexperiencing for high combat exposure, β = −.25, t(1456) = −7.50, p < .01, and low combat exposure, β = −.08, t(1456) = −2.43, p < .05, and indicates lower reexperiencing under conditions of high combat and high benefit finding (Time 1). To identify the source of this interaction, we plotted high and low combat exposure values (± 1 SD) by PTSD symptoms on benefit finding (± 1 SD).
Figure 1.
Two-way interaction at Time 1 of benefit finding by combat level (± 1 SD) on reexperiencing (± 1 SD) with demographic covariates, combat exposure, and benefit finding.
Note: Reexperiencing was rescaled to illustrate actual symptoms reported as opposed to mean level of symptoms. 95% confidence intervals were used to calculate the error bars.
For the outcome avoidance, less benefit-finding and more combat exposure were related to more avoidance, but the interaction between benefit finding and combat exposure was not significant. The same pattern of results was found for the analysis (shown in Table 3) for arousal.
Multiple regressions examining combat exposure and benefit finding as predictors of PTSD symptoms at Time 2
Table 4 illustrates multiple regressions of Time 2 PTSD symptoms and subscales (reexperiencing, avoidance, and arousal) regressed on Time 2 demographic covariates, benefit finding, and combat exposure. The benefit finding by combat exposure interaction did not significantly predict PTSD symptoms and a similar pattern of results was found for the outcomes reexperiencing, avoidance, and arousal.
Multiple regressions examining combat exposure and benefit finding as predictors of PTSD symptoms at Time 2, controlling for Time 1 symptoms
Table 5 provides the results for the matched group. For the outcome of arousal, the Step 4 benefit finding by combat interaction predicted Time 2 arousal, β = .07, t(371) = 1.98, p < .05, and accounted for 1% of model variance after controlling for Time 1 arousal.
Figure 2 simple slopes revealed that the level of benefit finding was not associated with Time 2 arousal for high combat exposure, β = −.10, t(372) = −1.46, n.s., but was associated with low combat exposure, β = −.25, t(372) = −3.60, p < .01, indicating that arousal symptoms at Time 2 decrease under conditions of high benefit finding and low combat exposure, even after controlling for arousal symptoms at Time 1.
Figure 2.
Two-way interaction of benefit finding by combat level (± 1 SD) on arousal time 2 (± 1 SD) with Time 1 arousal and demographic covariates, combat exposure, and benefit finding.
Note: Arousal was rescaled to illustrate actual symptoms reported as opposed to mean level of symptoms. 95% confidence intervals were used to calculate the error bars.
Discussion
The present study is the first known to examine the buffering effects of benefit finding among military personnel at different points in time closely following a combat deployment. Results revealed that benefit finding was associated with lower PTSD symptoms at Time 1 and Time 2. However, cross-sectional interaction effects of benefit finding and combat exposure (as reported in Wood et al., 2012b) were limited to the early recovery phase at Time 1 (4 months post-deployment). No cross-sectional interaction was found at Time 2 (9 months post-deployment). Furthermore, the combat exposure and benefit finding interaction failed to account for variance in PTSD symptoms across the 4, 9-month recovery period.
Additional analysis of interactions between benefit finding and combat exposure when predicting PTSD symptom subscales clarifies some discrepancies found for the overall PTSD measure. The buffering effects of benefit finding were found only for the combat-reexperiencing link at Time 1. These results show that benefit finding may function as a limited cross-sectional buffer at early time points in the post-deployment adjustment period. These data appear consistent with Tedeschi, Calhoun, and Cann’s theoretical explanation regarding stressor magnitude that heightened levels of stress may drive meaning making in the form of perceived benefits and coping to reduce the stressor-strain relationship. The small effect size found in the interaction between benefit finding and combat exposure at Time 1 may have limited impact on recovery. According to Tedeschi, Calhoun, and Cann’s theory, only a few in our sample may have experienced stressors sufficient to shatter one’s assumptive world view to activate the resources (Gilbert et al. 2004) sufficient to drive growth from trauma. However, the simplicity of this theory does not account for the persistent level of stress found at time 2 which failed to interact with benefit finding in predicting PTSD symptoms. These data may indicate that most postcombat reflections may be lower intensity persistent stressors insufficient to shatter one’s assumptive world view. Further examination should address combat stressor type (i.e., fighting, threat, killing, atrocities, witnessing death) as a mechanism for driving change in assumptive world view and subsequent benefit finding related recovery (Shakespear-Finch & Lurie-Beck, 2014).
