Driving Characteristics of Teens With Attention Deficit Hyperactivity and Autism Spectrum Disorder

Vehicle crashes are a leading cause of death among teens. Teens with attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), or both (ADHD–ASD) may have a greater crash risk. We examined the between-groups demographic, clinical, and predriving performance differences of 22 teens with ADHD– ASD (mean age 5 15.05, standard deviation [SD] 5 0.95) and 22 healthy control (HC) teens (mean age 5 14.32, SD 5 0.72). Compared with HC teens, the teens with ADHD–ASD performed more poorly on righteye visual acuity, selective attention, visual–motor integration, cognition, and motor performance and made more errors on the driving simulator pertaining to visual scanning, speed regulation, lane maintenance, adjustment to stimuli, and total number of driving errors. Teens with ADHD–ASD, compared with HC teens, may have more predriving deficits and as such require the skills of a certified driving rehabilitation specialist to assess readiness to drive

Indicators of Simulated Driving Skills in Adolescents with Autism Spectrum Disorder

Adolescents are at high risk for motor vehicle crashes (MVCs). Teens with autism spectrum disorder (ASD) may have an even greater risk for MVCs due to impaired visual, cognitive, and motor skills critical for driving. This prospective two group study demonstrated the demographic, clinical, and simulated driving skill differences of seven adolescents with ASD (mean age = 15.14, SD ±1.22) compared to 22 healthy controls (HC) (mean age = 14.32, SD ±.72) through a comprehensive driving evaluation (CDE) conducted by an occupational therapist certified driving rehabilitation specialist (OT-CDRS). Adolescents with ASD performed poorer on right eye acuity (Fischer’s (F) = 13.44, p = .003), cognition (Mann-Whitney Statistic (U) = 29.00, p = .01), visual motor integration (U = 27.50, p = .01), motor coordination (U = 5.00, p = .001), operational skills for managing simulator controls (U = 4.00, pU = 30.50, p = .02), speed regulation (U = 13.50, p = .001), lane maintenance (U = 34.00, p = .03), signaling (U = 38.50, p = .03), and adjustment to stimuli (U = 9.00, pU = 5.00, pConclusion). Compared to the HC, adolescents with ASD performed worse on visual, cognitive, motor, simulator operational, and fitness to drive skills, suggesting that an OT-CDRS may play an important role in assessing teens with ASD before they pursue traditional driver’s education

Fitness-to-Drive Screening Measure©: Patterns and Trends for Canadian Users

Background: The Fitness-to-Drive Screening Measure© (FTDS) is an online screening tool that enables proxy raters (caregivers, family members, and friends) to identify at-risk older adult drivers via 54 driving-related items. This study aimed to identify areas in need of improvement for the FTDS by identifying the patterns and trends of Canadian users and providing recommendations to increase the usage, reach, and potential impact of the FTDS as a health promotion tool. Methods: We used monthly Google Analytics reports to calculate descriptive statistics for web page and session specific variables. Variables were separated into Year 1 and Year 2 and were compared using the independent sample t-test. Results: Patterns were identified for session and web page specific variables; for example, users spent less than the recommended 20 min to complete the FTDS. There was only a significant decrease in the number of French speaking users (t (22) = .01, p \u3c .05) from Year 1 to Year 2. Conclusion: Canadians across the country are able to easily access and use the FTDS for screening older adult drivers in its current format. However, implementing suggested recommendations (e.g., short form FTDS) may increase the overall usage, utility, and/or reach of the FTDS, and, as such, may yield additional benefits to potential users

Indicators of Simulated Driving Skills in Adolescents with Attention Deficit Hyperactivity Disorder

