The Neurocognitive Driving Test: Applying Technology to the Assessment of Driving Ability Following Brain Injury
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Rehabilitation Psychology Copyright 2003 by the Educational Publishing Foundation
2003, Vol. 48, No. 4, 275–280 0090-5550/03/$12.00 DOI: 10.1037/0090-5550.48.4.275
The Neurocognitive Driving Test: Applying Technology to the Assessment
of Driving Ability Following Brain Injury
Maria T. Schultheis Frank Hillary
Kessler Medical Rehabilitation Research and Education Kessler Medical Rehabilitation Research and Education
Corporation, University of Medicine and Dentistry of New Corporation and University of Medicine and Dentistry of New
Jersey—New Jersey Medical School, and Drexel University Jersey—New Jersey Medical School
Douglas L. Chute
Drexel University
Objective: To compare the Neurocognitive Driving Test (NDT) with an established driving assessment
method. Study Design: A prospective matched-control study. Participants: Fifteen adult volunteers with
acquired brain injury (ABI), aged 21–59 years, referred for a driving evaluation and 15 healthy control
(HC) participants. Methods: Individuals with ABI were administered the NDT and a traditional
hospital-based driving evaluation. An overall performance score was calculated and used to rank order
driving ability. HCs were administered the NDT to establish NDT performance range. Main Outcome
Measures: Overall performance on the NDT; overall performance on a comprehensive hospital-based
evaluation. Results: Comparison of the rank orders of driving ability for participants with ABI revealed
a significant Spearman correlation. NDT scores discriminated between individuals with ABI who passed
the driving evaluation and those who failed. Conclusions: Results help establish the potential utility of
the NDT for evaluating driving ability in persons with ABI.
The physical and cognitive impairments that follow acquired community. As such, evaluation of driving ability following ABI
brain injury (ABI) can make driving an automobile difficult, and requires careful analysis of the individual’s cognitive, physical,
this limitation often disrupts vocational, social, and domestic ac- and behavioral capacities.
tivities. Among individuals with brain injury, the cessation of Rehabilitation specialists are often asked to determine capacity
driving has been related to difficulties in employment (Devani to return to driving following ABI. Protocols for making this
Serio & Devens, 1994), higher incidence of depression (Legh- determination can include neuropsychological tests, performance
Smith, Wade, & Langton Hewer, 1986; Marottoli, De Loen, & on behind-the-wheel evaluations, and driving simulator perfor-
Glass, 1997), and poor social integration (Dawson & Chipman, mance (Croft & Jones, 1987; Fox, Bowden, & Smith, 1998;
1995). Similarly, research examining loss of social autonomy Galski, Bruno, & Ehle, 1992; Van Zomeren, Brouwer, & Mind-
following traumatic brain injury has identified driving as the third erhoud, 1987). Some recommendations regarding the use of these
most impaired social ability postinjury (Mazaux et al., 1997). The and other protocols have been presented (e.g., Association for
privilege of driving serves as a gateway to independent functioning Driver Rehabilitation Specialists). However, the variability in state
but also poses potential dangers to the driver and members of the legislation regulating driving assessment of medical populations
and in professionals charged with the responsibility of determining
driving capacity (e.g., psychologist, physical and occupational
Maria T. Schultheis, Neuropsychology and Neuroscience Laboratory, therapists, physicians) has hindered the identification of a nation-
Kessler Medical Rehabilitation Research and Education Corporation, West ally accepted standardized clinical driving assessment method.
Orange, New Jersey; Department of Physical Medicine and Rehabilitation, This is remarkable, considering that 78% of all survivors of ABI
University of Medicine and Dentistry of New Jersey––New Jersey Medical
seek to regain driving privileges after injury (Fisk, Schneider, &
School; and Department of Psychology, Drexel University. Frank Hillary,
Neuropsychology and Neuroscience Laboratory, Kessler Medical Rehabil-
Novack, 1998), and of these, the majority (84%) report returning
itation Research and Education Corporation, and Department of Physical to driving on a daily basis.
