Simulated Driving Skills Evaluation of Teenagers With Attention Deficit Hyperactivity Disorder Before Driving Lessons

Abstract

OBJECTIVE. We evaluated the driving skills of teenagers with attention deficit hyperactivity disorder (ADHD) during simulated driving before starting driving lessons and observed whether methylphenidate (MPH) affected their performance.

METHOD. Sixty teenagers ages 15-18 yr were included; 29 teenagers with ADHD were tested with and without MPH, and 31 teenagers (control group) were tested once. All participants were tested on the STISIM Drive™ simulator.

RESULTS. The number of center-line crossings was higher in the group without MPH treatment than in the control group and the MPH-treated group. The group without MPH treatment had more road-edge excursions compared with the control group and drove faster than the MPH-treated group.

CONCLUSION. Adolescents with ADHD without MPH treatment demonstrated impaired performance more often while driving the simulator, resembling characteristics found during on-road driving among teenagers with ADHD. Trainer awareness is a primary intervention before taking driving lessons to help teenagers achieve safe driving performance.

Motor vehicle collisions (MVCs) are the leading cause of death and disability among adolescents (Koisaari et al., 2015; National Highway Traffic Safety Administration, 2003). Novice drivers make more judgment-related driving errors than do experienced drivers (McKnight & McKnight, 2003). Risky driving behaviors—including speeding, following too closely, driving under the influence of alcohol, using a cell phone, and not wearing a seatbelt while driving—are found to predict MVCs and driving citations (Garner, Fine, Franklin, Sattin, & Stavrinos, 2011; Murphy & Barkley, 1996; Narad et al., 2015). Crash risk among young drivers is particularly high under complex driving circumstances, such as late night driving and driving with adolescent passengers (Ouimet et al., 2015; Stafford Sewall, Whetsel Borzendowski, & Tyrrell, 2014; Williams, 2003). These behaviors in young drivers, coupled with a propensity for risk taking, contribute to an increased rate of unintentional injury beyond the risk due to inexperience alone.

Adolescents with attention deficit hyperactivity disorder (ADHD) are at increased risk for driving-related accidents. In a new meta-analysis, Vaa (2014) estimated the overall relative risk for accidents for the ADHD population at all ages (in comparison with healthy teen control participants) to be 1.36, 95% confidence interval (CI) [1.18, 1.57], without control for exposure; 1.29, 95% CI [1.12, 1.49], when correcting for publication bias; and 1.23, 95% CI [1.04, 1.46], when controlling for exposure. In earlier studies, researchers estimated that people with ADHD would be 2–4 times more likely to experience a MVC (Barkley, Guevremont, Anastopoulos, DuPaul, & Shelton, 1993; Barkley, Murphy, & Kwasnik, 1996), 4 times as likely to be at fault in the collision (McKnight & McKnight, 2003), and more than 3 times as likely to incur associated injuries because of the collision (Cox, Merkel, Kovatchev, & Seward, 2000).

Research has suggested that people with ADHD should have the therapeutic benefit of a stimulant medication when operating a vehicle (Cox et al., 2000). Vaa (2014) reviewed studies that evaluated the effect of medication both on actual driving and on simulated driving. Methylphenidate (MPH) improved safety of driving while reducing ADHD symptoms. The effect of medication for ADHD was also studied with a placebo-controlled cross-over method, and it succeeded in showing significant improvements in simulated driving (Kay, Michaels, & Pakull, 2009). Nevertheless, the effect of MPH medication on people with ADHD before starting driving lessons has not been studied. Determining what effect, if any, MPH has could allow people with ADHD to receive better guidance regarding driving before starting driving lessons.

A better ability to characterize driving of teenagers with ADHD before starting driving training may help quantify risk factors related to driving and lead to the development of screening tools and preemptive strategies (such as special techniques for teaching driving and special training programs for novice drivers with ADHD) for this at-risk group of drivers. Such instruments have the potential to reduce morbidity and mortality and have important public health implications for the driving population at large. Our aim in this study was to evaluate the driving skills of teenagers with ADHD during simulated driving before starting driving lessons and to observe whether MPH medication affected their driving performance on the driving simulator.

Method

We received the approval of the institutional review board for this study.

Participants

Seventy-six teenagers were approached (45 with ADHD; 31 healthy). Of these teenagers, 9 declined to participate, and 4 did not meet inclusion criteria; all 13 had ADHD. Thirty-two teenagers with ADHD and 31 healthy control participants were included in the study. Participants were 45 male and 18 female teenagers ages 15–18 yr (mean ± standard deviation = 16.28 ± 0.78; Table 1). Three teenagers with ADHD did not complete testing and were lost to follow-up. (The flow diagram is provided in Supplemental Figure 1, available online at http://otjournal.net; navigate to this article, and click on “Supplemental.”) A total of 29 teenagers with ADHD were tested with and without MPH. The control group was tested once.