Adolescents with attention deficit hyperactivity disorder (ADHD) have an increased risk for committing traffic violations, and they are four times more likely than neurotypical peers to be crash involved, making them a potentially high risk group for driving. We used a two-group design to measure differences in demographics, clinical off-road tests, and fitness to drive abilities in a driving simulator with nine adolescents with ADHD (mean age = 15.00, SD ± 1.00) compared to 22 healthy controls (HC) (mean age = 14.32, SD ±..716), as evaluated by an Occupational Therapist Certified Driving Rehabilitation Specialist (OT-CDRS). Despite few demographic differences, the adolescents with ADHD performed worse than the HC on tests of right visual acuity (F = 5.92, p = .036), right peripheral field (F = 6.85, p = .019), selective attention (U = 53.00, p = .046), and motor coordination (U = 53.00, p = .046). The ADHD group made more visual scanning (U = 52.50, p = .041), speed regulation (U = 28.00, p = .001), and total driving errors (U = 32.50, p = .003) on the simulator. Adolescents with ADHD performed worse on tests measuring visual, cognitive, motor, and pre-driving skills, and on a driving simulator. They may require the services of an OT-CDRS to determine their fitness to drive abilities prior to referring them for driver’s education

Utility of an Occupational Therapy Driving Intervention for a Combat Veteran

Many combat veterans are injured in motor vehicle crashes shortly after returning to civilian life, yet little evidence exists on effective driving interventions. In this single-subject design study, we compared clinical test results and driving errors in a returning combat veteran before and after an occupational therapy driving intervention. A certified driving rehabilitation specialist administered baseline clinical and simulated driving assessments; conducted three intervention sessions that discussed driving errors, retrained visual search skills, and invited commentary on driving; and administered a postintervention evaluation in conditions resembling those at baseline. Clinical test results were similar pre- and postintervention. Baseline versus postintervention driving errors were as follows: lane maintenance, 23 versus 7; vehicle positioning, 5 versus 1; signaling, 2 versus 0; speed regulation, 1 versus 1; visual scanning, 1 versus 0; and gap acceptance, 1 versus 0. Although the intervention appeared efficacious for this participant, threats to validity must be recognized and controlled for in a follow-up study

Clinical Utility of the DriveFocus™ Intervention on Young Drivers With and Without Experience

Introduction: The DriveFocus™ intervention addresses the ability of young drivers to detect and respond to critical roadway information. DriveFocus is an interactive video-based tablet application that teaches users how to detect and prioritize critical roadway items. However, young drivers with and without experience may respond differently to the intervention.Objectives: We compared the simulated driving performance of two 17 year-old licensed drivers with (novice) and without (learner) driving experience, after three (post-test 1) and six (post-test 2) intervention sessions.Methods: We collected clinical, driving performance (number of visual scanning, adjustment to stimuli, and total driving errors) and acceptability data.Results: The learner driver made more visual scanning, adjustment to stimuli and total errors when compared to the novice. Both participants exhibited a decrease in both types and number of driving errors from baseline to post-test 2 and the learner also made less driving errors at post-test 1. Both participants rated the perceived ease of use of the intervention favorably.Conclusions: This study lays the foundation to examine the impact of the DriveFocus™ intervention among novice and more experienced young drivers

The Effect of High and Low Antiepileptic Drug Dosage on Simulated Driving Performance in Person’s with Seizures: A Pilot Study

Background: Prior studies examining driving performance have not examined the effects of antiepileptic drugs (AED’s) or their dosages in persons with epilepsy. AED’s are the primary form of treatment to control seizures, but they are shown to affect cognition, attention, and vision, all which may impair driving. The purpose of this study was to describe the characteristics of high and low AED dosages on simulated driving performance in persons with seizures. Method: Patients (N = 11; mean age 42.1 ± 6.3; 55% female; 100% Caucasian) were recruited from the Epilepsy Monitoring Unit and had their driving assessed on a simulator. Results: No differences emerged in total or specific types of driving errors between high and low AED dosages. However, high AED drug dosage was significantly associated with errors of lane maintenance (r = .67, p \u3c .05) and gap acceptance (r = .66, p \u3c .05). The findings suggest that higher AED dosages may adversely affect driving performance, irrespective of having a diagnosis of epilepsy, conversion disorder, or other medical conditions. Conclusion: Future studies with larger samples are required to examine whether AED dosage or seizure focus alone can impair driving performance in persons with and without seizures

The Concurrent Criterion Validity of the 32-Item Fitness-to-Drive Screening Measure

