Postdeployment Driving Stress and Related Occupational Limitations Among Veterans of Operation Iraqi Freedom and Operation Enduring Freedom

Abstract

Difficulty in driving after deployment has emerged as an impediment for servicemembers returning from Operation Iraqi Freedom and Operation Enduring Freedom (OIF–OEF). This study explored postdeployment driving stress and related occupational limitations using two self-report instruments: the Driver’s Stress Profile and the Driving and Occupational Limitations questionnaire. Data gathered from 103 OIF–OEF returnees confirmed that driving and related occupational issues occur postdeployment. Significant low to moderate correlations were found between postdeployment driving stress and limitations in community mobility, leisure, and social participation. The returnees who drove off base more frequently during deployment showed significantly higher levels of postdeployment driving stress than the returnees who drove off base less frequently. Moreover, the returnees who demonstrated higher levels of driving stress and occupational limitations required more time to resume normal driving postdeployment. Findings raise awareness about the need to design effective driver rehabilitation and community reintegration programs for this population.

Keywords

Afghan campaign 2001–automobile driving human activities Iraq War,2003–2011 stress,psychological veterans health

More than 1.5 million returnees have served in Operation Iraqi Freedom and Operation Enduring Freedom (OIF–OEF) since the start of the war in 2001 (Meagher, 2009). Many of these servicemembers experience problems postdeployment that affect their reintegration into their former civilian roles. One of the occupational challenges combat veterans face is driving. According to the U.S. Department of Veterans Affairs (2009), the leading cause of death of veterans in the first years after returning home from combat is motor vehicle crashes (MVCs). Moreover, veterans of OIF–OEF have a higher chance (>75%) of dying in an MVC than the general population (National Highway Traffic Safety Administration, 2010). The reasons for this increased risk are not completely understood, but some believe it is because of a higher risk-taking tendency and unsafe behavior in veterans (Killgore et al., 2008). Four explanations for unsafe driving behaviors in veterans of OIF–OEF have been put forth: (1) driving stress, (2) substance and alcohol abuse, (3) posttraumatic stress disorder (PTSD), and (4) traumatic brain injury (TBI; Burke, Olney, & Degeneffe, 2009; Lew, Amick, Kraft, Stein, & Cifu, 2010; Sayer et al., 2010; Stern, Prudencio, & Sadler, 2011).

We conducted a previous qualitative inquiry into the experiences of uninjured and undiagnosed OEF–OIF veterans in an attempt to understand the occupational challenges they encountered on reentering civilian society (Kim, Nakama, Noble, & Peyton, 2011). One salient thematic finding was that combat veterans experienced high levels of anxiety and stress when driving in the United States after return from combat. Participants stated that their stress and anxiety were related to combat driving restrictions such as strict convoy rules and constant threat of roadside violence. They also mentioned having trouble driving in close proximity to other vehicles (e.g., in traffic) because of the lingering driving stress from war. These results suggest that driving during deployment can translate into high levels of driving stress postcombat even for veterans who do not have a diagnosis such as substance abuse, PTSD, or TBI.

Other authors have attributed postdeployment driving stress to the evasive or battlefield driving tactics taught to military personnel before deployment, including speeding, driving down the center of or off the road, swerving around objects in the road, ignoring traffic signals and signs (to avoid attack), and not wearing a seatbelt (to enable a quick escape; Lew et al., 2010; Stern et al., 2011). These driving behaviors, taught as life-saving techniques, are strongly reinforced during deployment to such a degree that they may become automatic driving habits (Stern et al., 2011). When used in postdeployment driving, however, these behaviors not only increase risk of injury to the driver, passenger, and other people but also raise levels of driving stress.

Although studies have explored unsafe driving behaviors among combat veterans, what has not been fully revealed is how postdeployment driving complications affect participation in daily occupations. Driving is an important instrumental activity of daily living that leads to functional independence in other areas of occupation such as work, education, leisure, and social participation (American Occupational Therapy Association, 2010). For example, according to data from the U.S. Census Bureau, 76.1% of American workers drive to work alone (McKenzie & Rapino, 2011). It is important that occupational therapy practitioners working with combat veterans be aware of potential driving issues and limitations in occupations caused by or related to those issues.