Table 1.

Gender Distribution of Study Group

Gender	ADHD Group		Control Group
Gender	n	%	n	%
Male	20	69	22	71
Female	9	31	9	29

Note. ADHD = attention deficit hyperactivity disorder.

Thirty-two teenagers (the study group) had been diagnosed with ADHD by a pediatric neurologist or by a psychiatrist—on the basis of Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000) criteria—and had been treated with long-acting MPH (Ritalin LA^® or Concerta^®) for a minimum of 3 yr. All participants were adequately dosed and well controlled (as per parental report) for several years. They had a positive history of stimulant responsiveness as disclosed by adolescent and parent reports. The control group included 31 healthy teenagers who were matched on age and gender.

Inclusion criteria for both groups required studying in a regular education school; no prior actual driving experience, theoretical training, or driver education; and intention to take a driver education course to obtain a driving license. All adolescents in the control group were evaluated by parents with the Conners’ Parent Rating Scale (CPRS; Conners, 1997) to detect possible ADHD symptoms. Adolescents with ADHD with a history of tics or any adverse reactions to MPH, a history of substance abuse disclosed by patient or parent, or a coexisting medical condition or medication usage known to interfere with the safe administration of stimulant medications were excluded.

Instruments

We tested participants using a desktop 350-MHz Pentium IV processor with 256 MB of RAM and a 128-MB ATI (Intel Corp., Santa Clara, CA). A Radeon graphics card (Advanced Micro Devices, Inc., Sunnyvale, CA) set up to exceed the minimum specifications to operate STISIM Drive™ (Systems Technology Inc., Hawthorne, CA; http://www.stisimdrive.com) was used. STISIM Drive is a PC-based computer simulation program. The scenarios were presented on one screen (50 × 30 cm). STISIM Drive is commonly used in driving evaluation and treatment. The tool was found to have high ecological validity (Lee, Lee, Cameron, & Li-Tsang, 2003). The STIMSIM Drive car control uses a Microsoft SideWinder steering wheel (Microsoft Corp., Redmond, WA) with force feedback as well as accelerator and brake pedals.

Two scenarios were installed in the simulator; one was used for training, and the second was used to evaluate the performance of simulated driving. The former mainly included practicing use of the steering wheel and pedals and getting the experience of driving the simulator in simple urban and interurban environments. The other scenario was defined by a specific route that included realistic images of the road in country, intercity, and city settings on a monitor. Participants drove first through a four-lane (two on each side) highway without and with other cars. The landscape included mainly trees, electricity poles, and road signs. After merging to an urban zone, they drove through a construction zone with one lane and warning cones. The last urban segment of driving included right and left turns, intersections, cars, pedestrians, dogs, and so forth.

The driver was asked to use the system’s steering wheel and pedals to drive as though on an actual road and to observe all traffic laws. As the scenario progressed, the driver had to cope with a variety of simultaneous tasks that simulated actual driving, such as yielding, stopping suddenly, adhering to driving laws, driving around “road work” obstacles, avoiding hitting pedestrians running across the road, or avoiding colliding into cars moving out from parking spots without signaling. The driver was provided with visual and auditory hints (navigating instructions, collision sounds, police sirens, etc.). To identify deficient driving skills, we used the simulator to produce an objective scoring of the simulated driving performance, including number of accidents (off-road accidents), number of collisions (accidents involving crashes with still objects, such as cones and cars), and number of occasions hitting pedestrians. In addition, the simulator recorded the time required to complete the scenario and infractions, including speeding, crossing the center line, and driving off the road.

Parents of the control group participants completed the CPRS (Conners, 1997) to locate any undiagnosed participants with ADHD. The CPRS is used as a screening tool to distinguish between populations with and without ADHD, and it is considered to be a reliable tool (Cronbach’s α ranges between .60 and .90) and a valid one (test–retest validity ranges between .75 and .90). In this study, we used the short version of the CPRS, with the attention and hyperactivity index ranging from 0 to 30 (higher score indicated more or stronger attention and hyperactive symptoms). Control participants scoring 20 or higher on the CPRS were excluded from the study.

Study Procedure

The study was approved by the Health Helsinki ethical review committee, and informed consent was obtained from parents and adolescents. To recruit participants, we sent letters to parents and teenagers in the relevant age group (ages 15–18 yr) who were treated with MPH in three clinics in the central distict of Israel. The volunteers were asked to share information about the study through social media to recruits peers who were not diagnosed with ADHD.

