Predicting changes in driving performance in individuals who use cannabis following acute use based on self-reported readiness to drive.

OBJECTIVE: It is unclear to what extent individuals who use cannabis can accurately assess their ability to drive safely following cannabis use, and lack of understanding as to what factors influence changes in driving performance following cannabis use. This research explores whether self-reported readiness to drive (RTD) and previous experience (PE) using cannabis within 2 h of driving can predict observed changes in driving performance following acute cannabis use. METHODS: Individuals who used cannabis at least monthly completed a baseline simulated drive, were dosed with cannabis of approximately 6.18% THC, then drove at approximately 30-minutes, 90-minutes, and 180-minutes post-dose. Before each drive, participants were asked if they felt safe to drive (on real roadways, not the simulator), a yes/no question (RTD-yes/RTD-no). Venous blood was drawn at baseline and approximately 15-minutes post-dose. Cannabis use history was obtained and included whether the participant had ever driven within 2 h of use (PE-yes/PE-no) and how many days out of the past 30 they had done so (NPD). Drives were segmented into events delineated by changes in the driving environment. Within events, standard deviation of lateral position (SDLP), average speed, and number of lane departures were calculated, and differences from baseline were modeled using mixed-effects regression. Models considered covariates of time, event, and speed, and used RTD-yes/RTD-no, PE-yes/PE-no, NPD, and their interactions as potential predictors. Conditional R2 was used to compare the predictive ability of RTD versus change in Delta-9-THC. DATA SOURCES: Data were collected from 30 individuals who use cannabis and included cannabis use patterns, driving behaviors after use, self-reported RTD, measures of driving performance, and cannabinoid blood levels. RESULTS: RTD-no predicted a 2.60 cm increase in SDLP relative to baseline (95 % CI: 0.43, 4.73, p = 0.018). Average speeds generally decreased relative to baseline, except for RTD-yes with PE-yes (+1.08 mph, 95 % CI: 0.05, 2.11). NPD predicted increased speed among RTD-yes (+0.11 mph per additional day, 95 % CI: 0.01, 0.22) and decreased speed among RTD-no (-0.06 mph per additional day, 95 % CI: -0.18, 0.32). The difference in these effects was statistically significant (p = 0.038). RTD, PE, and NPD were not significant predictors of changes in number of lane departures. For all outcomes, models using RTD achieved higher conditional R2 than models that replaced this variable with change in Delta-9-THC. Differences were most prominent when modeling change in speed with NPD (R2=0.544 with RTD vs. R2=0.481 with change in Delta-9-THC). SIGNIFICANCE OF RESULTS: These results suggest individuals who use cannabis can somewhat self-identify when they are likely to exhibit greater degraded lateral control, although RTD does not fully explain observed degradation in performance. Past research suggests drivers may reduce speed to compensate for recognized impairment following acute cannabis use. Our findings suggest this to be true for those who reported never having previously driven within 2 h of cannabis use or reported RTD-no, but not for those who had previously driven within 2 h of cannabis use and reported RTD-yes. This indicates compensatory behavior is not uniform and helps focus public health outreach efforts.

A study of self-reported personal cannabis use and state legal status and associations with engagement in and perceptions of cannabis-impaired driving.

Objective: The objectives of the current study were to (1) characterize predictors of perceived risk of driving within 2 h of cannabis use and driving after cannabis use in a sample of adults who have used cannabis in the past year and (2) determine whether the influence of these predictors vary by state legalizations status.Methods: Data for this study were from online surveys. Study participants from Colorado, Iowa, and Illinois were included if they reported being between 25 and 40 years old and had a history of cannabis use. Outcome variables included (1) days of cannabis use per month, (2) reported driving within 2 h of cannabis use (vs. not driving within 2 h as reference), (3) proportion of driving after cannabis use days per month (days of driving a car within 2 h of cannabis use per month/days of cannabis use per month), and (4) perception of safety of driving after cannabis use. Potential predictors included age of first use of cannabis, gender, education status, and state of residence. The SAS GLMSELECT Procedure was used for the analysis.Results: Increased age of first use of cannabis was associated with decreased days of cannabis use per month (B = -0.51 days/month per year), a reduction in the proportion of driving after cannabis use days per month (B = -0.02 per month), and decreased perception of safety of driving after cannabis use (B = -0.06 per year). Female gender was also associated with less use (B = -2.3 days per month), a lower proportion of driving following use (B = -0.06 days driving/days used), and decreased perception of safety (B = -0.29). In addition, residents of Colorado reported using the most days, had the highest likelihood of driving within 2 h of use, and had the most positive perceptions of being able to safely drive after cannabis use.Conclusions: The delay in onset of cannabis use may mitigate its use among adults and driving after cannabis use. This has important implications for driver safety. Intervention programs for reducing cannabis's effects on driving should focus on individuals with early onset of use, male drivers, and drivers in states where cannabis for adult recreational use is legalized.