Purposes of the Study

First, this study aimed to determine levels of postdeployment driving stress among OIF–OEF veterans using an existing instrument, the Driver’s Stress Profile (DSP; Larson, 1996). Second, through a tailor-made questionnaire, Driving and Occupational Limitations (DOL), we explored veterans’ perceived levels of limitations in occupations (including work, education, community mobility, leisure, social participation) related to driving difficulties. Last, we examined the correlations between driving stress and participation limitations in occupations among the veterans.

Method

Design

We used survey instruments in this cross-sectional descriptive study to collect data on postdeployment issues pertaining to driving and occupational participation among combat veterans. The study received institutional review board approval from California State University, Dominguez Hills, before beginning participant recruitment. Participants gave their informed consent before taking part in the study.

Participants

The inclusion criteria for this study were that the combat veteran had to have served in either the OIF or the OEF theater of operations and to have driving experience off base as a driver or passenger (or as both) during the deployment. No specific gender, age, ethnicity, military branch, socioeconomic status, or diagnosis was sought. Convenient and snowball sampling methods were used to recruit participants through the authors’ social networks and the assistance of key informants from four branches of service (U.S. Air Force, U.S. Army, U.S. Navy, and U.S. Marine Corps) in the Los Angeles area.

Instruments

The instruments used in the study were the DSP (Larson, 1996) and the DOL (the latter developed for this study). Both instruments, along with a front section asking for participant characteristics (e.g., age, gender, current employment status, driving frequency during deployment, deployment driving role), were included as one survey packet and distributed in hard copy or electronically. Respondents were instructed to answer both questionnaires in relation to the first 4 mo of postdeployment experience because earlier research revealed that driving difficulties occur mostly within the first 3–5 mo of returning home (Kim et al., 2011; Stern et al., 2011).

The DSP was used to identify the level of stress participants experienced while driving after returning home from combat. The instrument focuses on emotional responses to driving by assessing the frequency of different behaviors. It contains 40 items in four subscales: Anger, Impatience, Competing, and Punishing. Participants rate how often they display these driving behaviors on a scale ranging from 0 (never) to 3 (always; Larson, 1996). Therefore, total scores range from 0 to 120, with higher scores indicating higher levels of driving stress. Test–retest reliability for the overall DSP is .93, with a range of .84 to .96 for the four subscales (Blanchard, Barton, & Malta, 2000). The internal consistency coefficient for the full scale is .93, with a range of .78 to .89 for the subscales (Blanchard et al., 2000). Construct validity of the DSP was supported through its correlations with other instruments measuring patterns of aggressive or unsafe driving behaviors and with traffic citations, MVCs within the past 3 yr, and near accidents within the past 12 mo (Houston, Johnson, Skinner, & Clayton, 2006).

The DOL was tailor-made to meet the purposes of this study. The 20-item DOL consists of four categories of occupation—Work/Education, Community Mobility, Leisure, and Social Participation—with five items in each category. Participants rated on a scale of 0 (never) to 3 (always) how often they perceived limitations in those occupations related to postdeployment driving difficulties or reduced driving frequency. The total score on the DOL ranges from 0 to 60 and subtotal scores range from 0 to 15. Higher DOL scores suggest higher degrees of perceived limitations in driving and occupations. An additional question with a yes–no response placed before the Work/Education subscale asked participants whether they chose to work or take classes from home instead of commuting to work or school because they did not want to drive. If participants answered yes, they were instructed to ignore all items in the Work/Education subscale. Moreover, a question at the end of the DOL asked participants how long it took for their postdeployment driving to return to normal.

To ensure content validity of the DOL, we did two forms of survey piloting; three occupational therapists experienced in this practice–research area conducted an expert review, and three OIF–OEF veterans participated in debriefing interviews. We incorporated their comments and suggestions for strengthening the clarity and relevance of the questionnaire during the revision phase. Although some DOL items (e.g., “I carpooled to work or school,” “I took public transportation,” “I shopped at stores close by”) can be conceptualized as occupational adaptations rather than occupational limitations, the questionnaire instructions emphasized the causality or link between occupational limitations and postdeployment driving issues; that is, participants were directed to respond to items reflecting their concerns about driving.

Procedures

We used key informants from all four branches of service in the Los Angeles area and acquaintances from our social networks who knew veterans of OIF–OEF to assist in recruiting participants. An email containing information about the research and inclusion criteria was sent to all potential participants. Attached to this email was the informed consent form and instructions on how to contact us to receive the link to the online survey or a hard copy of the survey packet. Completed survey instruments were returned anonymously.

