Operation Enduring Freedom and Operation Iraqi Freedom Veterans with amputation: An exploration of resilience, employment and individual characteristics

by Amy J. Armstrong, Carolyn E. Hawley, Benjamin Darter, Adam P. Sima, Jason DiNardo, and Katherine J. Inge

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Armstrong, A., Hawley, C., Darter, B., Sima, A., DiNardo, J. & Inge, K. (2018). Operation Enduring Freedom and Operation Iraqi Freedom Veterans with amputation: An exploration of resilience, employment and individual characteristics. Journal of Vocational Rehabilitation, 48(2), 167-175.



Since 2002 approximately 1,700 US military service members have experienced trauma related amputations from injuries incurred in Afhanistan and Iraq (Fisher, 2015).


This study explores the variables of resilience, individual characteristics, and employment status of a sample of these Veterans who served in Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF) and sustained an amputation.


Veterans identified through the VA Corporate Data Warehouse (n=165) completed a survey on their experiences following amputation.


Results indicate that several variables were significantly related to resilience, to include employment status, pain status, and prosthetic use.


Recommendations for future research and practice are provided.


The U.S. has deployed more than 2.7 million Americans to Iraq and Afghanistan since 2001, and over half of these have been deployed more than once (Hautzinger et al., 2015). Due to medical advancements, as well as the improvement of protective gear, over 90% of injured OEF/OIF military personnel have survived injuries that in prior conflicts would have been fatal (Lew et al., 2007; Hoge et al., 2006; IOM, 2013). Approximately 1,700 military service members have experienced trauma related amputation since 2002 due to combat exposure in Afghanistan and Iraq (Fischer, 2015). The majority of these involve lower extremity but may also include upper extremity and/or multiple limb amputations at rates higher than the civilian population (Krueger, Wenke, & Ficke, 2012).

OEF/OIF Veterans are also experiencing high rates of post-traumatic stress disorder (PTSD), depression, and substance abuse (Seal, 2007Dursa, Reinhard, Barth, & Schneiderman, 2014). Additionally, a military culture to “man up” during difficulty contributes to the psychological functioning of service members, with residual effects experienced by Veterans. Furthermore, Veterans are committing suicide at higher rates than any other previous conflict (Tarabay, 2010). The complex interplay of these injuries and mental health conditions will likely have a prolonged impact upon the psychosocial, medical, and vocational experiences of OEF/OIF veterans, their families, and the communities in which they will live (Frain, Bishop, & Bethel, 2010).

A report from the Office of Internal Medicine (2013) cites the alleviation of health, economic, and social issues among Veterans as a significant and urgent need. Resilience and overall well-being have been identified by the U.S. Department of Defense (DoD) as a skill development need for military personnel and Veterans. Well-being Theory is framed within positive psychology and focuses upon the science of flourishing to include positive emotions, engagement, relationships, meaning and achievement (Seligman & Csikszentmihalyi, 2000). One aspect of flourishing is an individual’s resilience capacity (Huppert & So, 2013). Resilience is commonly described as the ability of an individual to “steer through and bounce back” from challenging life events, including trauma. Resilience is comprised of several abilities: emotion regulation, impulse control, empathy, optimism, causal analysis, self-efficacy, and social support seeking (Reivich & Shatte, 2002). Research demonstrates that resilience can be learned (Reivich & Shatte, 2002Luthans et al., 2006).

Two convergent lines in the extant literature suggest that resilience is key to successful repatriation of our combat soldiers. First, the essence of the concept of resilience is overcoming challenges – both the kind of acute trauma that occurs in battle situations as well as the chronic challenges experienced by returning combat Veterans. Second, there is evidence that resilient individuals are less likely to incur PTSD and similar mental health conditions (Wisco et al., 2014Tsai, Harpaz-Rotem, Pietrzak, & Southwick, 2012; Bonanno, 2004; Feder et al., 2009). The findings of a study of OEF/OIF Veterans suggests that interventions designed to bolster resilience and post-deployment support may help protect against traumatic stress and depressive symptoms, and improve psychosocial functioning in Veterans (Pietrzak et al., 2010). In particular, Veterans who experience disability may benefit from the development of resilience skills to promote adaptive responses to the challenges presented (Hawley et al., 2016). However, the exploration of resilience among Veterans who experience amputation is limited to date.

