Efficacy of an Occupational Therapy Driving Intervention for Returning Combat Veterans Sherrilene Classen, PhD, MPH, OT Reg. (Ont.), FAOTA; Nicole Leigh Cormack, BHS; Sandra M. Winter, PhD, OTR/L; Miriam Monahan, MS, OTR/L, CDRS; Abraham Yarney, MS; Amanda Link Lutz, MOT, OTR/L, DRS; and Kyle Platek, OTR/L, DRS keywords: automobile driving, intervention study, polytrauma ABSTRACT Polytrauma, including mild traumatic brain injury, posttraumatic stress disorder, and orthopedic conditions, is common among combat veterans (CVs) from Operations Enduring Freedom and Iraqi Freedom. Medical conditions, coupled with deployment-related training, may affect CVs’ fitness to drive and contribute to post-deployment crash and injury risks. However, empirical interventions are lacking. Therefore, the study purpose was to examine the efficacy of an occupational therapy driving intervention (OT-DI) with pre and post testing of CVs. Using a DriveSafety 250 simulator, Occupational Therapy-Driver Rehabilitation Specialists recorded driving errors. Eight CVs (mean age = 39.83, SD = 7.80) received three OT-DI sessions, which incorporated strategies to address driving errors and visual search retraining. We determined baseline driving errors (mean = 31.63, SD = 8.96) were double the number of posttest errors (mean = 15.38, SD = 9.71). At posttesting, a significant (p < 0.05) decrease was noted for total errors and lane maintenance. Despite study constraints, preliminary data support the efficacy of the OT-DI. [OTJR: Occupation, Participation and Health. 2014; 34(4):176-182.]
D
riving is considered an instrumental activity of daily living (IADL) and is, for many individuals, a key facilitator of independence, autonomy, quality of life, and participation in society (American Occupational Therapy Association, 2010). Being fit to drive depends on appropriate integration of visual, cognitive, perceptual, and motor skills in a dynamic environment, while maintaining control of the vehicle (Classen et al., 2011). Such skills can be compromised in combat veterans (CVs) with war-related injuries (Classen et al., 2009) such as polytrauma.
Polytrauma Polytrauma, a common threat to CVs who have served in Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF), includes mild traumatic brain injury (mTBI), posttraumatic stress disorder (PTSD), and orthopedic conditions (Owens,
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Kragh, Macaitis, Svoboda, & Wenke, 2007). Not surprisingly, these conditions may impair visual, cognitive, perceptual, and/or motor performance (Lew, Amick, Kraft, Stein, & Cifu, 2010). Specifically, a TBI resulting from an insult or penetration to the head may include symptoms such as headache, confusion, vertigo, exhaustion, and changes in mood (National Institute of Neurological Disorders and Stroke, 2014). A mTBI is characterized by loss of consciousness for less than 30 minutes, posttraumatic amnesia for less than 24 hours, or a Glasgow Coma Scale score of 13 to 15 (Carlson et al., 2009). From 20002013, the prevalence of TBI among CVs was 294,172, with 82.5% of these representing an mTBI (Defense and Veterans Brain Injury Center, 2014). TBI can have lasting effects on cognition, resulting in impaired memory, concentration, and anxiety (Lew et al., 2011), all of which can impair driving performance. PTSD is caused by a traumatic event that is followed by re-experiencing the event and results in
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avoidance behaviors, startle response, and changes in cognition, mood, and arousal (American Psychiatric Association, 2013). From 2000-2013, the prevalence of PTSD was 118,828 for all returning CVs from OEF/OIF (Congressional Research Service, 2014). PTSD mainly influences a person’s cognitive functions including attention, executive functions, or processing speed, which may impair driver fitness (Amick, Kraft, & McGlinchey, 2013; Lew et al., 2011). In addition to mTBI and PTSD, the battlemind phenomena—an effect of battlefield training prior to deployment—exists (Lew et al., 2010, 2011). This training consists of offensive (driving in the center of road to avoid explosive devices on the shoulder of the road) and defensive (scanning the environment instead of the immediate roadway) behaviors to prepare CVs for warzone survival. Without affording reintegration techniques to CVs, the battlemind phenomenon can impact driver fitness and promote behaviors that are not conducive to safe driving in civilian life (Hannold, Classen, Winter, Lanford, & Levy, 2013; Lew et al., 2011).