Data Analysis

Descriptive statistics and frequency analysis were used to summarize the demographic information and survey responses. To measure potential differences between categories of participant characteristics, a one-way analysis of variance (ANOVA) with post hoc analysis using Fisher’s least significant difference was performed. Pearson product–moment correlation coefficient (Pearson’s r) was used to measure the correlations between driving stress (DSP) and limitations in driving and occupations (DOL). The following cutoffs were used to interpret the strength of the correlations: 0–.20 = negligible, .20–.40 = low, .40–.60 = moderate, .60–.80 = high, and .80–1.00 = a very high correlation (Tomita, 2006). The significance level was set at .05. All statistical analyses were performed with IBM SPSS Version 20 (IBM Corporation, Armonk, NY).

Results

Participant Characteristics

A total of 122 OIF–OEF veterans consented to participate in the study and completed the survey instruments either in person or online. Five of these participants did not meet the inclusion criteria, and 14 did not complete the questionnaires. Therefore, 103 completed surveys were used in the analysis.

Table 1 summarizes participant characteristics. The majority of participants were male (89.3%) and between ages 21 and 30 (54.4%) during their deployment. Nearly equal numbers of participants were single or married during the first 4 mo postdeployment. Slightly more than half of participants (53.4%) reported their length of deployment as being 7–12 mo. Almost half (47.6%) served in the U.S. Army; 38.8% served in the U.S. Marine Corps. Most participants drove on a weekly or daily basis during deployment.

Table 1.

Participant Characteristics (N = 103)

Characteristic	n	%
Gender
Male	92	89.3
Female	11	10.7
Age at deployment, yr
18–20	15	14.6
21–30	56	54.4
31–40	24	23.3
41–50	6	5.8
No answer	2	1.9
Marital status during first 4 mo postdeployment
Single	44	42.7
Married	45	43.7
Divorced	10	9.7
Separated	4	3.9
Branch of service
U.S. Air Force	5	4.9
U.S. Army	49	47.6
U.S. Navy	9	8.7
U.S. Marine Corps	40	38.8
Location of deployment
Iraq	75	72.8
Afghanistan	16	15.5
Both countries	12	11.7
Length of deployment, mo
0–6	13	12.6
7–12	55	53.4
13–24	26	25.2
24+	9	8.7
Frequency of driving during deployment
Few times during deployment	17	16.5
A few times each month	15	14.6
Every week	31	30.1
Every day	40	38.8
Driving role during deployment
Driver	9	8.7
Passenger	34	33.0
Both	60	58.3
Residential area during first 4 mo postdeployment
Urban	31	30.1
Suburban	31	30.1
Rural	9	8.7
Base (postdeployment)	32	31.1
Employment status during first 4 mo postdeployment a
Civilian, employed	12	11.7
Civilian, unemployed	6	5.8
Student	10	9.7
Military, active duty	77	74.8
Military, guard or reserve	5	4.9
Military, terminal leave–separated	7	6.8

Note. Percentages may not add to 100 due to rounding.

Participants checked all that applied.

Driver’s Stress Profile

Table 2 summarizes participants’ responses to all 40 DSP items. The mean rating for each item is also provided to indicate levels of endorsement across the items. More than 70% of participants endorsed 24 of the items as always, often, or sometimes. Table 2 also provides the mean (M) and standard deviation (SD) of scores for each DSP subscale. Of the four subscales, Anger and Impatience were generally more endorsed (i.e., had higher means) than Competing and Punishing. The DSP full scale had a mean of 43.7 and a standard deviation of 24.9. The relatively high standard deviations seen across the individual item ratings and subscale mean ratings indicate that participants’ responses varied widely; therefore, we further identified the percentage of participants who scored significantly higher than previously reported DSP population norms. In a study of the general population, Blanchard et al. (2000) identified mean DSP scores of 38.8 (SD = 16.8) for men and 30.8 (SD = 30.8) for women. Using 1 SD above the mean as the cutoff, we determined that 28 (30.4%) male participants and 4 (36.4%) female participants in our study scored meaningfully higher than the established norms on the DSP.

Table 2.