The participants were tested on STISIM Drive, which is an interactive, fixed-platform, virtual-reality simulator. The use of STISIM Drive and the selection of the specific protocol and accompanying scenarios was based on a previous study in which Kizony et al. (2005) investigated baseline performance in a healthy population who possessed a driving license and drove daily. The training segment provided participants with approximately 10 min of driving experience. The actual simulated driving test lasted 10–12 min depending on the length of time it took the participant to complete the test.

The teenagers with ADHD were tested twice, with and without MPH. The MPH medication was administered 90 min before the driving simulator test began. The teenagers with ADHD underwent a minimum 5-day washout period before testing without MPH (according to manufacturer recommendations on the basis of medication half-lives). Eleven adolescents with ADHD started the study while on MPH, and 18 started the trial without MPH. The second laboratory driving simulator test was done 3–4 wk after the first test. MPH medication was administered 90 min before laboratory testing began. The control group was tested once.

Statistical Analysis

Descriptive statistics were used to characterize the sample, the simulator metrics, and the independent variables and to determine normal distribution. To test the differences in simulator metrics between teenagers with ADHD and control participants, we calculated t tests and Mann–Whitney tests for independent samples in accordance with the distribution of the variables (the calculation was done twice, once with medication and once without medication). In addition, to test the differences in simulator metrics between teenagers with ADHD with and without medication, we used a paired t test and Wilcoxon test for dependent samples according to the distribution of the variables.

To control for the learning effect of teenagers with ADHD who were tested twice, we calculated a t test and a Mann–Whitney test for independent samples in accordance with the distribution of the variables (the calculation was done twice, once to compare 18 teenagers with ADHD who were tested without medication for the first time with 11 teenagers with ADHD who were tested without medication for the second time, and once comparing 11 teenagers with ADHD who were tested with medication for the first time with 18 teenagers with ADHD who were tested with medication for the second time). Because no significant differences were found (data are not shown), the trial is related to only two conditions: teenagers with ADHD who were tested with medication and without medication. IBM SPSS Statistics (Version 19; IBM Corp., Armonk, NY) was used to analyze the data. The level significance was set at .05 for all statistical tests.

Results

Tables 2, 3, and 4 present the results of the differences in simulator metrics among teenagers with ADHD with and without MPH treatment and control participants as well as the differences in simulator metrics between teenagers with ADHD with and without medication. Overall driving performance was better with active MPH treatment. The instances of speeding were significantly higher (p = .04) in the ADHD group without MPH treatment compared with the control group (Table 2) and to the ADHD group with MPH treatment (Table 4). No statistical differences were observed between the ADHD group with MPH treatment and the control group (Table 3).

Table 2.

Comparison of ADHD Group Without MPH Treatment and Control Group

Simulator Indices	ADHD Group Without MPH Treatment, M ± SD	Control Group, M ± SD	t a	p
Center-line crossings	8.38 ± 5.04	4.60 ± 3.55	2.97	.00
Road-edge excursions	5.55 ± 4.24	3.50 ± 3.01	2.18	.03
Total run length (s)	625.73 ± 98.30	667.71 ± 102.95	1.71	.92
			Mann–Whitneyb
Collisions	0.81 ± 1.75	1.73 ± 7.06	0.47	.64
Objects hit	10.00 ± 8.76	9.47 ± 7.62	−0.20	.84
Pedestrians hit	1.81 ± 1.23	2.30 ± 1.42	−1.56	.19
Speeding incidents	4.31 ± 3.61	2.73 ± 2.98	−2.07	.03

Note. ADHD = attention deficit hyperactivity disorder; M = mean; MPH = methylphenidate; SD = standard deviation.

A t test was used for variables with normal distribution.

A Mann–Whitney test was used for variables with nonnormal distribution.

Table 3.

Comparison of ADHD Group With MPH Treatment and Control Group

Simulator Indices	ADHD Group With MPH Treatment, M ± SD	Control Group, M ± SD	t a	p
Objects hit	9.14 ± 6.81	9.47 ± 7.62	0.18	.86
Pedestrians hit	1.79 ± 1.35	2.30 ± 1.42	1.41	.16
Road-edge excursions	4.90 ± 4.38	3.50 ± 3.01	−1.43	.16
Total run length (s)	697.96 ± 181.40	667.71 ± 102.95	0.78	.44
			Mann–Whitneyb
Collisions	0.55 ± 1.50	1.73 ± 7.06	1.17	.24
Speeding incidents	2.86 ± 2.98	2.73 ± 2.98	−0.09	.93
Center-line crossings	5.83 ± 5.35	4.60 ± 3.55	−0.56	.57

Note. ADHD = attention deficit hyperactivity disorder; M = mean; MPH = methylphenidate; SD = standard deviation

A t test was used for variables with normal distribution.