Another aspect relevant to flourishing is employment. Individuals who have career wellbeing are more than twice as likely to be doing well in their lives overall (Gallup, 2010). Employment also facilitates social and community connections. Clark, Deiner, Gergellis & Lucas (2008) found that the long term impact of sustained unemployment (more than 1 year) may be the only major life event from which people do not fully recover within five years, this holds particularly true for men. Employment is a primary feature of our self-identity and self-efficacy. Employment in which individuals are actively engaged has been found to improve not only mental, but physical health as well as performance outcomes (Agrawal & Harter, 2009Harter, Canedy, & Stone, 2008Luthans, Norman, Avolio, & Avey, 2008Luthans, Youssef-Morgan, 2017). Thus, psychological capital, including resilience, is a key feature of individual health as well as positive organizational behavior.

The purpose of this study is to explore the resilience of OEF/OIF Veterans with amputation, particularly as it relates to individual characteristics and employment. The following research questions are addressed in this study:

  • 1) What is the resilience of OEF/OIF Veterans with amputation?

  • 2) What is the relationship between employment and resilience?

  • 3) What factors and individual characteristics predict resilience?



The researchers completed both VCU and Veterans Administration IRB approval processes. Upon approval from both institutions, the researchers implemented data collection procedures, as follows.


The VA Corporate Data Warehouse was used to generate a list of Veterans to contact to complete the questionnaire. Names were identified in the search using ICD-9 diagnostic codes for major amputation levels (partial foot or partial hand amputation(s) were excluded), OEF/OIF service, and our defined age (18–55 years). The Veterans could have one or more major amputations of the upper or lower limbs. The search yielded 870 mailing addresses, of which 154 letters were returned as undeliverable (i.e., the Veteran was no longer at the address and no valid forwarding address was listed). After reviewing the inclusion criteria and confirming contact information, approximately 716 veterans received the survey.

2.2Survey instrument

To measure resilience the 10-item CD-RISC was used. This abbreviated version is based upon the 25-item CD-RISC developed by Connor and Davidson. The 10-item CD-RISC was developed by Campbell-Sills & Stein and consists of questions 1, 4, 6, 7, 8, 11, 14, 16, 17, and 19 from the original 25-item scale, with a mean range of 0–40. The 10-item CD-RISC retains good reliability with a Cronbach Alpha of.85 (Campbell-Sills & Stein, 2007). Initial results indicated a mean score of 31.8 for a General Population (SD 5.4) (Campbell-Sills, Forde, & Stein, 2009). Subsequent studies with a General Adult Population sample indicate a 10-item CD-RISC mean score range of 29 to 33.5 (Connor-Davidson, 2017). Additional studies with trauma and disability populations reflect mean score ranges of 20.5–31.3 (Connor-Davidson, 2017). For this current study, individuals who completed 7 or more items of the 10-item score had any missing items imputed using the mean score of the items completed.

Participant demographics, and individual characteristics including: type of amputation, items related to pain, prosthetic use, impact of amputation on quality of life including transportation, community activities and ability to work, were also collected.

Two rounds of data collection occurred to increase participant response rate. The initial data collection was web-based, while the second used both web–based recruitment as well as the mailing of survey hardcopies as recommended by Dillman (2009). The population was provided a hard copy of the survey via U.S. postal service including a postage paid return envelope. This mailing also included a letter directing individuals to a password protected website should he or she prefer to complete the survey online. This was followed by two rounds of follow-up reminder postcards, sent approximately 2 weeks apart. Web based surveys are notorious for low response rates, typically 11% less than mail and phone surveys, with one study reporting a 2% response rate (Archer, 2008; Petchenik & Wiseman, 2011).


In this survey, 165 Veterans completed the Employment and Life Experience of Veterans with Amputation survey. Demographic variables included age (18–30, 31–35, 36–45, 46+ years), race (White/Caucasian, Non-White), level of education (college, high school/technical training), marital status (married/partnered, widowed/divorced/separated, single), children (Yes, No), and employment (employed, unemployed, retired). Participants indicating self-employment were coded as employed and those identifying as seeking employment were considered unemployed. Participants that did not specify whether they were employed or unemployed were treated as missing.

Amputation related quality of life measures included an indication of pain other than in the affected limb (back, shoulder, other leg), difficulty participating in social and community activities, overall situation as an amputee, and per day spent wearing a prosthesis. These items were categorized into 3 levels: No/slight trouble, Moderate trouble, or Considerable/great deal of trouble.