Responses on the Driver’s Stress Profile (N = 103)

	%
Subscale (Score Range) and Items	3 (Always)	2 (Often)	1 (Sometimes)	0 (Never)	M (SD)
Anger (1–30)					15.61(6.59)
1. Get angry at drivers	18.4	34.0	45.6	1.9	1.69(0.79)
2. Get angry at fast drivers	7.8	15.5	62.1	14.6	1.17(0.77)
3. Get angry at slow drivers	27.2	34.0	34.0	4.9	1.83(0.89)
4. Get angry when cut off	44.7	23.3	28.2	3.9	2.09(0.94)
5. Get angry at malfunctioning stoplights	17.5	16.5	33.0	33.0	1.18(1.08)
6. Get angry at traffic jams	23.3	26.2	43.7	6.8	1.66(0.91)
7. Spouse or friends tell you to calm down	42.7	30.1	24.3	2.9	2.13(0.88)
8. Get angry at tailgaters	11.7	22.3	36.9	29.1	1.17(0.98)
9. Get angry at your passengers	39.8	29.1	26.2	4.9	2.04(0.93)
10. Get angry when highway narrows	1.9	6.8	46.6	44.7	0.66(0.69)
Impatience (1–30)					11.89(7.83)
11. Impatient waiting for passengers to get in	7.8	14.6	33.0	44.7	0.85(0.94)
12. So impatient won’t let car engine warm up	12.6	18.4	35.9	33.0	1.11(1.01)
13. Impatient at stoplights	14.6	10.7	20.4	54.4	0.85(1.11)
14. Impatient waiting in lines (car wash, bank)	12.6	13.6	46.6	27.2	1.12(0.95)
15. Impatient waiting for parking space	13.6	25.2	35.9	25.2	1.27(0.99)
16. As passenger, impatient with driver	13.6	19.4	35.0	32.0	1.15(1.02)
17. Impatient when car ahead slows down	10.7	17.5	43.7	28.2	1.11(0.94)
18. Impatient if behind schedule on a trip	13.6	28.2	40.8	17.5	1.38(0.93)
19. Impatient driving in far right, slow lane	29.1	30.1	31.1	9.7	1.79(0.98)
20. Impatient with pedestrians crossing street	22.3	12.6	35.0	30.1	1.27(1.12)
Competing (1–30)					7.06(6.37)
21. Compete on the road	8.7	10.7	46.6	34.0	0.94(0.90)
22. Compete with yourself	7.8	18.4	34.0	39.8	0.94(0.95)
23. Compete with other drivers	15.5	21.4	33.0	30.1	1.22(1.05)
24. Challenge other drivers	6.8	17.5	34.0	41.7	0.89(0.93)
25. Race other drivers	2.9	9.7	24.3	63.1	0.52(0.79)
26. Compete with cars in tollbooth lines	1.0	4.9	31.1	63.1	0.44(0.64)
27. Compete with other cars in traffic jams	1.0	6.8	14.6	77.7	0.31(0.64)
28. Compete with drivers who challenge you	10.7	10.7	29.1	49.5	0.83(1.01)
29. Compete to amuse self when bored	4.9	6.8	29.1	59.2	0.57(0.82)
30. Drag race adjacent car at stoplights	1.9	5.8	21.4	70.9	0.39(0.69)
Punishing (1–30)					9.17(7.10)
31. “Punish” bad drivers	9.7	12.6	37.9	39.8	0.92(0.96)
32. Complain to passengers about other drivers	17.5	33.0	42.7	6.8	1.61(0.85)
33. Curse at other drivers	15.5	24.3	37.9	22.3	1.33(0.99)
34. Make obscene gestures	5.8	10.7	37.9	45.6	0.77(0.87)
35. Block cars trying to pass	9.7	13.6	35.9	40.8	0.92(0.97)
36. Block cars trying to change lanes	8.7	10.7	35.0	45.6	0.83(0.94)
37. Ride another car’s tail	3.9	14.6	34.0	47.6	0.75(0.85)
38. Brake suddenly to punish tailgater	9.7	14.6	34.0	41.7	0.92(0.98)
39. Use high beams to punish bad driver	7.8	11.7	25.2	55.3	0.72(0.95)
40. Seek personal encounter with bad driver	3.9	4.9	18.4	72.8	0.40(0.76)
Total (0–120)					43.73 (24.95)

A one-way ANOVA did not show significant differences in DSP total score among participants by age, marital status, length of deployment, or residential area postdeployment. However, we found significant differences in DPS total score between subcategories of frequency of driving off base during deployment, F (3, 99) = 4.08, p = .009: (1) Participants who drove only a few times during the entire deployment scored significantly lower on the DSP than those who drove every day (p = .011), (2) those who drove a few times each month during deployment had a lower DSP score compared with those who drove every day (p = .007), and (3) those who drove on a weekly basis during deployment demonstrated a lower DSP score than those who drove every day (p = .020). Moreover, comparison between the subcategories of deployment driving role also yielded a significant difference, F (2, 100) = 3.72, p = .027: Those who were only passengers during deployment scored significantly lower than those who had both driver and passenger roles (p = .009).