Medicine and Rehabilitation, University of Medicine and Dentistry of New A critical review of the driving assessment literature reveals
Jersey––New Jersey Medical School. Douglas L. Chute, Department of research that is varied in both its sources and claims. For example,
Psychology, Drexel University. the Pennsylvania state legislature has maintained that visual scan-
We thank Carmela Strano and Joseph Barisa for their assistance and ning and reaction time, combined with knowledge of traffic laws,
cooperation with this project. This study was presented in part at the 19th are the best predictors of driving ability. Other researchers, how-
annual meeting of the National Academy of Neuropsychology, San Anto-
ever, have indicated that these variables are not predictive of
nio, Texas, November 1999.
Correspondence concerning this article should be addressed to Maria T. accident risk (Hopewell & Van Zomeren, 1990). As a result, much
Schultheis, PhD, Kessler Medical Rehabilitation Research and Education controversy remains regarding the most appropriate method for
Corporation, 1199 Pleasant Valley Way, West Orange, New Jersey 07052. determining driving capacity following ABI.
E-mail: mschultheis@kmrrec.org Neuropsychological assessment has received considerable atten-
275276 SCHULTHEIS, HILLARY, AND CHUTE tion in driving evaluations (Brooke, Questad, Patterson, & Valois, congested traffic, or emergency situations). However, it has been 1992; Galski, Bruno, & Ehle, 1993; Gouvier et al., 1989; Jones, argued that complex situations may be most predictive of driving Gidden, & Croft, 1983; Korteling & Kaptein, 1996; Sivak, Olson, ability (Fox et al., 1998). Kewman, Won, & Henson, 1981). Investigators have reported that In summary, current methods for determining driving capacity performance on tests such as the Trail Making Test (Galski et al., include the assessment of individualized skills (e.g., reaction time, 1993; McKenna, 1998; Van Zomeren et al., 1987) and the Wech- visual perception, cognitive skills), simulated driving, and behind- sler Adult Intelligence Scale Digit Symbol (Lundqvist et al., 1997) the-wheel evaluations. Attempts to develop comprehensive driver and Block Design subtests (Galski et al., 1993) is predictive of evaluations have resulted in complex multilevel systems that are pass/fail performance on behind-the-wheel evaluations. Although not practical or cost effective for many clinicians or facilities. the results of these studies have been highly variable (Korteling & These methods also have significant shortcomings in their objec- Kaptein, 1996), they have led to the identification of specific tivity, ecological validity, theoretical basis, and practicality. First, cognitive skills deemed important for driving (e.g., visual percep- methods should require the consistent incorporation of objective tion, divided attention). However, it remains unclear how neuro- measures of driving behavior. Although clinical observation of psychological performance can meaningfully characterize func- driving performance remains an important tool, empirical mea- tional driving ability (Wilson, 1993). sures of individual performance should be an integral part of driver Researchers have also developed computerized tasks that at- analysis and could help further elucidate the cognitive demands of tempt to assess specific skills believed to be important in driving. driving, allow for increased consistency across evaluators, and For example, Gianutsos (1994) introduced the Elemental Driving help establish the reliability and validity of these methods. Second, Simulator, a PC-based driving simulator designed to evaluate the inclusion of ecologically valid stimuli, specifically more com- abilities such as simultaneous information processing, dealing with plex and challenging driving situations, may increase our ability to complexity, mental flexibility, impulse control, and measures of an predict real-life driving behavior. Although some methods, such as individual’s ability to estimate their own performance (metacog- the clinical behind-the-wheel evaluation, have strong face validity, nition). More recently, Ball and Owsley (1993) introduced the further research is needed examining the ability of these methods Useful Field of View, a computerized task designed to measure to predict impairment in everyday driving. Third, the incorporation visual attention and cognitive processing. Analysis of this program of existing theoretical perspectives could enhance the development has revealed positive correlations with risk of accident involve- of assessment paradigms. For example, Michon (1985) proposed a ment among elderly clinical populations (Ball, Owsley, Sloane, hierarchical model of car driving, which incorporated strategic, Roenker, & Bruni, 1993). Others have used simulator-based sys- tactical, and operational levels of tasks. To date, only portions of tems that emphasize evaluations of the temporal detection of this model have been used in driving assessment (Gianutsos, 1994; driving “vectors” (i.e., other cars, people, road signs; Schiff, Ar- Hopewell & Van Zomeren, 1990; Van Zomeren et al., 