Driving Among Combat Veterans Motor vehicle crashes are one of the top four causes of injury and disability for OEF/OIF CVs (Lew et al., 2010). Researchers suggest that CVs display risky driving behaviors as evidenced by speeding, failing to signal, tailgating, and frequent or fast lane changes (Amick et al., 2013; Hannold et al., 2013; Zamorski & Kelley, 2012). Additionally, Lew et al. (2011) studied 205 CVs and found that 93% reported difficulty with driving upon return to civilian life. Particularly, this sample reported experi-
encing anger, attention deficits, and evasive driving tactics—learned during battlemind training—which impaired their driving in civilian life. Likewise, using a driving simulator, Classen et al. (2011) compared the driving errors of 18 CVs with mTBI and/ or PTSD to those of 20 healthy controls. They found that compared with the controls, CVs made statistically significantly more speeding and adjustmentto-stimuli (properly responding to road signs, other vehicles, pedestrians, or hazards) errors. Taken together, these studies suggest that CVs are more likely than controls to make driving errors, which may put them and/or other road users’ safety at risk. Although driving simulators afford safer options to on-road driving (Lew, Rosen, Thomander, & Poole, 2009) and have been recommended for use in veteran-centric driving assessment and intervention (Amick et al., 2013), a potential limitation is the onset and effects of simulator sickness. Classen and Owens (2010) examined the occurrence of simulator sickness in CVs by comparing Simulator Sickness Questionnaire (SSQ) scores (Kennedy, Lane, Berbaum, & Lilienthal, 1993) of 21 CVs with mTBI and/or PTSD to 23 healthy controls at baseline, post-acclimation, and post-driving. Compared with the controls under each of the three conditions (baseline, post-acclimation, and post-driving), the CVs experienced a statistically significant greater severity of simulator sickness. These findings suggest that caution needs to be employed when simulators are used to test fitness to drive of CVs. Specifically, simulator sickness mitigation strategies must be used to prevent the onset or decrease the duration of simulator sickness. Using a DriveSafety 250 simulator (Figure), researchers studied the effect of an occupational ther-
Dr. Classen is Professor and Chair, School of Occupational Therapy, Western University, London, Ontario, Canada; and Adjunct Professor, Department of Occupational Therapy and Institute for Mobility, Activity and Participation, College of Public Health and Health Professions, University of Florida, Gainesville, Florida. Ms. Cormack is Bachelor of Health Science Student, College of Public Health and Health Professions, University of Florida, Gainesville, Florida. Dr. Winter is Research Assistant Professor, Department of Occupational Therapy, and Research Assistant Professor, Institute for Mobility, Activity and Participation, College of Public Health and Health Professions, University of Florida, and Health Science Specialist, Gainesville site, Veterans Affairs Center of Innovation on Disability and Rehabilitation Research-CINDRR, North Florida/South Georgia Veterans Health System, Gainesville, Florida. Ms. Monahan is Adjunct Scholar, Department of Occupational Therapy, and Certified Driver Rehabilitation Specialist, Institute for Mobility, Activity and Participation, College of Public Health and Health Professions, University of Florida, Gainesville, Florida. Mr. Yarney is Graduate Research Assistant, Institute for Mobility, Activity and Participation, College of Public Health and Health Professions, University of Florida, Gainesville, Florida. Ms. Lutz is Driver Rehabilitation Specialist, University of Florida, Health Rehabilitation Center at Magnolia Parke, Gainesville, Florida. Mr. Platek is Driver Rehabilitation Specialist, University of Florida, Health Rehabilitation Center at Magnolia Parke, Gainesville, Florida. Submitted: May 5, 2014; Accepted: August 4, 2014; Posted online: October 20, 2014 The authors have no financial or proprietary interest in the materials presented herein. Address correspondence to Sherrilene Classen, PhD, MPH, OT Reg. (Ont.), FAOTA, Professor and Chair, School of Occupational Therapy, Western University, Elborn College, 1201 Western Road, London, Ontario, Canada N6G 1H1; e-mail: [email protected]. doi:10.3928/15394492-20141006-01
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Figure. DriveSafety250 simulator in Dodge® Sprinter® van. The van contained a wheelchair lift, live primary controls (i.e., gas and brake pedals, steering wheel, turn signals), audio system with engine sound, and a speedometer.
apy driving intervention (OT-DI) in a single subject design (Classen, Monahan, Canonizado, & Winter, 2014). The Occupational Therapy-Driver Rehabilitation Specialists (OT-CDRS) administered baseline clinical and simulated driving assessments; conducted three intervention sessions that provided strategies for driving errors, retrained visual scanning, and incorporated commentary driving; and administered a post-evaluation resembling baseline testing. Pre- and post-intervention clinical test results were similar, whereas driving errors were reduced or stayed the same: lane maintenance 23 vs. 7, vehicle positioning 5 vs. 1, signaling 2 vs. 0, speed regulation 1 vs. 1, visual scanning 1 vs. 0, and gap acceptance 1 vs. 0.
Rationale and Significance Driving is a valued instrumental activity of daily living but may be compromised in CVs as a result of the effects of polytrauma and battlefield mindset. The use of driving simulators affords safer options to assess fitness to drive abilities, but mitigation strategies to prevent or reduce simulator sickness must be employed (Classen & Owens, 2010). Although the literature reveals information on the driving errors (Amick et al., 2013; Classen et al., 2011; Lew et al., 2011) or driving behaviors (Hannold et al., 2013; Zamorski & Kelley, 2012) of returning CVs, only one single-subject driving intervention study (Classen et al., in press) exists in the current literature.
Purpose and Research Question The objective of this pilot study was to determine the impact of an OT-DI on the type and num-
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ber of driving errors made by the CVs in a driving simulator. Based on previous literature (discussed above), the driving errors of interest were speed regulation (maintaining speed limits), lane maintenance (lateral positioning of the vehicle), visual scanning (checking mirrors before lane changes and checking cross streets at intersections), gap acceptance (determining a safe time to cross in front of oncoming traffic), adjustment to stimuli (properly responding to road signs, other vehicles, pedestrians, or hazards), vehicle positioning (space between vehicles), signaling (appropriate use of turn signals), as well as the total number of errors. The research question was: For OIF/OEF CVs with polytrauma, what is the efficacy of an OT-DI? Based on the single-subject design study, we expected to see a decrease in, at least, the total number of errors post-intervention.
Method This study was approved by the University of Florida’s Institutional Review Board, the North Florida/ South Georgia Veterans Affairs Research Committee, and the Department of Defense Human Research Protection Office. All participants provided written informed consent before being enrolled in the study. Recruitment We recruited participants via flyers, community and professional presentations by the study team, and clinician/veterans affairs (VA) medical team referrals. Eight returning CVs were recruited from VA facilities in North Florida/South Georgia. Eligibility requirements included: (a) a history of OIF/ OEF deployment; (b) diagnosis of mTBI, PTSD, or orthopedic injury; (c) driving prior to the injury/ condition; (d) valid driver’s license; (e) being community dwelling; (f) potential for following driving safety recommendations and community integration strategies (Mini-Mental State Examination score of at least 24/30); and (g) ability to participate in a driving evaluation battery. Measures Using standardized data collection sheets (Classen et al., 2011), we obtained demographic information such as age, gender, race, living status, education, marital status, and blast exposure. Using the driving history and habits section of the validated Fitness-toDrive Screening Measure (Classen et al., 2012), we also collected from the caregiver (e.g., family member, spouse, significant other, friend), the number of citations and crashes of the CVs in the past 3 years. Three
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Table 1 (cont’d)
Table 1 Descriptive Statistics for Combat Veterans on Demographics, Driving History, Exposures, and Simulator Sickness (N = 8) Variable
Statistic
Demographic data
Descriptive Statistics for Combat Veterans on Demographics, Driving History, Exposures, and Simulator Sickness (N = 8) Variable
Statistic
Exposure during combat
Mean age (SD)
39.83 (7.80) 8 (100)
Male gender, n (%) Race, n (%)
Primary exposurec, n (%) Explosive device
4 (50)
Mortar
4 (50)
White
7 (87.5)
Sniper fire
Othera
1 (12.5)
Grenade
2 (25)
Land mine
2 (25)
Ethnicity, n (%) Not Hispanic
7 (87.5)
Hispanic/Latino
1 (12.5)
Educational level, n (%)
Rocket propelled grenade
2 (25)
Some college
1 (12.5)
AA degree or higher
5 (62.5)
Marital status, n (%) Married
6 (75)
Divorced
2 (25)
Living status, n (%) With someone
6 (75)
Alone
2 (25)
c
Secondary exposure , n (%) Motor vehicle accident
Completed high school/GED (12th grade)
6 (75)
Falls
5 (62.5)
Flying debris
3 (37.5)
Falling debris
2 (25)
Note. GED = General Education Development; AA = Associate in Arts. a Self-reported as Black/Irish; b Only six proxies provided feedback on citation and crash history; c Frequencies and percentages total more than 100%, as a combat veteran could have experienced more than one exposure.