Questions 2 and 7 included overall, ability to work, and quality of life. Overall and ability to work was converted to a 3-level ordinal variable (great/considerable, moderate, slight/no trouble) from its original (great, considerable, moderate, slight, no trouble). Quality of life was converted to a 3-level ordinal variable (great/considerable, moderate, slight/no reduction) from its original (great, considerable, moderate, slight, no reduction). Question 10 was converted to a 3-level ordinal variable (extremely good/good, moderate, poor/extremely poor) from its original (extremely good, good, moderate, poor, extremely poor). Question 12 was converted to a 2-level binary variable (greater or equal to 7 hours, less than 7 hours) from its original (0, 1–3, 4–6, 7–9, 10–12, 13–15, more than 15 hours).

Amputation characteristics considered were the time from injury (in years), amputation group (bilateral, above knee, below knee amputation, other injuries), first altered amputation group (lower extremity, other), second altered amputation group (bilateral, above/below knee amputation, other). Substance use was collected via self-report (Yes, No).

For the amputation group, participants who obtained an above knee aka transfemoral or a hip disarticulation were above knee amputees, below knee aka transtibial were below knee amputees, and partial foot excluding toe(s) only, hand excluding partial finger(s) only, below elbow aka transradial, above elbow aka transhumeral, and shoulder disarticulation were other injuries. Participants who obtained either an above or below knee amputation on both left and right sides were bilateral amputees. The first altered amputation group consists of two levels, lower extremity (bilateral, above knee, below knee), and other injuries. The second altered amputation group consists of three levels, bilateral, above/below knee amputation, and other.

2.4Statistical methods

Means and standard deviations (SD) for CD-RISC scores were reported for each of the 10 CD-RISC items as well as the total score. Additionally, means and standard deviations for total CD-RISC scores were reported separately for each of the demographic, amputation related quality of life, and employment items. Unadjusted and adjusted models were used to predict total CD-RISC scores using a linear regression model. All demographic, amputation related quality of life indicators, and employment survey questions available were used in the model. Backward elimination in stepwise regression was used for the adjusted model. Differences and standard errors were reported for both unadjusted and adjusted models. All tests were performed at the 0.05 level with the backward elimination threshold set at P=0.15.


A total of 165 Veterans responded for a response rate of 23%. Of these, 73.7% (n=121) were completed and returned via U.S. Postal Service and 26.7% (n=44) were completed via the online format. Although this is less than the desired 30% for standard survey research, it is actually more reflective of a typical online survey response (Dillman, et al., 2013). Coupled with the probability that some Veterans may also be experiencing research fatigue, these aspects may account for the lower response rate. Of these respondents, 91.5% reported that their amputation was service connected. The majority experienced Lower Extremity amputation with 45.3% below the knee and 37.6% above the knee (n=97). Interestingly 48 individuals did not respond to this item, therefore 117 participants were used for this analysis. Many Veterans who experience amputation also experience secondary or co-occurring conditions as a result of their injury. Table 1 reports co-occurring conditions.

Table 1

Co-occurring conditions

Disability/Condition Frequency*
Traumatic Brain Injury 60.2%
Post Traumatic Stress Disorder 57.1%
Musculoskeletal injury (other than amputation) 36.6%
Hearing 51.6%
Vision 24.8%
Spinal Cord Injury 9.9%
Depression 34.2%
Anxiety 44.7%
Substance Use 6.2%
Burn 14.3%
None 7.5%

*Respondents checked all that applied. Amount will exceed 100%.

In terms of employment status, 151 (92.1%) did not return to active duty with 118 (79.2%) stating that they could not do so due to their disability. When responding to a binary item (employed/unemployed), 61 (39.3%) reported being employed, with 51 indicating full time employment. The largest employment sector of this sample were individuals (N=20) working in the Government. Ninety-eight (60.1%) indicated that they were unemployed. Parsing this further, of the unemployed category, 35% identified as being unemployed, with approximately 26% identifying as being retired.

The 10-item CD-RISC mean score for this sample of Veterans who experience amputation was 28.2, within mean score ranges identified in earlier research of traumatized populations (20 to 31). See Table 2.

