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Post-Traumatic Growth Among US Military Veterans Essay

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Research Aims

Being in a distressing situation may lead to subsequent emotional suffering or regrowth. Exposure to potentially traumatic experiences (PTEs) may lead to the development of various mental disorders, most notably post-traumatic stress disorder (PTSD) (Tsai et al., 2016). Of particular concern are military veterans, as they are more likely than their civilian counterparts to be exposed to violent events such as combat (Tsai et al., 2015). In addition to adverse outcomes, exposure to PTEs has also been linked to post-traumatic growth (PTG), which consists of positive psychological development in areas such as a greater sense of personal strength, social connectedness, and religious/spiritual changes (Tedeschi et al., 2018). It has also been noted that veterans are especially prone to PTG achievement (Na et al., 2021). However, it is still unclear whether PTSD plays a pivotal role in PTG.

Previous literature has extensively focused on the prevalence of PTG in the military population. Several studies reported an overall PTG prevalence among veterans of 50-52%, suggesting an elevated level of PTG occurrence in veterans (Palmer et al., 2017; Pietrzak et al., 2021; Wu et al., 2019). It also means that PTG is a frequent phenomenon for veterans. However, concerning the five domains of PTG, other prevalence rates have been established. The most prevalent domains are proposed to be the appreciation of life and personal strength, which are most frequently reported by veterans who experienced PTG after trauma (Hijazi et al., 2015; Tsai et al., 2015). Some studies have also noted relating to others as a potentially prevalent PTG domain; nevertheless, appreciation of life and personal strength are more commonly referred to (Na et al., 2021). Individual resilience seems to play a critical in PTG among veterans.

The relationship between PTSD symptoms and PTG has also been a topic of interest for numerous researchers. As such, the nature of this association still remains a pertinent question. Mark et al. (2016) state the results of recent studies are mixed, suggesting the existence of a third variable, such as resilience, which may impact the connection. Schubert et al. (2016) corroborate this idea, proposing that the relationship between PTSD symptoms and PTG might be non-linear; however, the authors also note that very few articles appropriately measure PTSD diagnosis and PTG occurrence. Another interesting finding demonstrates that the veterans’ functioning is better when both PTSD symptoms and PTG are present (Tsai et al., 2016). In contrast, the likelihood of experiencing PTG and overall functioning tends to decrease in veterans who were not diagnosed with PTSD but had PTG.

Other aspects of PTG refer to the sociodemographic, trauma, health, and psychosocial factors that might promote PTG experiences in veterans. It has been proposed that such sociodemographic variables as age and ethnicity could be connected to PTG, with older veterans and those from ethnic minorities becoming more likely to develop PTG (Mark et al., 2016). Trauma severity also influences PTG, as moderately severe trauma more often results in successful PTG than non-severe or extremely intense negative experiences (Greenberg et al., 2021). Physical and mental health has also been linked to PTG occurrence, with some studies reporting that veterans who were more worried about their health could improve PTG prevalence (Na et al., 2021). Finally, some psychosocial aspects of PTG are deliberate rumination, social support, and resilience, which have been proposed to promote PTG experiences among veterans (Schubert et al., 2016). The combination of factors seems to play an essential role in PTG.

The first goal of this research is to describe the Prevalence of PTG – overall and in the five domains. The second goal is to describe the nature of the association between PTG and PTSD symptoms in veterans, determining whether its linear or non-linear. The third target is to define which sociodemographic, trauma, health, and psychosocial factors are related to PTG. The fourth aim is to identify if PTSD+PTG is associated with better functioning than PTSD-PTG. One additional area of interest could include evaluating whether PTSD and PTG comorbidity is connected to better functioning in comparison with PTSD symptoms presence only.

Although previous studies proposed that veterans with PTSD are more likely to experience PTG achievement, these works utilized the questionnaires based on the fourth edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM-IV). Since slight differences in PTSD descriptions have been integrated, this project intends to refer to the most recent modification of the manual, DSM-V, released in 2013 (American Psychological Association [APA], 2013). It is possible that the novel 7-factor model could ideally account for the negative experiences connected to PTSD (Armour et al., 2015). Correlate analysis regressions, ROC curve analysis, and relative importance analysis will be the primary methods of analyzing the retrieved data. The study results are expected to be beneficial for promoting wellness and resilience among veterans, improving their capabilities for battling trauma, and maintaining a high quality of life.