2 (25)
Driving history Have driver’s license, n (%)
8 (100) b
Number of citations in past 3 years , n (%) None
3 (50)
One
3 (50) b
Number of crashes in past 3 years , n (%) None
2 (33.3)
One
1 (16.7)
Two or more
3 (37.5)
3 (50)
OT-DRSs completed the visual, cognitive, sensory, and motor function tests (not further discussed), and assessed the seven driving errors, with a standardized score sheet (Classen et al., 2011) in a DriveSafety CDS250 Mobile VA Simulator (DriveSafety, Inc., Salt Lake City, UT). The interrater reliability among the each of the two secondary raters and the primary rater was 99.3% and 98%, respectively. Intervention The OT-DI was administered in three sessions, lasting approximately 60 to 90 minutes each and
typically occurring over a 6- to 8-week period. Specifically, in the first session, the OT-DRSs discussed baseline driving errors with the CV and explained strategies to diminish these errors. In the second session, the OT-DRSs used a visual search CD that depicted roadways typical of those found in the United States (Monahan, 2009). The CVs first identified distractions they were taught to attend to while in combat and then verbally called out the critical roadway information (e.g., a car pulling out of a driveway, a traffic light turning red as they are approaching) to manage safe driving in civilian life. The third session consisted of the CVs performing a narrated drive applying and demonstrating the strategies taught previously. The OT-DRSs assessed driving errors and addressed those observed errors via feedback. Posttesting consisted of the OT-DRSs repeating the baseline test. Procedure We used a pre/posttest experimental design that included baseline testing (clinical tests and simulated drive), three OT-DI sessions of 1 hour each, and a posttest similar to baseline testing. All testing was
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Table 2 Within-Group Differences for Simulator Sickness and Driving Errors by Type and Number (N = 8) Baseline
Posttest
Mean (SD)
Mean (SD)
Statistic (p Value)
Pre-acclimation
171.44 (163.42)
180.02 (205.53)
–0.42 (0.67)
Post-acclimation
236.82 (235.46)
135.55 (107.94)
–1.21 (0.23)
Post driving
370.14 (428.10)
226.19 (208.40)
–0.73 (0.46)
2.13 (1.25)
1.63 (1.41)
–0.68 (0.50)
Variable Total simulator sickness score
Driving errors Gap acceptance Signaling
2.00 (2.00)
0.50 (1.07)
–1.54 (0.13)
Adjustment-to-stimuli
1.13 (2.80)
0.38 (0.74)
–0.18 (0.85)
Vehicle positioning
2.38 (2.13)
0.63 (0.52)
–1.84 (0.07)
8.38 (5.73)
3.88 (4.22)
–1.89 (0.06)
Speed regulation Under speeding Over speeding
2.63 (3.62)
1.13 (1.73)
–0.77 (0.44)
Lane maintenance
7.88 (5.74)
4.13 (3.04)
–1.99 (0.05)
Encroach
.38 (0.74)
0.00 (0.00)
–1.34 (0.18)
Wide
4.13 (1.64)
3.13 (3.31)
–1.06 (0.29)
Visual scanning
0.63 (0.74)
0.00 (0.00)
–1.89 (0.06)
Total number of errors
31.63 (8.96)
15.38 (9.71)
–2.24 (0.03)
conducted in the mobile simulator (Figure) situated in a parking lot on the VA premise. The van contained a wheelchair lift, live primary controls (i.e., gas and brake pedals, steering wheel, turn signals), audio system with engine sound, and a speedometer. The CVs drove two 5-minute acclimation scenarios, followed by two main drives. The acclimation drive was used as a simulator sickness mitigation strategy and to allow participants to feel confident and comfortable in the simulator. The first main drive consisted of a suburban setting with residential neighborhoods and rural roads and lasted 6 minutes. The second main drive consisted of city and highway settings and lasted 10 minutes. Based on previous interviews with the CVs (Hannold et al., 2013), specific triggers—stimuli with potential to elicit a response of hypervigilence—were built into the scenarios, and the OT-DRSs evaluated the CVs’ responses accordingly. These triggers, which included trash bags, pedestrians crossing the street, roadkill, the sound of a helicopter flying overhead, and a loud backfire noise, were strategically embedded into the roadways scenarios. Additionally, the OT-DRSs screened the participants for simulator sickness using the SSQ at three time periods: before
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the acclimation drive, after the acclimation drive, and after the main drive (Kennedy et al., 1993). The SSQ includes 14 questions relating to three domains: nausea, oculomotor, and disorientation symptoms, resulting in a total score used in this study. Analysis A trained research assistant entered all of the data into a secure and password-protected server network, while the principal investigator performed quality control spot checks. In consultation with a biostatistician, we analyzed the data using SPSS version 21. Specifically, we used descriptive statistics (i.e., frequencies, percentages, means, standard deviations) to summarize the data and a Shapiro-Wilks test to determine the normality of the data. Based on normality results, we used the nonparametric Wilcoxon signed-rank test to determine whether there was a statistically significant difference (p < 0.05) among the baseline and posttest driving errors, as well as in the simulator sickness scores.