These results support Zoellner and Maercker’s theory. The palliative side of coping may enable buffering properties of benefit finding through positive illusions to stress. In support of this conclusion, Taylor et al. (1983) explained that positive self-serving biases, i.e., ”positive illusions,” may even facilitate buffering of threats and setbacks by restoring self-esteem, improved sense of mastery and control over the stressor event, and both physiological and perceived benefits that accompany optimism. However, the timing in which “illusions” may occur does not appear to coincide with collective stress experienced during the post-deployment recovery phase. These data may simply be a marker of early constructive processing to enable coping later on.
The Janus-faced model laudably challenges linear theoretical frameworks to demand more clarity regarding the mechanisms behind the function of finding benefits from stress. Positive illusions therefore, propose that individuals have the ability to assess coping resources (i.e., individual capability to manage stress). Our matched group analysis revealed that the interaction between combat exposure and benefit finding failed to account for changes in PTSD symptoms during the 4-to-9-month recovery period. However, the benefit finding by combat interaction at Time 1 did account for variance in arousal symptoms at Time 2, after controlling for arousal at Time 1. Additionally, higher benefit finding was related to lower arousal symptoms but only under conditions of low combat exposure. These findings are consistent with Liu et al. (2021) and Tomich and Helgeson (2006) who identified that persistent/recurrent stressors are related to lower perceptions of benefit. Higher perceptions of combat were no longer associated with the benefit finding-arousal relationship indicting that benefit finding appeared to function as an immediate adjustment mechanism designed to reduce stress to baseline rather than a mechanism to drive growth over time.
Although, interaction effect sizes were small, these data provide valuable information regarding practical functioning of benefit finding during a critical period allotted for soldier recovery. It is however, possible that benefit finding may rebound as a buffer of symptoms after longer recovery periods. For example, Helgeson et al. (2006) suggest that greater lengths of time (approximately 2 years) may be necessary for benefit finding to mature into psychological growth; thus, future studies should investigate longer follow-up periods after combat. Research should also investigate the causal relationship between benefit finding and PTSD symptom clusters to clarify their function as markers of coping stage of recovery from PTSD.
Despite these methodological limitations, these data provide guidance concerning the future examination of benefit finding in a postdeployment military recovery context and encourage the examination of longer recovery periods that include multiple time points. Future study should also examine benefit finding as an outcome of mental health as well as a predictor of recovery from stress as theory has difficulty describing why benefit finding occurs. Furthermore, longitudinal models should include pretrauma benefit finding as well as other coping resources and stressors to clarify the role of benefit finding as part of a greater coping process. Lastly, the Wood et al. (2012a) results suggest that military personnel inexperienced in how to channel coping skills into action (engaging other forms of coping resources: social support, exercise, participating in community events, etc.) may need additional training in using benefit finding approaches as coping strategies to buffer the combat-PTSD symptom link. Thus, future research should target soldiers educated with military resilience training that includes action-focused coping and elements of benefit finding to determine how benefit finding may alter behavioral health outcomes.