Method

Participants

We analyzed data from the 2019-2020 National Health and Resilience in Veterans Study (NHRVS), which surveyed a nationally representative sample of 4,069 U.S. military veterans. In the current study, only those veterans who reported exposure to at least one potentially traumatic event on the Life Events Checklist for DSM-5 were included (n=3,764; 92.5% of the total sample). Veterans completed an anonymous, web-based survey. The NHRVS sample was drawn from KnowledgePanel®, a survey research panel of more than 50,000 households maintained by research firm Ipsos. KnowledgePanel® is a probability-based survey panel of a representative sample of U.S. adults that covers approximately 98% of U.S. households. Panel members are recruited through national random samples, originally by telephone and now almost entirely by postal mail. To permit generalizability of results to the entire U.S. veteran population, Ipsos computed post-stratification weights using the following benchmark distributions of U.S. veterans from the most recent (August 2019) Current Veteran Population Supplemental Survey of the Census Bureau’s American Community Survey: age, gender, race/ethnicity, metropolitan status, education, household income, a branch of service, and years in service. An iterative proportional fitting (raking) procedure was used to produce the final post-stratification weights. All study participants provided informed consent, and the research was approved by the Human Subjects Subcommittee of the V.A. Connecticut Healthcare System.

Measures

Table 1 describes variables that were examined as potential correlates of post-traumatic growth.

Post-traumatic Growth. Post-traumatic growth was assessed using the Posttraumatic Growth Inventory-Short Form (PTGI-SF; Cann et al., 2010; α=0.92). Total scores range from 0 to 50, and five subscales, including personal strength, relating to others, new possibilities, spiritual change, and appreciation of life, were assessed (sample item: “Please indicate the degree to which you experienced these changes in your life as a result of [WORST EVENT assessed on the LEC-5]: I know better that I can handle difficulties.”) Endorsement of “moderate,” “great,” or “very great” growth on any of the PTGI-SF items was indicative of PTG. Given that the distribution of PTGI-SF scores was zero-inflated, non-normal, and positively skewed (Kolmogorov-Smirnov test statistic=0.13, p<0.001), we dichotomized responses based on the moderate or greater endorsement of any item; this approach to operationalizing endorsement of PTG has been used in a meta-analysis on the prevalence of PTG (Wu et al., 2019), as well as a recent study on the prevalence of COVID-19 pandemic-related PTG (Pietrzak et al., 2021).

Mental Health Functioning. The Mental Health Component Summary score from the Medical Outcomes Study Short Form 8 Health Survey score (Ware et al., 2001) was administered to assess mental functioning. This score is comprised of items assessing role limitations caused by emotional problems, vitality, social functioning, and mental health. Higher scores better functioning.

Brief Inventory of Psychosocial Functioning (B-IPF). The Brief IPF is a 7-item self-report measure that assesses functional impairment over the past 30 days in romantic relationships, parenting, family relationships, friendship and socializing, work, education, and self-care. Twenty-three responses are on a 7-point Likert scale (0 = “Never”; 1-5 = “Sometimes”; 6 = “Always”; or “Not Applicable”). Scores on applicable items are summed, divided by the total possible score, and multiplied by 100 to yield a 0-100% range. Past research has shown strong psychometric properties; internal consistency in the current sample was α=0.85. Higher scores indicate greater psychosocial difficulties.

Data Analysis

Data analyses proceeded in four steps. First, we computed descriptive statistics to summarize study variables and compute the prevalence of PTG in each of the five domains assessed by the PTGI. Second, we fitted linear and quadratic functions between the severity of PTSD symptoms and PTGI-SF scores. An analysis of variance was implemented to determine which part provided the best fit to these data and explained the most variance in predicting PTGI-SF scores. Third, we conducted a multivariable logistic regression analysis to identify significant correlates of PTG; interactions between PTSD symptoms and protective variables such as personality and defensive psychosocial characteristics that were significantly associated with PTG were incorporated into this analysis to test for possible interactions among these variables. When multidimensional variables (e.g., PTSD symptoms, protective psychosocial characteristics) emerged as significant correlates of PTG, we conducted secondary analyses to evaluate which component aspects of these variables were independently associated with this outcome. Fourth, we conducted a multivariable analysis of variance (MANOVA) among veterans who screened positive for PTSD to examine whether endorsement of PTG in each of the five domains assessed by the PTGI-SF was associated with scores on measures of mental functioning and psychosocial difficulties.

Results

Prevalence of PTG

Figure 1 shows the prevalence of PTG in the entire sample and among veterans who screened positive for PTSD. In the whole sample, 63.2% endorsed PTG in one or more domains, with the most prevalent domains being personal strength (44.5%), appreciation of life (42.5%), and new possibilities (32.2%). Among veterans with a positive screen for PTSD, 84.2% endorsed PTG in one or more domains, with the most prevalent being appreciation of life (68.9%), personal strength (53.7%), and spiritual change (51.4%). Relative to veterans without a positive screen for PTSD, the prevalence of PTG was significantly higher among veterans with a positive screen for PTSD for endorsement of any PTG (84.1% vs. 61.6%; χ2(1)=52.31, p<0.001) and all PTG domains except relating to others (all χ2(1)>9.49, all p’s<0.003).