Results Table 1 shows the descriptive statistics for eight CVs (mean age = 39.83, SD = 7.80 years, age range =
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30 to 55). Overall, the participants were male, highly educated, and White, and most did not live alone. All participants had a valid driver’s license, and according to proxy report, three CVs had received a driving citation or were involved in a crash in the past 3 years. Additionally, six CVs reported being in a motor vehicle crash during deployment. Table 2 shows the descriptive statistics for simulator sickness and driving errors by type and number. With the exception of gap acceptance, all other errors decreased in mean number, with lane maintenance, under speeding, and total driving errors decreasing the most. A Spearman correlation test, used for both baseline and posttest 1 conditions, indicated that no significant correlations existed between total driving errors and total simulator sickness scores post-acclimation (r = –0.18, p = 0.68) or post-drive (r = 0.04, p = 0.93). The Shapiro-Wilks test indicated that almost all of the variables examined were statistically significant (p < 0.05), and as such, the data were not normally distributed. Table 2 illustrates the results of the Wilcoxon signed-rank test for the SSQ scores and the driving errors. No statistically significant difference existed among simulator sickness scores during baseline testing or during posttesting. However, we did observe a statistically significant decrease in lane maintenance errors and total number of driving errors.
Discussion The purpose of this pilot study was to determine whether the OT-DI could impact the type and number of driving errors of OEF/OIF CVs with polytrauma, by comparing pre- and post-intervention results. In this study, unlike others, all of the participants were men and the majority were White. The primary deployment exposures reported were mortars/ explosive devices or sniper fire, while most of the secondary exposures were caused by motor vehicle accidents—both of which are common among OEF/ OIF CVs and consistent with prior research (Classen et al., 2011). Unlike previous work, we found no statistically significant differences in simulator sickness scores between baseline and follow-up testing (Classen & Owens, 2010). The small sample size in this study may have obscured a difference if one truly existed (type 2 error). Total driving errors and lane maintenance errors significantly decreased from baseline to posttest 1, indicating potential efficacy of the OT-DI. These findings are also consistent with a single-subject design study, where the total driving errors, as well as
lane maintenance errors, decreased post-intervention (Classen et al., 2014). All seven driving errors decreased after the intervention but did not reach statistical significance, potentially due to the small sample size and type 2 error. However, the cumulative effect of these decreases were perhaps evident in the statistically significant decrease of the total number of driving errors post-intervention, which were a two-fold decrease when compared with baseline. The ability to maintain one’s lane suggests CVs were able to attend to roadway information and adjust their vehicle control responses accordingly. Clearly, for the CVs to have decreased lane maintenance errors post intervention suggests they disregarded triggers (e.g., trash, dead animals, or loud noises), which prior to intervention, impaired their lane maintenance ability. As such, we surmised that the CVs could adapt their driving behaviors, specifically ignoring triggers, to maintain their lanes post intervention. Of course, further follow up is needed to determine whether such changes carry over to realworld driving. The main limitations of this pilot study pertain to sample size and the absence of a control group. However, ongoing research by our group, adequately powered to detect a statistically significant difference in driving errors, is currently enrolling participants in an experimental and control arm. The gender and racial bias evident in the study also restrict the generalizability of results to samples not fitting the profile of this study.
Conclusion Despite these limitations, the results of this pilot study suggest that an OT-DI is efficacious, at least in the short term, for OEF/OIF CVs with polytrauma. Specifically, the CVs in this study showed a two-fold improvement in maintaining their lanes or decreasing their total number of driving errors post intervention. More CVs are being tested to further validate the OT-DI. Thus, the OT-DI shows potential to improve driver fitness in the simulator and, as such, lays an important foundation for eventual decreases in risk of crash-related injuries or death. Acknowledgments
This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Congressionally Directed Medical Research Program under Award W81XWH-11-1-0454. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the Department of Defense. Infrastructure and support were provided by the University of Florida’s Institute for Mobility, Activity,
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and Participation. This work was also supported with resources and the use of facilities within the North Florida/ South Georgia Veterans Health System, the Malcom Randall VA Medical Center, and the VA’s Center of Innovation on Disability and Rehabilitation Research, Gainesville, Florida.