1987). Such none, & Cross, 1994). Although these systems may appear to have a theoretical foundation could help to provide stability and direc- greater face validity, their limitation, similar to that seen in tradi- tion in this rapidly developing area of research. Finally, the issue tional film/video-based driving simulators, is a lack of substantial of cost effectiveness must be considered in the development of any interaction between participants and the environment. That is, new assessment protocol. The need to minimize current costs of although driving scenes that elicit measurable responses from driving evaluations is particularly important, as driving assessment participants are presented, the actions or responses of the partici- is currently an out-of-pocket expense for most ABI survivors pant (e.g., turning) do not alter the course of the scenario, resulting (Rosenthal, Griffith, Kreutzer, & Pentland, 1999). in a lack of immediate feedback. Traditional driving simulators have been incorporated by some for driving assessment (Galski et al., 1992; Schiff et al., 1994); however, there is little evidence that Development of the Neurocognitive Driving Test (NDT) simulators do anything more than assess basic driver operational skills, such as steering, braking, and using appropriate turn signals The NDT is a computer-based driving assessment protocol (Lings & Jensen, 1991; Lovsund, Hedin, & Tornros, 1991). designed to address some of the current limitations in driving Although there are a myriad of driver assessment measures assessment. The NDT is a MacIntosh-based computer program available, evaluation of behind-the-wheel performance remains the that was developed through the use of PowerLaboratory software “gold standard” in driving assessment (Brooke et al., 1992; Fox et (Chute & Westall, 1996) and was based on Michon’s (1985) al., 1998). Typically, these evaluations involve having individuals theoretical model of driving behavior. Specifically, Michon pro- drive on preselected routes while being rated on specific driving posed that all tasks related to driving can be organized into three behaviors by a trained evaluator. Unfortunately, selection of the hierarchical levels: the strategic level, the tactical level, and the behind-the-wheel route can vary from evaluator to evaluator. For operational level. Briefly, the strategic level consists of driving example, some are limited to closed driving areas (e.g., parking behaviors, such as route determination, day and time of the jour- lots), whereas others may be more comprehensive and include a ney, costs, and other executive decisions. The tactical level in- variety of driving conditions (e.g., parking lot, highway, and cludes driving adjustment behaviors, such as adjusting speed to the residential areas). Furthermore, there is a risk of high subjectivity driving environment and switching on headlights when visibility is in rating driving behavior, as not all evaluators use a structured reduced. In addition, this level includes operator judgments, such checklist or other methods of quantifying driving behaviors ob- as when to pass another vehicle, how to negotiate a curve, and how served during the behind-the-wheel evaluation. Not surprisingly, to handle emergency situations. The lowest level, the operational to reduce risk of injury (for both patient and evaluator), an effort level, involves the common actions and decisions of driving that is made to avoid challenging driving situations (e.g., night driving, are made by the vehicle operator under constant time pressure,
NEUROCOGNITIVE DRIVING TEST 277
including decisions in steering, braking, perception of driving provided driving evaluations, driver training, and assessment for adaptive
situation, and the use of mirrors and controls. driver’s equipment for individuals with a wide variety of disabilities (e.g.,
The five sections of the NDT, designed to measure driving traumatic brain injury, stroke, multiple sclerosis). Following completion of
behaviors of the three levels proposed by Michon (1985), include the clinical evaluation, participants were offered the opportunity to partic-
ipate in the study. Participants were informed that participation was vol-
self-evaluation questions, predriving questions, simple and choice
untary, would not affect their current driving status, and did not include
reaction-time tasks, driving scenarios, and a visual task (see Table
monetary compensation. Prior to initiation of testing, all participants com-
1 for descriptions). For each task, a measure of error and a measure pleted a consent form approved by the Institutional Review Board.
of time to respond (i.e., latency) are automatically recorded by the Limited medical information was available for participants with ABI,
computer. Initial pilot testing was conducted to determine admin- given the high variability of time of and source of referral for driving
istration and scoring protocols. evaluation. For ABI participants, records provided to the driving program
A total performance score (NDT total score) was calculated were used to verify loss of consciousness and diagnosis of brain injury.