Association between PTSD symptoms and PTG

Results of a curve estimation analysis of the relationship between severity of PTSD symptoms and PTGI-SF scores revealed that a quadratic, inverted-U shaped function explained 60% more variance in these scores than a linear function (βquadratic= -0.43 vs. βlinear=0.22; t=11.00, p<0.001; R2quadratic=0.08 vs. R2linear=0.05). Figure 2 shows a scatterplot of the association between PCL-5 and PTGI-SF scores.

Sample Characteristics and Correlates of PTG

Table 2 shows descriptive statistics of the full sample and results of multivariable analysis of correlates of PTG. Significant correlations of PTG endorsement included non-White race/ethnicity, married/partnered status, lower household income, a greater number of adverse childhood experiences, direct and indirect traumas, the severity of PTSD symptoms, and higher scores on measures of agreeableness and conscientiousness, and protective psychosocial characteristics. When interaction terms were incorporated into this model, a significant interaction was observed between PTSD symptom severity and purpose in life (p=0.001; see Figure 3) and dispositional gratitude (p=0.007). Interactions between PTSD symptom severity and agreeableness and conscientiousness were insignificant (both p’s>0.05).

Secondary analyses revealed that, of the PTSD symptom clusters, greater severity of intrusive symptoms (OR=1.14, 95%CI=1.08-1.19; unwanted upsetting memories: OR=1.32, 95%CI=1.12-1.56; trauma-related emotional reactivity: OR=1.32, 95%CI=1.12-1.55), dysphoric arousal (OR=1.15, 95%CI=1.07-1.24; sleep difficulties: OR=1.22, 95%CI=1.11-1.34), and anxious arousal (OR=1.11, 95%CI=1.03-1.19; hypervigilance: OR=1.35, 95%CI=1.20-1.52) were independently associated with PTG. Further, of the protective psychosocial characteristics, higher scores on measures of dispositional gratitude (OR=1.08, 95%CI=1.01-1.15) and purpose in life (OR=1.04, 95%CI=1.02-1.06) were independently associated with this outcome.

Association between PTG and Functioning in Veterans with PTSD

Results of a MANOVA in veterans who screened positive for PTSD revealed that endorsement of improved social relationships (40.1±1.3 vs. 34.9±0.8; F=10.04, p=0.002; d=0.45, 95%CI=0.18-0.73) and personal strength (39.6±1.0 vs. 35.4±1.2; F=7.14, p=0.008; d=0.29, 95%CI=0.04-0.55) was associated with higher mental functioning scores, while endorsement of personal strength (34.4±2.1 vs. 43.8±2.6; F=7.37, p=0.007; d=0.39, 95%CI=0.14-0.65) and new possibilities (35.0±2.3 vs. 43.3±2.2; F=6.84, p=0.010; d=0.36, 95%CI=0.11-0.61) was associated with fewer psychosocial difficulties. None of the other associations were significant (all F’s<2.75, all p’s>0.09).

References

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Chen, I. H., Lin, C. Y., Zheng, X., & Griffiths, M. D. (2020). Assessing mental health for China’s police: psychometric features of the self-rating depression scale and symptom checklist 90-revised. International Journal of Environmental Research and Public Health, 17(8), 1-17.

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Greenberg, J., Tsai, J., Southwick, S. M., & Pietrzak, R. H. (2021). Can military trauma promote psychological growth in combat veterans? Results from the national health and resilience in veterans study. Journal of Affective Disorders, 282, 732–739.

Hijazi, A. M., Keith, J. A., & O’Brien, C. (2015). Predictors of post-traumatic growth in a multi-war sample of U.S. combat veterans. Peace and Conflict: Journal of Peace Psychology, 21(3), 395–408.

Mark, K. M., Stevelink, S. A. M., Choi, J., & Fear, N. T. (2018). Post-traumatic growth in the military: A systematic review. Occupational and Environmental Medicine, 75(12), 904–915.

Na, P. J., Tsai, J., Southwick, S. M., & Pietrzak, R. H. (2021). Factors associated with post-traumatic growth in response to the COVID-19 pandemic: Results from a national sample of U.S. military veterans. Social Science & Medicine (1982), 289, 114409.