References American Occupational Therapy Association. (2010). Statements: Driving and community mobility. American Journal of Occupational Therapy, 64(6 Suppl.), S112-S124. doi:10.5014/ ajot.2010.64S112 American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author. Amick, M.M., Kraft, M., & McGlinchey, R. (2013). Driving simulator performance of veterans from the Iraq and Afghanistan wars. Journal of Rehabilitation Research & Development, 50, 463-470. Carlson, K., Kehle, S., Meis, L., Greer, N., MacDonald, R., Rutks, I., & Wilt, T. J. (2009). The assessment and treatment of individuals with history of traumatic brain injury and post-traumatic stress disorder: A systematic review of the evidence. Retrieved from the National Center for Biotechnology Information website: http://www.ncbi.nlm.nih.gov/books/NBK49144/ Classen, S., Levy, C., McCarthy, D., Mann, W.C., Lanford, D., & Waid-Ebbs, K.J. (2009). Traumatic brain injury and driving assessment: An evidence based literature review. American Journal of Occupational Therapy, 63, 580-591. Classen, S., Levy, C., Meyer, D., Bewernitz, M., Lanford, D.N., & Mann, W.C. (2011). Simulated driving performance of combat veterans with mild traumatic brain injury and posttraumatic stress disorder: A pilot study. American Journal of Occupational Therapy, 65, 419-427. Classen, S., Monahan, M., Canonizado, M., & Winter, S.M. (2014). An occupational therapy driving intervention’s utility for a combat veteran. American Journal of Occupational Therapy, 68, 405-411. Classen, S., & Owens, A. B. (2010). Simulator sickness among returning combat veterans with mild traumatic brain injury and/or post-traumatic stress disorder. Advances in Transportation Studies, 2010 Special Issue, 45-52. Classen, S., Wen, P.S., Velozo, C., Bédard, M., Winter, S.M., Brumback, B., & Lanford, D.N. (2012). Psychometrics of the self-report Safe Driving Behavior Measure for older
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adults. American Journal of Occupational Therapy, 66, 233-241. doi:10.5014/ajot.2012.001834 Congressional Research Service. (2014). U.S. military casualty statistics: Operation New Dawn, Operation Iraqi Freedom, and Operation Enduring Freedom. Retrieved from http://www.fas. org/sgp/crs/natsec/RS22452.pdf Defense and Veterans Brain Injury Center. (2014). DOD numbers for traumatic brain injury. Retrieved from http://dvbic.dcoe. mil/dod-worldwide-numbers-tbi Hannold, E.M., Classen, S., Winter, S., Lanford, D., & Levy, C. (2013). Exploratory pilot study of driving perceptions among OIF/OEF veterans with mTBI and PTSD. Journal of Rehabilitation Research & Development, 50, 1315-1330. Kennedy, R.S., Lane, N.E., Berbaum, K.S., & Lilienthal, M.G. (1993). Simulator Sickness Questionnaire: An enhanced method for quantifying simulator sickness. The International Journal of Aviation Psychology, 3, 203-220. Lew, H.L., Amick, M.M., Kraft, M., Stein, M.B., & Cifu, D.X. (2010). Potential driving issues in combat returnees. NeuroRehabilitation, 26, 271-278. doi:10.3233/NRE-2010-0562 Lew, H.L., Kraft, M., Pogoda, T.K., Amick, M.M., Woods, P., & Cifu, D.X. (2011). Prevalence and characteristics of driving difficulties in Operation Iraqi Freedom/Operation Enduring Freedom combat returnees. Journal of Rehabilitation Research and Development, 48, 913-926. doi:10.1682/JRRD.2010.08.0140 Lew, H.L., Rosen, P.N., Thomander, D., & Poole, J.H. (2009). The potential utility of driving simulators in the cognitive rehabilitation of combat-returnees with traumatic brain injury. Journal of Head Trauma Rehabilitation, 24, 51-56. Monahan, M. (2009). Visual search skills. Richmond, VT: Driver Rehabilitation Institute. National Institute of Neurological Disorders and Stroke. (2014). NINDS traumatic brain injury information page. Retrieved from http://www.ninds.nih.gov/disorders/tbi/tbi.htm Owens, B., Kragh, J.J., Macaitis, J., Svoboda, S., & Wenke, J. (2007). Characterization of extremity wounds in Operation Iraqi Freedom and Operation Enduring Freedom. Journal of Orthopedic Trauma, 21, 254-257. Zamorski, M.A., & Kelley, A.M. (2012). Risky driving behaviour. In Psychological aspects of deployment and health behaviours (NATO report TR-HFM-164, pp. 5-1-5-21). Neuilly-sur-Seine, France: Research and Technology Organisation of the North Atlantic Treaty Organisation. Retrieved from http://natorto. cbw.pl/uploads/2012/5/$$TR-HFM-164-ALL.pdf
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D
riving is considered an instrumental activity of daily living (IADL) and is, for many individuals, a key facilitator of independence, autonomy, quality of life, and participation in society (American Occupational Therapy Association, 2010). Being fit to drive depends on appropriate integration of visual, cognitive, perceptual, and motor skills in a dynamic environment, while maintaining control of the vehicle (Classen et al., 2011). Such skills can be compromised in combat veterans (CVs) with war-related injuries (Classen et al., 2009) such as polytrauma.
Polytrauma Polytrauma, a common threat to CVs who have served in Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF), includes mild traumatic brain injury (mTBI), posttraumatic stress disorder (PTSD), and orthopedic conditions (Owens,
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Kragh, Macaitis, Svoboda, & Wenke, 2007). Not surprisingly, these conditions may impair visual, cognitive, perceptual, and/or motor performance (Lew, Amick, Kraft, Stein, & Cifu, 2010). Specifically, a TBI resulting from an insult or penetration to the head may include symptoms such as headache, confusion, vertigo, exhaustion, and changes in mood (National Institute of Neurological Disorders and Stroke, 2014). A mTBI is characterized by loss of consciousness for less than 30 minutes, posttraumatic amnesia for less than 24 hours, or a Glasgow Coma Scale score of 13 to 15 (Carlson et al., 2009). From 20002013, the prevalence of TBI among CVs was 294,172, with 82.5% of these representing an mTBI (Defense and Veterans Brain Injury Center, 2014). TBI can have lasting effects on cognition, resulting in impaired memory, concentration, and anxiety (Lew et al., 2011), all of which can impair driving performance. PTSD is caused by a traumatic event that is followed by re-experiencing the event and results in
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avoidance behaviors, startle response, and changes in cognition, mood, and arousal (American Psychiatric Association, 2013). From 2000-2013, the prevalence of PTSD was 118,828 for all returning CVs from OEF/OIF (Congressional Research Service, 2014). PTSD mainly influences a person’s cognitive functions including attention, executive functions, or processing speed, which may impair driver fitness (Amick, Kraft, & McGlinchey, 2013; Lew et al., 2011). In addition to mTBI and PTSD, the battlemind phenomena—an effect of battlefield training prior to deployment—exists (Lew et al., 2010, 2011). This training consists of offensive (driving in the center of road to avoid explosive devices on the shoulder of the road) and defensive (scanning the environment instead of the immediate roadway) behaviors to prepare CVs for warzone survival. Without affording reintegration techniques to CVs, the battlemind phenomenon can impact driver fitness and promote behaviors that are not conducive to safe driving in civilian life (Hannold, Classen, Winter, Lanford, & Levy, 2013; Lew et al., 2011).