Table 2

Average and total resilience for CD-RISC items

CD-RISC Item Content Mean±SD
Able to adapt when changes occur1 2.9±0.9
Can deal with whatever comes in the way2 2.9±0.9
Trying to see the humorous side of things when I am faced with problems1 2.9±1.0
Having to cope with stress can make me stronger1 2.6±1.1
Tend to bounce back after illness, injury, or other hardships1 2.9±1.0
Believing in achieving goals, even if there are obstacles1 2.9±0.9
Stay focused and think clearly under pressure3 2.7±1.0
Not easily encouraged by failure4 2.6±1.0
Thinking of oneself as a strong person when dealing with life’s challenges and difficulties1 3.1±0.9
Able to handle unpleasant or painful feelings like sadness, fear, and anger2 2.7±1.1
Total score 28.2±7.8

1N=161, 2N=162, 3N=160, 4N=159.

Age, race, amputation group (above or below knee, bilateral etc.), and education were not found to be related to resilience at the 0.05 level. Variables with significance include employment (P=0.008); pain (Great vs Moderate P=<0.001) (Great vs Slight P=0.002); Difficulties participating in social/community activities (Great vs Moderate & Great vs Slight P=<0.001); perception of overall situation as an amputee (Average vs Good P=<0.001) (Average vs Poor P=<0.001); (Good vs Poor P=<0.001), and duration of prosthetic use (equal to or less than 7 hours vs greater than 7 hours P=0.007).

Interestingly, and counter to prior resilience research on Veterans (Pietrzak & Southwick, 2011), Veterans who are Single (29.5) reported a slightly higher level of resilience than those who are Married/Partnered (28.4). However, this difference did not meet statistical significance. With a much higher mean than those who are Widowed, Divorced or Separated who reported the lowest level (25.8). See Table 3 for a summary of demographics, characteristics and additional survey questions.

Table 3

Summary of CD-RISC scores by various demographics, individual characteristics, and perceived function

Characteristic Levels N (%) CD-RISC
Age 18–30 years 38 (24%) 28.4 (6.9)
  31–35 years 56 (35%) 28.9 (7.5)
  36–45 years 48 (30%) 28.9 (8.1)
  46+ years 19 (11%) 23.9 (8.8)
Employment Employed 62 (39%) 30.3 (7.0)
  Unemployed 56 (35%) 26.8 (8.4)
  Retired 42 (26%) 27.1 (7.6)
Race White 128 (82%) 28.7 (7.2)
  Non-White 29 (18%) 27.2 (9.7)
Amputation Group Bilateral 51 (31%) 29.5 (6.7)
  Above Knee 30 (19%) 27.3 (9.2)
  Below Knee 54 (33%) 26.8 (8.0)
  Other 27 (17%) 29.6 (7.5)
Amputation Group (Altered 1) Bilateral 51 (31%) 29.5 (6.7)
  Above/Below Knee 84 (52%) 27.0 (8.4)
  Other 27 (17%) 29.6 (7.5)
Amputation Group (Altered 2) Lower Extremity 135 (83%) 27.9 (7.8)
  Other 27 (17%) 29.6 (7.5)
Substance use Yes 10 (6%) 25.6 (7.4)
  No 154 (94%) 28.4 (7.8)
Education College degree 77 (48%) 28.5 (8.2)
  High school/Technical training 84 (52%) 28.0 (7.5)
Marital Status Married/Partnered 108 (67%) 28.4 (8.0)
  Single 28 (17%) 29.7 (5.8)
  Widowed/Divorced/Separated 25 (16%) 25.8 (8.6)
Time from injury 2–5 years 38 (23%) 28.6 (7.1)
  6–10 years 75 (46%) 27.7 (8.2)
  >10 years 49 (30%) 28.7 (7.7)
Experienced other pain (back, shoulder, other leg)? Slight trouble 31 (19%) 30.4 (5.9)
  Moderate Trouble 59 (37%) 30.4 (7.2)
  Great trouble 71 (44%) 25.4 (8.2)
Other pain affected ability to work? Slight trouble 61 (38%) 31.8 (6.0)
  Moderate Trouble 38 (24%) 28.9 (7.4)
  Great trouble 62 (38%) 24.0 (7.7)
Other pain affected quality of life? Slight reduction 65 (40%) 31.9 (6.1)
  Moderate reduction 40 (25%) 28.6 (6.7)
  Great reduction 57 (35%) 23.7 (8.0)
Difficulty participating in social and community activities?