The limitations of this study included a smaller sample size for the matched group (N = 388) due to attrition. Despite this, the matched group did not significantly differ from the Time 1 population (N = 1,510) on key study variables and was considered a fair representation of the post-deployment combat population sampled. Transition of military personnel during the recovery period is typical and tends to be high for combat brigades deployed to the current Afghanistan and Iraqi conflicts. Nonetheless, efforts should be made to track individuals longitudinally. Second, these data did not account for pretrauma benefit finding or benefit finding at greater periods of time posttrauma; thus, benefit finding as a moderator of stressor−strain relationships is unclear regarding periods of longer recovery time. Third, all measures in the present study were self-report, thus the perception of benefits was assessed and not the actual benefits (Frazier et al., 2001) accrued by the individual. Fourth, the Time 2 population (Time 2, N = 783 versus Time 1, N = 1,510) included individuals who had combat deployment experience from other units prior to joining this unit which may have affected the length of recovery time. Fifth, the benefit finding scale used in the present study only included five items. Although these items showed high internal consistency and were face valid for our population, future research should replicate and extend these findings using a more established measure of benefit finding, such as the Posttraumatic Growth Inventory (Tedeschi & Calhoun, 1996). Additionally, future studies should examine postdeployment stresssors e.g., redeployment stress, in addition to combat stress, and examine the moderating effects of benefit finding on the postdeployment stressors and adjustment outcomes relationship. Lastly, interaction effect sizes were small (range r = −.09 to r = .07) suggesting that the impact of benefit finding on PTSD symptoms is small and that other variables account for the variance in the outcome.
In summary, the present study contributes to the field of research examining benefit finding as a buffer of the combat exposure-PTSD symptoms relationship by showing the presence of a buffering effect relatively early in the re-deployment process, but not at a later point in time. Future longitudinal research with multiple time points is needed to clarify the role that benefit finding plays in how military personnel adjust to the traumatic stressors they face on combat operations.
Acknowledgments
This paper would not be possible without the efforts, guidance, and inspiration from Kathleen P. Wright, PhD.
Funding Statement
The findings described in this article were collected under a Walter Reed Army Institute of Research Protocol. The views expressed in this article reflect those of the authors and do not necessarily represent the official policy or position of the U.S. Army Medical Command or the Department of Defense. Military Operational Medicine Research Program (MOMRP).
Notes
In addition to examining overall differences between time 1 participants and matched participants, we also examined whether rank and multiple deployments may relate to differences in study variables of interest, namely – benefit finding, PTSD symptoms and combat exposure. Bivariate associations revealed no significant relationship between rank, combat exposure, and time 2 PTSD symptoms. The increase in rank was associated with a an increase in benefit finding F(2, 378) = 9.52, p < .001. Officers / warrant officers reported higher benefit finding (M = 3.90, SD = 0.57), than junior enlisted soldiers (M = 3.29, SD = 0.80) and noncommissioned officers (M = 3.33, SD = 0.67). Furthermore, the increase in rank was also related to a decrease in time 1 PTSD symptoms F(2, 378) = 4.81, p < .01, such that, officers / warrant officers showed a significantly lower time 1 PTSD symptoms (M = 1.45, SD = 0.58) than junior enlisted soldiers (M = 1.95, SD = 0.80), or noncommissioned officers (M = 1.89, SD = 0.67). Multiple deployments showed no significant relationship with combat exposure, time 1 PTSD symptoms or time 2 PTSD symptoms. The increase in multiple deployments was associated with a decrease in benefit finding F(1, 385) = 4.25, p < .05. First time deployers reported higher benefit finding (M = 3.41, SD = 0.75), than multiple deployers (M = 3.25, SD = 0.71).
Additional hierarchical regression analyses were conducted using the cross-sectional group of matched participants at time 2. Demographics did not significantly predict PTSD symptoms F change (3, 368) = 2.38, p= .07; however, similar to previous models where combat exposure predicted more PTSD symptoms, ΔR² = .09, F change (1, 367) = 39.27, p < .01, benefit finding was associated with fewer PTSD symptoms ΔR² = .04, F change (1, 366) = 18.01, p < .01, and the interaction between combat exposure and benefit finding failed to predict PTSD symptoms ΔR² = .00, F change (1, 365) = .00, p = .95.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data supporting the findings in this study are not publicly available on request from the corresponding author, [MDW], because they are still under an active Walter Reed Army Institute of Research. Protocol.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data supporting the findings in this study are not publicly available on request from the corresponding author, [MDW], because they are still under an active Walter Reed Army Institute of Research. Protocol.