Driving Among Combat Veterans Motor vehicle crashes are one of the top four causes of injury and disability for OEF/OIF CVs (Lew et al., 2010). Researchers suggest that CVs display risky driving behaviors as evidenced by speeding, failing to signal, tailgating, and frequent or fast lane changes (Amick et al., 2013; Hannold et al., 2013; Zamorski & Kelley, 2012). Additionally, Lew et al. (2011) studied 205 CVs and found that 93% reported difficulty with driving upon return to civilian life. Particularly, this sample reported experi-
encing anger, attention deficits, and evasive driving tactics—learned during battlemind training—which impaired their driving in civilian life. Likewise, using a driving simulator, Classen et al. (2011) compared the driving errors of 18 CVs with mTBI and/ or PTSD to those of 20 healthy controls. They found that compared with the controls, CVs made statistically significantly more speeding and adjustmentto-stimuli (properly responding to road signs, other vehicles, pedestrians, or hazards) errors. Taken together, these studies suggest that CVs are more likely than controls to make driving errors, which may put them and/or other road users’ safety at risk. Although driving simulators afford safer options to on-road driving (Lew, Rosen, Thomander, & Poole, 2009) and have been recommended for use in veteran-centric driving assessment and intervention (Amick et al., 2013), a potential limitation is the onset and effects of simulator sickness. Classen and Owens (2010) examined the occurrence of simulator sickness in CVs by comparing Simulator Sickness Questionnaire (SSQ) scores (Kennedy, Lane, Berbaum, & Lilienthal, 1993) of 21 CVs with mTBI and/or PTSD to 23 healthy controls at baseline, post-acclimation, and post-driving. Compared with the controls under each of the three conditions (baseline, post-acclimation, and post-driving), the CVs experienced a statistically significant greater severity of simulator sickness. These findings suggest that caution needs to be employed when simulators are used to test fitness to drive of CVs. Specifically, simulator sickness mitigation strategies must be used to prevent the onset or decrease the duration of simulator sickness. Using a DriveSafety 250 simulator (Figure), researchers studied the effect of an occupational ther-
Dr. Classen is Professor and Chair, School of Occupational Therapy, Western University, London, Ontario, Canada; and Adjunct Professor, Department of Occupational Therapy and Institute for Mobility, Activity and Participation, College of Public Health and Health Professions, University of Florida, Gainesville, Florida. Ms. Cormack is Bachelor of Health Science Student, College of Public Health and Health Professions, University of Florida, Gainesville, Florida. Dr. Winter is Research Assistant Professor, Department of Occupational Therapy, and Research Assistant Professor, Institute for Mobility, Activity and Participation, College of Public Health and Health Professions, University of Florida, and Health Science Specialist, Gainesville site, Veterans Affairs Center of Innovation on Disability and Rehabilitation Research-CINDRR, North Florida/South Georgia Veterans Health System, Gainesville, Florida. Ms. Monahan is Adjunct Scholar, Department of Occupational Therapy, and Certified Driver Rehabilitation Specialist, Institute for Mobility, Activity and Participation, College of Public Health and Health Professions, University of Florida, Gainesville, Florida. Mr. Yarney is Graduate Research Assistant, Institute for Mobility, Activity and Participation, College of Public Health and Health Professions, University of Florida, Gainesville, Florida. Ms. Lutz is Driver Rehabilitation Specialist, University of Florida, Health Rehabilitation Center at Magnolia Parke, Gainesville, Florida. Mr. Platek is Driver Rehabilitation Specialist, University of Florida, Health Rehabilitation Center at Magnolia Parke, Gainesville, Florida. Submitted: May 5, 2014; Accepted: August 4, 2014; Posted online: October 20, 2014 The authors have no financial or proprietary interest in the materials presented herein. Address correspondence to Sherrilene Classen, PhD, MPH, OT Reg. (Ont.), FAOTA, Professor and Chair, School of Occupational Therapy, Western University, Elborn College, 1201 Western Road, London, Ontario, Canada N6G 1H1; e-mail: [email protected]. doi:10.3928/15394492-20141006-01
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Figure. DriveSafety250 simulator in Dodge® Sprinter® van. The van contained a wheelchair lift, live primary controls (i.e., gas and brake pedals, steering wheel, turn signals), audio system with engine sound, and a speedometer.
apy driving intervention (OT-DI) in a single subject design (Classen, Monahan, Canonizado, & Winter, 2014). The Occupational Therapy-Driver Rehabilitation Specialists (OT-CDRS) administered baseline clinical and simulated driving assessments; conducted three intervention sessions that provided strategies for driving errors, retrained visual scanning, and incorporated commentary driving; and administered a post-evaluation resembling baseline testing. Pre- and post-intervention clinical test results were similar, whereas driving errors were reduced or stayed the same: lane maintenance 23 vs. 7, vehicle positioning 5 vs. 1, signaling 2 vs. 0, speed regulation 1 vs. 1, visual scanning 1 vs. 0, and gap acceptance 1 vs. 0.
Rationale and Significance Driving is a valued instrumental activity of daily living but may be compromised in CVs as a result of the effects of polytrauma and battlefield mindset. The use of driving simulators affords safer options to assess fitness to drive abilities, but mitigation strategies to prevent or reduce simulator sickness must be employed (Classen & Owens, 2010). Although the literature reveals information on the driving errors (Amick et al., 2013; Classen et al., 2011; Lew et al., 2011) or driving behaviors (Hannold et al., 2013; Zamorski & Kelley, 2012) of returning CVs, only one single-subject driving intervention study (Classen et al., in press) exists in the current literature.
Purpose and Research Question The objective of this pilot study was to determine the impact of an OT-DI on the type and num-
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ber of driving errors made by the CVs in a driving simulator. Based on previous literature (discussed above), the driving errors of interest were speed regulation (maintaining speed limits), lane maintenance (lateral positioning of the vehicle), visual scanning (checking mirrors before lane changes and checking cross streets at intersections), gap acceptance (determining a safe time to cross in front of oncoming traffic), adjustment to stimuli (properly responding to road signs, other vehicles, pedestrians, or hazards), vehicle positioning (space between vehicles), signaling (appropriate use of turn signals), as well as the total number of errors. The research question was: For OIF/OEF CVs with polytrauma, what is the efficacy of an OT-DI? Based on the single-subject design study, we expected to see a decrease in, at least, the total number of errors post-intervention.