Palmer, E., Murphy, D., & Spencer-Harper, L. (2017). Experience of post-traumatic growth in U.K. veterans with PTSD: A qualitative study. Journal of the Royal Army Medical Corps, 163(3), 171–176.

Pietrzak, R. H., Tsai, J., & Southwick, S. M. (2021). Association of symptoms of post-traumatic stress disorder with post-traumatic psychological growth among U.S. veterans during the COVID-19 pandemic. JAMA Network Open, 4(4).

Tedeschi, R. G., Shakespeare-Finch, J., Taku, K., & Calhoun, L. G. (2018). Post-traumatic growth: Theory, research, and applications. Routledge.

Tsai, J., El-Gabalawy, R., Sledge, W. H., Southwick, S. M., & Pietrzak, R. H. (2015). Post-traumatic growth among veterans in the USA: Results from the national health and resilience in veterans study. Psychological Medicine, 45(1), 165–179.

Tsai, J., Sippel, L. M., Mota, N., Southwick, S. M., & Pietrzak, R. H. (2016). Longitudinal course of post-traumatic growth among U.S. military veterans: Results from the national health and resilience in veterans study. Depression and Anxiety, 33(1), 9–18.

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Table 1. Variables examined as potential correlates of post-traumatic growth in U.S. military veterans

Sociodemographic characteristicsAge, gender, race (white vs. non-white), education (college graduate or higher vs. up to high school diploma), marital status (married/living with a partner vs. unmarried/unpartnered), annual household income ($60,000 or more vs. less than $60,000), employment (working vs. retired), and combat status (no combat exposure vs. combat exposed)
Background characteristics
Adverse childhood experiencesScore on Adverse Childhood Experiences Questionnaire (Felitti et al., 1998).
Direct potentially traumatic eventsThe Life Events Checklist for DSM-5 (LEC-5) was used to assess exposure to 17 potentially traumatic events (PTEs) that “happened to me” (i.e., direct PTEs), such as natural disasters, motor vehicle accidents, and assaultive violence.
Indirect potentially traumatic eventsThe Life Events Checklist for DSM-5 (LEC-5) was used to assess exposure to 17 potentially traumatic events (PTEs) that were “witnessed” or “learned about” (i.e., indirect PTEs), such as natural disasters motor vehicle accidents, and assaultive violence.
PTSD symptomsThe PTSD Checklist for DSM-5 (PCL-5) was used to assess the past-month severity of PTSD symptoms related to the “worst event” endorsed on the LEC-5. The PCL-5 is a 20-item self-report measure of DSM-5 PTSD symptoms. Each sign is rated on a 5-point Likert scale from 0 (not at all) to 4 (extremely) in relation to an individual’s “worst” PTE indicated on the LEC-5. A positive screen for PTSD was operationalized as a score of 33 or higher (Bovin et al., 2016). The PCL-5 has been shown to have high psychometric validity in past research and had excellent internal consistency in this study (In the current sample, Cronbach’s α = 0.96).
Personality traitsAssessed using the Ten-Item Personality Inventory (TIPI; Gosling, Rentfrow, & Swann, 2003), a 10-item self-report brief measure of the “Big Five” personality traits of emotional stability (anxious vs. confident and calm), extraversion (outgoing vs. reserved), openness to experience (imaginative and inventive vs. cautious and routine-like), agreeableness (friendly and cooperative vs. detached), and conscientiousness (efficient and organized vs. careless).
Physical health difficultiesComposite factor score of (1) sum of several medical conditions endorsed in response to the question: “Has a doctor or healthcare professional ever told you that you have any of the following medical conditions?” (e.g., arthritis, cancer, diabetes, heart disease, asthma, kidney disease). Range: 0-24 conditions; endorsement of ADL and/or IADL disability (e.g., At the present time, do you need assistance from another person to do the following (e.g., bathe [ADL]; pay bills [IADL] (Edemekong et al., 2021); and (3) Score on somatization subscale of the Symptom Checklist 90-Revised (Chen et al., 2020).
Protective psychosocial characteristics composite score
ResilienceConnor-Davidson Resilience Scale-10 (CDRISC-10); 10 items (e.g., “I am able to adapt when changes occur”) on a 5-point Likert scale (1=not at all true to 5=true nearly all the time; Campbell-Sills and Stein, 2007); In the current sample, Cronbach’s α = 0.90.
Purpose in lifeScore on Purpose in Life Test-Short Form (Schulenberg et al., 2010); In the current sample, Cronbach’s α = 0.89.
Dispositional optimismScore on a single-item measure of optimism from the Life Orientation Test-Revised (Scheier et al., 1994); “In uncertain times, I usually expect the best”; (rating 1=strongly disagree to 7=strongly agree).
Dispositional gratitudeScore on a single-item measure of gratitude from the Gratitude Questionnaire (McCullough et al., 2002); “I have so many things in life to be grateful for”; (rating 1=strongly disagree to 7=strongly agree).
Curiosity/explorationScore on a single-item measure of curiosity/exploration from Curiosity and Exploration Inventory-II (Kashdan et al., 2009); “I frequently find myself looking for new opportunities to grow as a person (e.g., information, people, resources”); (rating 1=strongly disagree to 7=strongly agree).
GritScore on the Short Grit Scale, which assesses the extent to which statements such as “I am a hard worker” apply to an individual. In the current sample, Cronbach’s α = 0.79.
Social connectedness composite score
Structural social supportA number of close friends and family members: “About how many close friends and relatives do you have (individuals you feel at ease with and can discuss what is on your mind)?”
Secure attachmentEndorsement of option to the following question: “Please select ONE of the following statements that best describes your feelings and attitudes in relationships:” a) I am somewhat uncomfortable being close to others; b) I find it relatively easy to get close to others (secure); c) I find that other people are reluctant to be as close as I would want (Hazan and Shaver, 1990)
Perceived social supportMedical Outcomes Study Social Support Scale-5; 5 items assessing how often each type of support is available when needed (e.g., “Someone to confide in or talk to about your problems”) on a 5-point Likert scale: 1=none of the time to 5=all of the time. Higher scores reflect greater perceived social support (Sherbourne and Stewart, 1991); In the current sample, Cronbach’s α = 0.89.
Engagement in mental health treatmentPositive endorsement of lifetime mental health treatment: “Have you ever received mental health treatment (e.g., prescription medication or psychotherapy) for a psychiatric or emotional problem?”