A Mann–Whitney test was used for variables with nonnormal distribution.

Table 4.

Comparison of ADHD Groups With and Without MPH Treatment

Simulator Indices	ADHD Group With MPH Treatment, M ± SD	ADHD Group Without MPH Treatment, M ± SD	t a	p
Objects hit	9.14 ± 6.81	10.00 ± 8.76	0.66	.51
Pedestrians hit	1.79 ± 1.35	1.83 ± 1.23	0.10	.92
Speeding incidents	2.86 ± 2.98	4.31 ± 3.61	2.14	.41
Center-line crossings	5.83 ± 5.35	8.38 ± 5.04	3.15	.004
Road-edge excursions	4.90 ± 4.38	5.55 ± 4.24	1.01	.32
Total run length, s	697.96 ± 181.40	625.73 ± 98.30	2.65	.01
			Wilcoxonb
Collisions	0.55 ± 1.50	0.81 ± 1.75	−1.19	.23

Note. ADHD = attention deficit hyperactivity disorder; M = mean; MPH = methylphenidate; SD = standard deviation.

A paired t test was used for variables with normal distribution.

A Wilcoxon test was used for variables with nonnormal distribution.

The number of center-line crossings (CLCs) was significantly higher in the ADHD group without MPH treatment (p = .004) compared with the control group (Table 2) and with the ADHD group with MPH treatment (p = .004; Table 4). More CLCs were observed in the ADHD group with MPH treatment compared with the control group (p = .577) but without statistical significance (Table 3).

The number of road-edge excursions (REEs) was higher in the ADHD group without MPH treatment (p = .03) compared with the control group. More REEs were also observed in the ADHD group without MPH treatment compared with the ADHD group with MPH treatment (p = .322), without statistical significance (Table 4). The ADHD group with MPH treatment had a higher rate of REEs than the control group but without statistical significance (p = .158; Table 3).

The time of total run length varied between test groups (Table 4). The ADHD group without MPH treatment completed the simulation in a shorter period than the ADHD group with MPH treatment (p = .013). The ADHD group without MPH treatment demonstrated a trend toward completing the course faster (p = .092) compared with the control group. The longest time to complete the test was observed in the ADHD group with MPH treatment. There were no statistically significant differences among the groups in the other driving simulator parameters that were tested.

Discussion

This study demonstrated that before starting driving training, teenagers with ADHD tested with a driving simulator exhibited impaired driving performance while driving the simulator. Impairments included instances of speeding, CLCs, and REEs as well as completing the test too quickly (overall excess speed). The incidences of speeding and CLCs were significantly higher in the ADHD group without MPH treatment compared with the control group and to the ADHD group with MPH treatment. The number of REEs was also higher in the ADHD group without MPH treatment compared with the control group. The ADHD group with MPH treatment took a longer time to complete the total run length compared with the ADHD group without MPH treatment and the control group.

The increased incidence of CLCs and REEs may be reflective of inattention and distracted driving activity related to ADHD. The main types of distractions present in driving include visual (taking one’s eyes off the road), manual (taking one’s hands off the wheel), and cognitive (taking one’s mind away from the driving task; Ishigami & Klein, 2009). The increased number of speeding episodes and the shorter driving time may reflect the impulsive part of ADHD. Given that CLCs, REEs, and speeding were identified as factors for MVCs in actual driving (Garner et al., 2011; McDonald, Curry, Kandadai, Sommers, & Winston, 2014; Shope & Bingham, 2008) and given that driving a simulator is considered to have an ecological validity (Lee et al., 2003), this behavior should be considered as a risk factor for safe driving. Nonetheless, at the same time there were no significant differences between the ADHD group without MPH treatment and the control group in number of accidents and collisions. Both groups demonstrated similar patterns of performance. However, these results must be interpreted with caution because research has shown that drivers must be followed for long periods of time to experience accidents (Jonasson & Rootzén, 2014). As such, it is reasonable to assume that participants using the simulator would also need to drive for a long period of time to experience an accident.

As observed in our study, teenagers with ADHD who were treated with MPH had better driving ability and fewer speeding instances, CLCs, and REEs. They also drove more slowly than the ADHD group without MPH treatment and the control group. Even though all participants were inexperienced drivers, the medication appeared to have affected their simulated driving skills.