Method This study was approved by the University of Florida’s Institutional Review Board, the North Florida/ South Georgia Veterans Affairs Research Committee, and the Department of Defense Human Research Protection Office. All participants provided written informed consent before being enrolled in the study. Recruitment We recruited participants via flyers, community and professional presentations by the study team, and clinician/veterans affairs (VA) medical team referrals. Eight returning CVs were recruited from VA facilities in North Florida/South Georgia. Eligibility requirements included: (a) a history of OIF/ OEF deployment; (b) diagnosis of mTBI, PTSD, or orthopedic injury; (c) driving prior to the injury/ condition; (d) valid driver’s license; (e) being community dwelling; (f) potential for following driving safety recommendations and community integration strategies (Mini-Mental State Examination score of at least 24/30); and (g) ability to participate in a driving evaluation battery. Measures Using standardized data collection sheets (Classen et al., 2011), we obtained demographic information such as age, gender, race, living status, education, marital status, and blast exposure. Using the driving history and habits section of the validated Fitness-toDrive Screening Measure (Classen et al., 2012), we also collected from the caregiver (e.g., family member, spouse, significant other, friend), the number of citations and crashes of the CVs in the past 3 years. Three
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Table 1 (cont’d)
Table 1 Descriptive Statistics for Combat Veterans on Demographics, Driving History, Exposures, and Simulator Sickness (N = 8) Variable
Statistic
Demographic data
Descriptive Statistics for Combat Veterans on Demographics, Driving History, Exposures, and Simulator Sickness (N = 8) Variable
Statistic
Exposure during combat
Mean age (SD)
39.83 (7.80) 8 (100)
Male gender, n (%) Race, n (%)
Primary exposurec, n (%) Explosive device
4 (50)
Mortar
4 (50)
White
7 (87.5)
Sniper fire
Othera
1 (12.5)
Grenade
2 (25)
Land mine
2 (25)
Ethnicity, n (%) Not Hispanic
7 (87.5)
Hispanic/Latino
1 (12.5)
Educational level, n (%)
Rocket propelled grenade
2 (25)
Some college
1 (12.5)
AA degree or higher
5 (62.5)
Marital status, n (%) Married
6 (75)
Divorced
2 (25)
Living status, n (%) With someone
6 (75)
Alone
2 (25)
c
Secondary exposure , n (%) Motor vehicle accident
Completed high school/GED (12th grade)
6 (75)
Falls
5 (62.5)
Flying debris
3 (37.5)
Falling debris
2 (25)
Note. GED = General Education Development; AA = Associate in Arts. a Self-reported as Black/Irish; b Only six proxies provided feedback on citation and crash history; c Frequencies and percentages total more than 100%, as a combat veteran could have experienced more than one exposure.
2 (25)
Driving history Have driver’s license, n (%)
8 (100) b
Number of citations in past 3 years , n (%) None
3 (50)
One
3 (50) b
Number of crashes in past 3 years , n (%) None
2 (33.3)
One
1 (16.7)
Two or more
3 (37.5)
3 (50)
OT-DRSs completed the visual, cognitive, sensory, and motor function tests (not further discussed), and assessed the seven driving errors, with a standardized score sheet (Classen et al., 2011) in a DriveSafety CDS250 Mobile VA Simulator (DriveSafety, Inc., Salt Lake City, UT). The interrater reliability among the each of the two secondary raters and the primary rater was 99.3% and 98%, respectively. Intervention The OT-DI was administered in three sessions, lasting approximately 60 to 90 minutes each and
typically occurring over a 6- to 8-week period. Specifically, in the first session, the OT-DRSs discussed baseline driving errors with the CV and explained strategies to diminish these errors. In the second session, the OT-DRSs used a visual search CD that depicted roadways typical of those found in the United States (Monahan, 2009). The CVs first identified distractions they were taught to attend to while in combat and then verbally called out the critical roadway information (e.g., a car pulling out of a driveway, a traffic light turning red as they are approaching) to manage safe driving in civilian life. The third session consisted of the CVs performing a narrated drive applying and demonstrating the strategies taught previously. The OT-DRSs assessed driving errors and addressed those observed errors via feedback. Posttesting consisted of the OT-DRSs repeating the baseline test. Procedure We used a pre/posttest experimental design that included baseline testing (clinical tests and simulated drive), three OT-DI sessions of 1 hour each, and a posttest similar to baseline testing. All testing was
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Table 2 Within-Group Differences for Simulator Sickness and Driving Errors by Type and Number (N = 8) Baseline
Posttest
Mean (SD)
Mean (SD)
Statistic (p Value)
Pre-acclimation
171.44 (163.42)
180.02 (205.53)
–0.42 (0.67)
Post-acclimation
236.82 (235.46)
135.55 (107.94)
–1.21 (0.23)
Post driving
370.14 (428.10)
226.19 (208.40)
–0.73 (0.46)
2.13 (1.25)
1.63 (1.41)
–0.68 (0.50)
Variable Total simulator sickness score
Driving errors Gap acceptance Signaling
2.00 (2.00)
0.50 (1.07)
–1.54 (0.13)
Adjustment-to-stimuli
1.13 (2.80)
0.38 (0.74)
–0.18 (0.85)
Vehicle positioning
2.38 (2.13)
0.63 (0.52)
–1.84 (0.07)
8.38 (5.73)
3.88 (4.22)
–1.89 (0.06)
Speed regulation Under speeding Over speeding
2.63 (3.62)
1.13 (1.73)
–0.77 (0.44)
Lane maintenance
7.88 (5.74)
4.13 (3.04)
–1.99 (0.05)
Encroach
.38 (0.74)
0.00 (0.00)
–1.34 (0.18)
Wide
4.13 (1.64)
3.13 (3.31)
–1.06 (0.29)
Visual scanning
0.63 (0.74)
0.00 (0.00)
–1.89 (0.06)
Total number of errors
31.63 (8.96)
15.38 (9.71)
–2.24 (0.03)
conducted in the mobile simulator (Figure) situated in a parking lot on the VA premise. The van contained a wheelchair lift, live primary controls (i.e., gas and brake pedals, steering wheel, turn signals), audio system with engine sound, and a speedometer. The CVs drove two 5-minute acclimation scenarios, followed by two main drives. The acclimation drive was used as a simulator sickness mitigation strategy and to allow participants to feel confident and comfortable in the simulator. The first main drive consisted of a suburban setting with residential neighborhoods and rural roads and lasted 6 minutes. The second main drive consisted of city and highway settings and lasted 10 minutes. Based on previous interviews with the CVs (Hannold et al., 2013), specific triggers—stimuli with potential to elicit a response of hypervigilence—were built into the scenarios, and the OT-DRSs evaluated the CVs’ responses accordingly. These triggers, which included trash bags, pedestrians crossing the street, roadkill, the sound of a helicopter flying overhead, and a loud backfire noise, were strategically embedded into the roadways scenarios. Additionally, the OT-DRSs screened the participants for simulator sickness using the SSQ at three time periods: before