Background: The Fitness-to-Drive Screening Measure© (FTDS) is a free online screening tool that identifies at-risk older drivers. This tool screens for at-risk drivers using proxy rater responses (family, friends, and caregivers) to 54 driving-related items. Consumer usage analysis of the FTDS determined that reducing the time commitment to complete the 54-item FTDS might increase usability and uptake of the tool. To address this need, we used classical test theory and exploratory factor analysis to construct a 32-item version of the FTDS. This study aims to establish the concurrent criterion validity of the 32-item FTDS.Method: Two hundred older driver on-road assessments and Two hundred caregiver FTDS responses were used to generate a receiver operating characteristic (ROC) curve, in which we plotted the rate of true positives against the rate of false positives, calculated the area under the curve (AUC), and used Youden's index to identify the optimal cut-point for the 32-item FTDS. In this study, the true positive rate was the 32-item FTDS' ability to predict a fail when the older driver actually failed the on-road assessment, and the false positive rate was the the 32-item FTDS' ability to predict a pass when the older driver actually passed the on-road assessment. We computed the sensitivity, specificity, positive predictive value, negative predictive value and total number of misclassifications for the optimal cut-point.Results: The ROC curve results indicated an acceptable AUC, with a magnitude of 0.75, p < 0.05. At the optimal cut-point of 4.87, the 32-item FTDS had a sensitivity of 0.74, specificity of 0.69, positive predictive value of 0.30, negative predictive value of 0.93 and 61 (of 200) misclassifications.Conclusion: Although the 32-item FTDS met the criterion (AUC 0.75, p < 0.05.) for good concurrent criterion validity in predicting older driver on-road outcomes, it also misclassified 30% of the drivers and as such may be overly sensitive

Stakeholder Recommendations to Refine the Fitness-to-Drive Screening Measure

In developing the web-based Fitness-to-Drive Screening Measure (FTDS) and keyform (results output) for use to identify at-risk older drivers, we examined the needs, perspectives, and suggestions of three stakeholders groups: occupational therapy practitioners, certified driver rehabilitation specialists (CDRSs), and family members/caregivers. We conducted three focus groups, which were moderated, recorded, transcribed, and analyzed using directed content analysis. Respondents in two focus groups also rated FTDS aspects (e.g., ease of use, format, and relevance), using a visual analog scale (VAS, 0-10 scale with 10 being excellent). All three stakeholder groups contributed to the development of the web-based FTDS. Results from occupational therapy practitioners addressed face validity, appearance, wording, and usability; CDRSs informed follow-up recommendations; and family members/caregivers provided keyform feedback. High VAS ratings (\u3e 7 on 1-10 scale) from the CDRSs (8.4, SD+0.8) and family members/caregivers (9.01, SD+1.02) indicated FTDS acceptability. Overall, our findings support the measure’s utility and acceptability among these users. As such, the FTDS may position family members/caregivers to identify at-risk older drivers, facilitate targeted discussions of driving difficulty among occupational therapists and their clients, and afford OT-CDRS an entry point for intervention and clinical decision making

Construction and Validation of the 21 Item Fitness-to-Drive Screening Measure Short-Form

Introduction: The Fitness-to-Drive Screening Measure is a free online screening tool that detects at-risk older drivers, however, it's 20 min administration time may render the 54-item tool less than optimal for clinical use. Thus, this study constructed and validated a 21-item FTDS Short-Form (FTDS-SF).Method: This mixed methods study used 200 proxy rater responses and older driver on-road assessments. We conducted a Rasch analysis to examine information at the level of the item and used content validity index scores to select items. Using a receiver operator characteristics curve we determined the concurrent validity of the FTDS-SF to on-road outcomes.Results: Twenty-one items were selected for the FTDS-SF. The area under the curve = 0.72, indicated the FTDS-SF predicted on-road outcomes with acceptable accuracy. Still, 68 drivers were misclassified.Conclusion: The FTDS-SF may reduce administration time, while still yielding acceptable psychometric properties. Yet, caution needs to be executed in clinical decision making as the measure is overly specific