Driving and Occupational Limitations

Table 3 displays the results for the DOL individual items and subscales. Seven participants (6.8%) responded that they chose to work or take classes from home instead of commuting to work or school to avoid driving. The top five most-reported aspects of driving and occupational limitations were “I chose my place of residence to be close to work or school” (Work/Education), “I avoided driving to places that were unfamiliar” (Community Mobility), “I shopped at stores close by” (Community Mobility), “I spent my free time at home” (Leisure), and “I did leisure activities that did not require driving” (Leisure). In contrast, two aspects of driving and occupational limitations that showed noticeably low frequency were “I took public transportation” (Community Mobility) and “I would rather have waited for someone else to drive” (Community Mobility). Overall, the means and standard deviations across the four DOL subscales appeared to be similar (see Table 3). A one-way ANOVA did not show any significant differences in DOL total scores among participants by age, marital status, length of deployment, frequency of deployment driving, deployment driving role, and residential area postdeployment.

Table 3.

Responses on the Driving and Occupational Limitations Questionnaire (N = 103)

	%
Subscale (Score Range) and Items	3 (Always)	2 (Often)	1 (Sometimes)	0 (Never)	M (SD)
Work/Education (0–15; N = 96)					5.19(4.85)
1. I chose my place of residence to be close to work or school.	20.8	33.3	25.0	20.8	1.73(1.21)
2. I was late to work (or school) or left early from work (or school).	3.1	6.2	43.8	46.9	0.90(1.15)
3. I skipped work (or school).	4.2	3.1	22.9	69.8	0.70(1.25)
4. I took a longer route to school (or work) to avoid traffic (or fewer bridges).	8.3	18.7	36.5	36.5	1.20(1.21)
5. I carpooled to work or school.	2.1	7.3	19.8	70.8	0.66(1.17)
Community Mobility (0–15)					4.73(2.69)
6. I took public transportation.	4.9	6.8	20.4	67.9	0.34(0.60)
7. I would rather have waited for someone else to drive.	2.9	4.9	16.5	75.7	0.35(0.71)
8. I shopped at stores close by.	15.5	36.9	40.8	6.8	1.61(0.83)
9. I avoided driving to places that were unfamiliar.	15.5	45.6	34.0	4.9	1.72(0.79)
10. After deployment I drove less.	7.8	11.7	24.3	56.3	0.71(0.96)
Leisure (0–15)					5.09(3.63)
11. I spent my free time at home (e.g., Netflix vs. movie theater).	13.6	40.8	35.0	10.7	1.57(0.86)
12. I did leisure activities that did not require driving (e.g., exercise at home vs. local gym).	6.8	29.1	42.7	21.4	1.21(0.86)
13. I quit previously participated-in leisure activities.	2.9	13.6	24.3	59.2	0.60(0.83)
14. I failed to explore new leisure activities.	5.8	18.4	25.2	50.5	0.80(0.94)
15. I participated in fewer leisure activities.	7.8	19.4	28.2	44.7	0.90(0.98)
Social Participation (0–15)					4.85(3.41)
16. I stayed home instead of going out with friends (e.g., clubs, restaurants).	8.7	25.2	37.9	28.2	1.15(0.93)
17. I refused social invitations (e.g., parties, dinner invites).	6.8	26.2	33.0	34.0	1.06(0.94)
18. I chose to socialize with my friends and family via phone or online social network sites.	8.7	20.4	37.9	33.0	1.05(0.94)
19. I carpooled to social events.	4.9	7.8	33.0	54.4	0.63(0.83)
20. My circle of friends changed.	8.7	17.5	35.9	37.9	0.97(0.95)
Total (0–60)					19.86 (11.43)

Note. Rating means range from 0 to 3, with higher means indicating higher levels of driving and occupational limitations. Seven participants responded that they chose to work or take classes from home instead of commuting to work or school and therefore skipped the Work/Education scale.