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the acclimation drive, after the acclimation drive, and after the main drive (Kennedy et al., 1993). The SSQ includes 14 questions relating to three domains: nausea, oculomotor, and disorientation symptoms, resulting in a total score used in this study. Analysis A trained research assistant entered all of the data into a secure and password-protected server network, while the principal investigator performed quality control spot checks. In consultation with a biostatistician, we analyzed the data using SPSS version 21. Specifically, we used descriptive statistics (i.e., frequencies, percentages, means, standard deviations) to summarize the data and a Shapiro-Wilks test to determine the normality of the data. Based on normality results, we used the nonparametric Wilcoxon signed-rank test to determine whether there was a statistically significant difference (p < 0.05) among the baseline and posttest driving errors, as well as in the simulator sickness scores.
Results Table 1 shows the descriptive statistics for eight CVs (mean age = 39.83, SD = 7.80 years, age range =
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30 to 55). Overall, the participants were male, highly educated, and White, and most did not live alone. All participants had a valid driver’s license, and according to proxy report, three CVs had received a driving citation or were involved in a crash in the past 3 years. Additionally, six CVs reported being in a motor vehicle crash during deployment. Table 2 shows the descriptive statistics for simulator sickness and driving errors by type and number. With the exception of gap acceptance, all other errors decreased in mean number, with lane maintenance, under speeding, and total driving errors decreasing the most. A Spearman correlation test, used for both baseline and posttest 1 conditions, indicated that no significant correlations existed between total driving errors and total simulator sickness scores post-acclimation (r = –0.18, p = 0.68) or post-drive (r = 0.04, p = 0.93). The Shapiro-Wilks test indicated that almost all of the variables examined were statistically significant (p < 0.05), and as such, the data were not normally distributed. Table 2 illustrates the results of the Wilcoxon signed-rank test for the SSQ scores and the driving errors. No statistically significant difference existed among simulator sickness scores during baseline testing or during posttesting. However, we did observe a statistically significant decrease in lane maintenance errors and total number of driving errors.
Discussion The purpose of this pilot study was to determine whether the OT-DI could impact the type and number of driving errors of OEF/OIF CVs with polytrauma, by comparing pre- and post-intervention results. In this study, unlike others, all of the participants were men and the majority were White. The primary deployment exposures reported were mortars/ explosive devices or sniper fire, while most of the secondary exposures were caused by motor vehicle accidents—both of which are common among OEF/ OIF CVs and consistent with prior research (Classen et al., 2011). Unlike previous work, we found no statistically significant differences in simulator sickness scores between baseline and follow-up testing (Classen & Owens, 2010). The small sample size in this study may have obscured a difference if one truly existed (type 2 error). Total driving errors and lane maintenance errors significantly decreased from baseline to posttest 1, indicating potential efficacy of the OT-DI. These findings are also consistent with a single-subject design study, where the total driving errors, as well as
lane maintenance errors, decreased post-intervention (Classen et al., 2014). All seven driving errors decreased after the intervention but did not reach statistical significance, potentially due to the small sample size and type 2 error. However, the cumulative effect of these decreases were perhaps evident in the statistically significant decrease of the total number of driving errors post-intervention, which were a two-fold decrease when compared with baseline. The ability to maintain one’s lane suggests CVs were able to attend to roadway information and adjust their vehicle control responses accordingly. Clearly, for the CVs to have decreased lane maintenance errors post intervention suggests they disregarded triggers (e.g., trash, dead animals, or loud noises), which prior to intervention, impaired their lane maintenance ability. As such, we surmised that the CVs could adapt their driving behaviors, specifically ignoring triggers, to maintain their lanes post intervention. Of course, further follow up is needed to determine whether such changes carry over to realworld driving. The main limitations of this pilot study pertain to sample size and the absence of a control group. However, ongoing research by our group, adequately powered to detect a statistically significant difference in driving errors, is currently enrolling participants in an experimental and control arm. The gender and racial bias evident in the study also restrict the generalizability of results to samples not fitting the profile of this study.
Conclusion Despite these limitations, the results of this pilot study suggest that an OT-DI is efficacious, at least in the short term, for OEF/OIF CVs with polytrauma. Specifically, the CVs in this study showed a two-fold improvement in maintaining their lanes or decreasing their total number of driving errors post intervention. More CVs are being tested to further validate the OT-DI. Thus, the OT-DI shows potential to improve driver fitness in the simulator and, as such, lays an important foundation for eventual decreases in risk of crash-related injuries or death. Acknowledgments
This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Congressionally Directed Medical Research Program under Award W81XWH-11-1-0454. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the Department of Defense. Infrastructure and support were provided by the University of Florida’s Institute for Mobility, Activity,
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and Participation. This work was also supported with resources and the use of facilities within the North Florida/ South Georgia Veterans Health System, the Malcom Randall VA Medical Center, and the VA’s Center of Innovation on Disability and Rehabilitation Research, Gainesville, Florida.
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