Perhaps the single most effective way for people with ADHD to improve their driving performance is to be on medication while driving (Cox et al., 2006, 2012; Cox, Humphrey, Merkel, Penberthy, & Kovatchev, 2004). ADHD medication has been shown to increase vigilance, reduce impulsivity, and improve behavioral control, all of which contribute greatly to driving ability.

The fact that we aimed to evaluate adolescents with ADHD before they acquired a license dictated the usage of a simulator for driving assessment. Simulators do not provide a direct measure of real-life driving performance. They are used in an artificial laboratory environment, as opposed to actual road conditions. The driver’s view is limited to what is presented on the computer monitor. The gears, pedals, and steering wheel, although very lifelike, still do not re-create the experience of actually driving a car. Additionally, it is likely that the motivation level of the driver is lower in a simulation than in a real-life driving experience, primarily because there is no actual personal safety or health risk involved in performing the simulated task. On the contrary, driving in the real world involves an inherent element of risk and danger that is experienced to some degree by all drivers, resulting in increased vigilance and caution while driving. Even so, the simulated driving procedure is considered an accepted method for examining driving behavior in people with ADHD (Classen & Monahan, 2013; Monahan, Classen, & Helsel, 2013). Moreover, evidence about the associations between simulated driving and actual on-road driving is growing (Classen & Brooks, 2014). This finding was also demonstrated in this present study in which the significant variables that characterize teenagers with ADHD not using MPH were also found in other studies in which researchers used naturalistic driving and on-road evaluation, and in which the same risk factors were found (speeding and lane departure CLCs and REEs; Merkel et al., 2016; Sobanski et al., 2013). In addition, the effects of using medication (Sobanski et al., 2013) were similar between the simulated and on-road driving groups.

It has been suggested that people with ADHD might benefit from a graduated licensing procedure (Barkley, 2004) or may even require a certified driving rehabilitation specialist to assess driving readiness (Monahan et al., 2013). This could involve longer and more intensive training periods, stressing the importance of driving safety and the risks and dangers involved in careless, inattentive driving habits.

Clinicians should educate teenagers and caregivers about the increased risk for adverse outcomes among untreated adolescents with ADHD and the role of medication in potentially improving driving performance. Additionally, driving education instructors should be made aware of the potential driving impairments of teenagers with ADHD, and accommodating training programs and licensing procedures should be provided for these teenagers. Implementation of special teaching strategies at the early stage of driving instruction might prepare the teenager with ADHD for improved future driving performance and reduced risk for crashes and injuries. It is recommended that further research on this matter be conducted in which adolescents with ADHD receive specialized driving education and then receive follow-up testing to determine whether such training has affected their performance on simulated and real driving.

Certain limitations deserve to be mentioned. The simulated driving scenario is generally free of the main distractions typically encountered in real-life situations, such as noisy passengers, cell-phone conversations, or music, which make driving more dangerous. These additional elements of real-life driving situations require the ability to divide attention and ignore distraction, likely resulting in a much more challenging situation for drivers, especially for those with attention deficits. An additional limitation lies in the length of the scenario. A longer scenario might induce a better opportunity to observe collisions and accidents. Finally, simulator adaptation syndrome was not monitored during the course of this study, and participants did not spontaneously endorse experiencing it.

Conclusion

This study demonstrated that teenagers with untreated ADHD before starting driving training had impaired driving performance while driving the simulator, indicated by more CLCs and REEs as well as speeding and completing the total run length faster, as tested with a driving simulator. When treated with MPH medication before the driving test, their driving performance was improved. These results are similar to real-life driving of teenagers with ADHD. This similarity emphasizes the need to consider a primary intervention program before taking driving lessons to help teenagers with ADHD acquire correct driving habits, avoid typical mistakes, and achieve safer driving performance. Further studies are warranted to identify other possible risk factors.

Implications for Occupational Therapy Practice

The findings of the study have the following implications for occupational therapy practice:

Treating teenagers with ADHD with MPH medication improved simulated driving performance.

Teen drivers with ADHD may benefit from sessions on a simulator before beginning driving lessons.

Supplemental Material

Supplementary material for Simulated Driving Skills Evaluation of Teenagers With Attention Deficit Hyperactivity Disorder Before Driving Lessons

Supplementary material, sj-pdf-1-aot-10.5014_ajot.2017.020164.pdf for Simulated Driving Skills Evaluation of Teenagers With Attention Deficit Hyperactivity Disorder Before Driving Lessons by Navah Zelda Ratzon, Efrat Kadury Lunievsky, Arie Ashkenasi, Joseph Laks and Herman Avner Cohen in The American Journal of Occupational Therapy

Footnotes

Acknowledgment

This trial has been registered at . The clinical trial identification number is NCT01179386.

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