Table 2. Sample characteristics and results of multivariable regression models examining correlates of post-traumatic growth and functional difficulties in U.S. military veterans

Sample
Characteristics
Multivariable Regression Model
Predicting PTG
Weighted Mean (S.D.) or
N (weighted %)
Odds ratio (95%CI)
Age61.8 (15.5)1.00 (0.99-1.00)
Male sex3,283 (89.9%)1.15 (0.88-1.51)
White, non-Hispanic race/ethnicity3,070 (78.4%)0.78 (0.64-0.95)*
College graduate or higher education1,723 (33.8%)1.27 (1.08-1.49)**
Married/partnered2,667 (71.8%)1.45 (1.21-1.73)***
Retired2,035 (43.8%)1.06 (0.87-1.29)
Annual household income ≥$60K2,214 (60.0%)0.80 (0.68-0.94)**
Combat veteran1,289 (36.0%)0.89 (0.75-1.04)
Adverse childhood experiences1.6 (2.0)1.06 (1.01-1.11)*
Direct potentially traumatic events3.4 (2.5)1.16 (1.12-1.21)***
Indirect potentially traumatic events6.2 (7.3)1.03 (1.01-1.04)***
Severity of PTSD symptoms8.5 (13.3)1.05 (1.04-1.06)***
Extraversion3.8 (1.5)1.05 (1.00-1.11)
Agreeableness5.0 (1.2)1.19 (1.11-1.28)***
Conscientiousness5.8 (1.2)1.09 (1.01-1.18)*
Emotional stability5.2 (1.4)0.98 (0.91-1.06)
Openness to experiences4.8 (1.2)0.97 (0.90-1.04)
Physical health difficulties0 (1.0)1.03 (0.93-1.13)
Protective psychosocial characteristics0 (1.0)1.16 (1.04-1.30)**
Social connectedness0 (1.0)0.95 (0.86-1.05)
History of mental health treatment878 (23.3%)1.17 (0.95-1.44)

Note. 95%CI=95% confidence interval; PTG=posttraumatic growth; PTSD=posttraumatic stress disorder.

Statistically significant association: *p<0.05; **p<0.01; ***p<0.001.

 Prevalence of post-traumatic growth in trauma-exposed U.S. veterans in the full sample and among those who screened positive for PTSD
Figure 1. Prevalence of post-traumatic growth in trauma-exposed U.S. veterans in the full sample and among those who screened positive for PTSD

A positive screen for PTSD was operationalized as a PTSD Checklist for a DSM-5 score of 33 or higher.

Scatterplot of association between PTSD symptoms and post-traumatic growth
Figure 2. Scatterplot of association between PTSD symptoms and post-traumatic growth
Probability of endorsing post-traumatic growth as a function of screening positive for PTSD and level of purpose in life
Figure 3. Probability of endorsing post-traumatic growth as a function of screening positive for PTSD and level of purpose in life

Error bars represent 95% confidence intervals.

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