Correlations Between the Instruments

Moderate correlations were found between the DSP total scores and scores on the Leisure (.53) and Social Participation (.59) subscales, and a low correlation was found between the DSP total scores and scores on the Community Mobility (.28) subscale (p < .01). No significant correlation was yielded between the DSP total scores and scores on the Work/Education (.09) subscale.

Length of Time for Postdeployment Driving to Return to Normal

Table 4 presents the results of the last survey question in which participants were asked how long it took for their postdeployment driving to return to normal. Fifty-five (54.5%) participants reported returning to normal driving within 6 mo postdeployment, 17 (16.8%) required 6 mo or more to resume normal driving, and 29 (28.7%) reported still being unable to return to normal driving.

Table 4.

Length of Time for Driving to Return to Normal (N = 101)

Time	n	%
1 wk or less	23	22.8
2–4 wk	12	11.9
1–6 mo	20	19.8
7–12 mo	11	10.9
>1 yr	6	5.9
Still not normal	29	28.7

A one-way ANOVA revealed significant differences in DPS total scores by length of time needed to resume normal driving postdeployment, F (5, 95) = 8.56, p < .0001. Participants who were still unable to return to normal driving scored significantly higher on the DSP than those who needed <1 wk (p < .0001), 2–4 wk (p < .0001), 1–6 mo (p < .0001), or 6–12 mo to resume normal driving (p = .012). In addition, those who required >1 yr to return to normal driving had significantly higher DSP total scores compared with those who needed 1 wk (p = .037) and those who needed 2–4 wk to resume normal driving.

Likewise, a one-way ANOVA showed significant differences in DOL total scores by length of time needed to resume normal driving postdeployment, F (5, 95) = 8.13, p < .0001. Participants who were still unable to return to normal driving scored significantly higher on the DOL than all other subgroups (ps ranged from .032 to <.0001), and those who required >1 yr to return to normal driving had significantly higher DOL total scores than the four other subgroups (1 wk, 2–4 wk, 1–6 mo, 7–12 mo; ps < .0001).

Discussion

The unique nature of combat-related injuries in veterans of OIF–OEF has contributed to the emergence of a “new disability” for rehabilitation professionals, including occupational therapists, to address (Burke et al., 2009, p. 5). Although TBI and PTSD are two commonly reported injuries and have attracted tremendous attention from the American public, postdeployment driving issues merit further research as an obstacle to veterans’ transition and reintegration into civilian society. After the thematic finding of our previous qualitative inquiry into postdeployment driving stress (Kim et al., 2011), we undertook this study to further explore and quantify driving stress and the related driving and occupational limitations among OIF–OEF veterans.

In this study, the occurrence of postdeployment driving stress among returning OEF–OIF servicemembers was generally evidenced by the overall results on the DSP, which measures the frequency of driving-related behaviors related to anger, impatience, and competition with and punishment of other drivers (Larson, 1996). In addition, using previously established norms on the DSP (Blanchard et al., 2000), we found that approximately 30% of male and female participants presented these risky driving behaviors to a degree that was statistically noticeable. Moreover, participants who drove off base more frequently during deployment showed higher scores on the DSP than those who drove less frequently, and those who assumed both driver and passenger roles during deployment scored significantly higher than those who were only a passenger. Combat veterans have acknowledged that one of their postdeployment driving issues is unintentionally reverting to evasive or battlefield driving tactics in the civilian setting, which can result in considerable stress and aggressive behavior in driving (Killgore et al., 2008; Lew et al., 2010).

People who show impaired driving ability may have limited opportunities to participate in work, education, social, recreational, and community activities. For this study, we developed the DOL to measure the degree to which participants perceived limitations in their occupational performance because of driving difficulties and discontinued driving postdeployment. Overall, mean scores on the DOL and its four subscales (Work/Education, Community Mobility, Leisure, and Social Participation) reached approximately 30% of their highest possible scores. Highly endorsed items (e.g., “I chose my place of residence to be close to work or school,” “I shopped at stores close by,” “I did leisure activities that did not require driving”), though conceptualized as relevant driving and occupational limitations in this study, could otherwise be indicative of the veterans’ problem-solving approaches (or alternatives) to overcome driving issues or reduce the necessity for driving. The two least endorsed items (i.e., “I took public transportation,” “I would rather have waited for someone else to drive”) could suggest the veterans’ strong desire to preserve their driving independence. According to Lew and colleagues (2010), most combat returnees resume driving on their return to civilian life despite their awareness of being at risk for impaired driving safety.