incorporating the individual latency and error variables of four out Eight participants were injured in motor vehicle accidents, 4 were involved
of the five NDT tasks. Responses to the self-evaluation questions in other types of accidents (e.g., struck on the head), and 3 underwent
were not included in the NDT total score, and an error variable for surgical interventions for neurological abnormalities (e.g., brain tumor,
aneurysm). Control participants were recruited from staff and students of a
the predriving questions was not calculated, given the broad spec-
local university. No statistically significant differences in age, t(29) ⫽
trum of responses generated. To ensure equal weighting of each
– 0.18, ns; gender, 2(1, N ⫽ 30) ⫽ 0.95, ns; education, t(29) ⫽ – 0.42, ns;
variable into the NDT total score, values were converted to a range or years of driving experience, t(29) ⫽ – 0.18, ns, were observed between
of 0 to 1. Conversion was completed by dividing individual values the two groups. A summary of the participant characteristics can be found
by highest possible errors for that variable, resulting in a score of in Table 2.
1 for worst performance and 0 for best performance. A total sum All participants spoke English as their primary language, and all but 2
of the variables was then calculated, yielding the NDT total score, expressed moderate familiarity with computers. All participants were also
which ranged from 1.2 (best score) to 6.0 (worst score), based on required to be independent of the need for assistive driving devices at the
findings from our pilot sample. time of the evaluation. Those with a history of psychiatric illness, signif-
icant substance abuse, neurological degeneration or disease, or previous
neurologic injury were excluded from the study.
Purpose of the Study
The purposes of this study were (a) to compare the NDT to a Measures
comprehensive hospital-based driving evaluation in the assessment Two measures were used to assess driving ability: (a) overall perfor-
of driving performance in individuals with ABI and (b) to contrast mance on the NDT (see description above), as determined by the NDT total
the NDT performance of adults with ABI who passed a driver score, and (b) overall performance on a comprehensive hospital-based
evaluation to that of adults with ABI who failed a driver evaluation evaluation that included a visual acuity and peripheral vision task—the
and of control participants. Motor-Free Visual Perceptual Test—and a 30-min behind-the-wheel eval-
uation. The evaluation was completed by the same occupational therapist,
who specialized in driving assessment and was certified by the Association
Method
for Driver’s Educators for the Disabled.
Participants
Procedure
The participants were 15 adults with ABI and 15 age-, gender-, and
driving experience-matched healthy control (HC) participants. All partic- All participants with ABI first completed the hospital-based driving
ipants with ABI were recruited from incoming referrals for driving eval- evaluation. For each participant, at the end of the hospital-based driving
uations at the MossRehab Driving School, which, for nearly 25 years, has evaluation, the instructor/evaluator completed a driver evaluation form.
Table 1
Description of the Various Sections of the Neurocognitive Driving Test
Section Description
Self-evaluation questions Five self-report questions on which participants rate their driving ability on a 5-point scale.
Predriving questions Series of 12 open-ended and multiple-choice questions assessing an individual’s ability to identify
information needed prior to engaging in driving (e.g., check gas in car, have proper
documentation).
Simple and choice reaction-time tasks Total of 24 counterbalanced trials, 12 simple and 12 choice measures. Participants respond via
foot pedal to color stimuli presented through a modified photograph of a traffic light. Latency
and total errors are recorded.
Driving scenarios Simulated driving scenarios engineered to measure driving ability by requiring participants to
drive through three scenarios using a steering wheel and foot pedals. Driving situations include
emergency, verbal directions, and written directions. Initiation time (measure of time required
for driver to reengage in the act of driving after stop stimulus has been presented) and total
errors are recorded.
Visual task Assesses gross field cuts and visual inattention. Incorporates 40 trials, with measures for both
peripheral and focal visual field errors. Latency and errors are recorded.278 SCHULTHEIS, HILLARY, AND CHUTE
Table 2
Demographic Description of the Study Participants
Demographic variable ABI HC
n 15 15
Age (years)
M 38.6 33.2
SD 10.8 6.8
Range 21–59 23–45
Education (years)
M 14.3 15.0
SD 1.9 2.4
Range 12–18 12–18
Time postinjury (months)
M 23.8
SD 22.8
Range 4–96
Gender
Male (%) 10 (75) 9 (60)
Female (%) 5 (25) 6 (40)
Driving experience (years)
M 21.0 16.2
SD 9.7 6.6
Range 3–34 5–28
Note. ABI ⫽ acquired brain injury group; HC ⫽ healthy control group.
After all hospital-based driving evaluations were completed, the instructor/ Figure 1. Person sitting at the Neurocognitive Driving Test.
evaluator ranked the performance of participants with ABI from best to
worst (1–15). In addition, consistent with standard procedures, a pass or
fail grade was assigned to participants with ABI at the completion of the
hospital-based evaluation. To minimize bias, the experimenter was blind to exceeded the two standard deviation cutoff score. In addition, it is
the results of the hospital-based driving evaluation. worth noting for those passing the hospital evaluation that the
Following completion of the hospital-based driving evaluation, partici- NDT cutoff score accurately categorized patients 72% of the time;
pants with ABI were scheduled for a one-time session for administration of only 3 individuals passing the hospital-based driving evaluation
the NDT. All testing sessions included completion of a brief history scored above the cutoff of 4.32 (see Figure 3). As noted, the NDT
questionnaire. For administration of the NDT, participants were seated at a correctly matched the top 2 participants ranked by the hospital
MacIntosh computer with attached steering wheel and foot pedals and a evaluator and placed the 4 individuals who failed the hospital-
19-in. (48.26-cm) monitor, which was adjusted to eye level (see Figure 1). based driving evaluation at the lower end of the rank order.
At completion of the NDT, a rank order of driving ability from best to
Overall, the NDT cutoff score successfully categorized 80% of all
worst (1–15) was generated for all participants with ABI on the basis of the
NDT total score performance.
participants with ABI.
A Spearman rank-order correlation was calculated to compare the rank
order generated by the NDT total score and the rank order provided by
hospital-based driving evaluation. HC participants were seen for only one Table 3
testing session, which included completion of a brief history questionnaire
Comparison of the Ranking of Driving Ability Between
and the same administration of the NDT.
Neurocognitive Driving Test (NDT) and
the Hospital-Based Evaluation
Results
Participant no. NDT ranking Hospital-based ranking
Comparisons of the rank order of driving ability as determined 111 1 1
by the NDT total score and the hospital-based driving evaluation 116 2 2
revealed a significant relationship between the two measures 107 3 10
(Spearman rank-order r ⫽ .743, p ⬍ .01; see Table 3). 102 4 6
115 5 9
To examine the NDT’s ability to distinguish participants with 106 6 5
ABI who passed the hospital-based driving evaluation (ABI Pass; 117 7 3
n ⫽ 11) from those who failed (ABI Fail; n ⫽ 4), we calculated a 108 8 7
cutoff score equal to two standard deviations from the control 113 9 4
110 10 8
group mean (cutoff ⫽ 4.32). The mean NDT total score for the 109 11 15
ABI Pass group was 3.78 (SD ⫽ 0.96), the ABI Fail group 112 12 13
obtained a mean NDT total score of 5.31 (SD ⫽ 0.22), and the HC 114 13 12
group obtained a mean NDT total score of 3.24 (SD ⫽ 0.54; see 104 14 11
Figure 2). All patients failing the hospital-based driving evaluation 105 15 14NEUROCOGNITIVE DRIVING TEST 279
Discussion
The current study was designed to compare a newly developed
computer-based driving assessment tool, the NDT, with the current
“gold standard” of driver assessment, a comprehensive hospital-
based driving evaluation. The findings revealed a significant rela-
tionship between the two measures, suggesting that both programs
are targeting similar skills, which at present serve as the criteria for
an individual’s return to driving after an ABI. Furthermore, the
findings support the NDT’s ability to discriminate between those
individuals who passed the hospital-based driving evaluation and
those who failed and consequently were not eligible for relicens-
ing. Specifically, a derived NDT cutoff score (based on HC per-
formance) demonstrated sensitivity for detecting driving impair-
ment and accurately categorized 80% of the entire brain-injured
Figure 3. Comparison of pass/fail driving performance of the two assess-
sample.
ment measures. NDT ⫽ Neurocognitive Driving Test.
Although these initial findings are encouraging, more research is
needed to determine the utility of this new measure. In particular,
future investigations should include larger sample sizes, with
greater diversity in the nature of neurological impairment (e.g., ment tool (i.e., screening measure) and to enhance driving assess-
multiple sclerosis, degenerative diseases) and more clearly defined ment and inform treatment planning.
characteristics of the sample. Comparison of NDT performance to
other tasks thought to measure driving ability (e.g., neuropsycho-
logical measures) would also help further validate its use. Al- References
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