A significant moderate correlation was found between the DSP and the DOL total scores, and significant low to moderate correlations were found between the DSP total scores and scores on the three DOL subscales: Community Mobility (low), Leisure (moderate), and Social Participation (moderate). The findings suggest that returning OEF–OIF servicemembers who experience higher levels of driving stress may be limited in their participation in social activities, leisure, or instrumental activities of daily living for which they have to drive. However, we found no significant correlation between DSP total scores and DOL Work/Education subscale scores. This finding could be because the majority of participants (74.8%) were still serving on active duty the first 4 mo after they returned from their overseas deployment. As a result, the items related to work or school participation might not have fit in their contexts. Because of the inherent complexity of issues that could be involved in combat veterans’ transition to civilian society, we did not expect high correlations or exact causality between the driving and occupational issues studied. Nevertheless, it is clear that this transition is fraught with impediments across personal, occupational, and environmental dimensions (Burke et al., 2009; Stern et al., 2011).

Although combat veterans were reportedly able to resume driving instantly on their reentry in civilian society (Lew et al., 2010), paramount to the subject matter is how long it may take for their postdeployment driving to return to normal. Our study revealed individual differences in the length of time required to resume normal driving in the civilian setting. Some participants declared that it took 1 wk or less to drive normally after their overseas deployment; at the other extreme, participants reported still being unable to return to normal driving. Further data analysis concluded that those who reported needing >1 yr to return to normal driving and those who proclaimed their inability to resume normal driving had significantly higher levels of driving stress as measured by the DSP and greater limitations to driving and occupational participation as measured by the DOL than those who required less time to restart normal driving.

Although our current research was centered on the psychosocial aspect of postdeployment driving issues, previous studies have confirmed other areas of driving impairments and errors among combat veterans through the measure parameters of driving simulators (e.g., turning ability, merging, speed, adherence to traffic signals and signs, ability to avoid collisions; Amick, Kraft, & McGlinchey, 2013; Kraft, Amick, Barth, French, & Lew, 2010). Given the emerging findings of combat returnees’ impaired driving abilities and the potentially adverse effects of these impairments on daily occupations, occupational therapy practitioners can assume an important role in veterans’ rehabilitative interventions and reintegration programs.

Limitations and Future Research

Several limitations of this study merit consideration. First, the relatively small sample of participants recruited through nonprobabilistic sampling procedures limits the generalizability of the results. Second, the survey instruments used in this study directed the participants to recall their relevant driving and occupational issues experienced within the first 4 mo postdeployment. Participants’ levels of ability to retain information and recollect the temporal context could have affected the veracity of data. Last, because of the nature of a descriptive study, potentially confounding personal or contextual factors (e.g., military duty; diagnoses of TBI, PTSD, and substance–alcohol abuse; traffic conditions; MVCs) that could affect participants’ postdeployment driving and occupations were not adequately identified and controlled. Similarly, the conclusions regarding the relationships between driving stress and limitations in driving and occupations do not necessarily suggest causality. Future longitudinal cohort studies using large samples of combat veterans and systematic control and analysis of multiple factors are suggested to strengthen both the validity and the depth of the exploratory findings of this study.

Implications for Occupational Therapy Practice

The findings of this study inform occupational therapy practitioners how postdeployment driving stress can affect combat veterans’ daily driving and occupations and raise awareness about the need to design effective driver rehabilitation and community reintegration programs for this population. The results have the following implications:

Postdeployment driving stress can strike uninjured and undiagnosed combat veterans. Transition and reintegration programs for returning servicemembers should include holistic and individualized evaluation protocols that emphasize timely identification of postdeployment driving difficulties (e.g., driving stress, aggressive and unsafe driving) and the interplay between driving and occupational limitations.

Strategies should be implemented to minimize the adverse effects of driving difficulties on returning veterans’ valued occupations. Personal, environmental, or occupational adaptations and modifications can be considered throughout their transition and integration to civilian society.

Driver rehabilitation programs should address psychosocial issues (e.g., anger, impatience, aggressiveness) through the driving simulator and on-road evaluation and training components. A cognitive–behavioral approach can be used to enable returning veterans to first acknowledge unsafe driving and recognize the triggers, to practice coping strategies and relaxation, and finally to exercise control over risky driving behaviors and negative emotions carried over from evasive or battlefield driving tactics and experiences.

Footnotes

Acknowledgment

We express gratitude to all research participants for their time and contributions to this study.

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