Perceived effects of cannabis: Generalizability of changes in driving performance.

OBJECTIVE: The objective of this analysis was to determine the generalizability of the relationship between different samples of a driver's perceived state after cannabis use and related performance while operating a motor vehicle. METHODS: Data were collected from 52 subjects in a study examining the effects of cannabis on driving performance. Data were analyzed using the SAS GLM Select procedure, using stepwise selection, with subjective effects, dosing condition (placebo vs. 6.18% delta-9-tetrahydrocannabinol [THC]), and driving context as independent measures. Correlation matrices of measures of driving performance against subjective responses and dosing condition used Pearson's and Spearman's test statistics, respectively. Results were compared to a prior study from a sample of 10 subjects. RESULTS: Subjective perceptions of acute cannabis impairment remain significant predictors of driving performance and explain individual variability in driving performance degradation as well as the data, beyond that which can be explained by acute use of cannabis alone. However, the significant subjective predictors of driving performance differ between the current and prior studies. To better understand these differences, correlations between subjective effects and performance measures were evaluated, which revealed that most correlations matched directionally (e.g., an increase in "good drug effect" was correlated with an increase in standard deviation of lane position [SDLP]). When there was a mismatch, 1 or more correlations were insignificant. Dosing condition and "stoned" were perfectly consistent; "high" and "sedated" contained 1 mismatch; and "anxious," "good drug effect" and "restless" contained 3 or more mismatches. CONCLUSIONS: The results indicate that across both studies, differences in the perceived effects of cannabis are reflected in changes in both lateral and longitudinal control beyond the acute effects of cannabis, which may help explain individual variability in response to acute intoxication. However, the generalizability of these findings is lacking, as shown by inconsistencies in when and where subjective effects were significant. Other factors such as frequency of use, usage type, the evolving profile of a cannabis user, as well as other individual differences should be considered to explain this additional variability.

Alterations in Electroencephalography Theta as Candidate Biomarkers of Acute Cannabis Intoxication.

The trend toward cannabis legalization in the United States over the past two decades has unsurprisingly been accompanied by an increase in the number of cannabis users and use patterns that potentially pose wider risks to the public like driving under the influence. As such, it is becoming increasingly important to develop methods to accurately quantify cannabis intoxication and its associated impairments on cognitive and motor function. Electroencephalography (EEG) offers a non-invasive method for quantitatively assessing neurophysiological biomarkers of intoxication and impairment with a high degree of temporal resolution. Twelve healthy, young recreational cannabis users completed a series of neurocognitive tasks with concurrent EEG acquisition using the ABM STAT X24 EEG headset in a within-subject counterbalanced design. The 1-h testbed consisted of resting state tasks and tests of attention and memory. Spectral densities were computed for resting state tasks, and event-related potentials (ERPs) were obtained for the attention and memory tasks. Theta band power (3-5 Hz) was decreased during cannabis intoxication compared to placebo during resting state tasks, as were average P400 and late positive potential (LPP) amplitudes during attention and memory tasks. Cannabis intoxication was also associated with elevated frontal coherence and diminished anterior-posterior coherence in the Theta frequency band. This work highlights the utility of EEG to identify and quantify neurophysiological biomarkers from recordings obtained during a short neurocognitive testbed as a method for profiling cannabis intoxication. These biomarkers may prove efficacious in distinguishing intoxicated from non-intoxicated individuals in lab and real-world settings.

Perceived effects of cannabis and changes in driving performance under the influence of cannabis.

OBJECTIVE: Reports indicate that cannabis users will adapt their driving to compensate for the perceived drug effects of cannabis. This analysis examined the relationship between driver perceptions of their state contrasted with objective measures of their performance while operating a motor vehicle. METHODS: Data was collected from ten subjects in a study examining the effects of cannabis on driving performance. Driving performance was collected on the NADS quarter-cab miniSim, a limited field of view non-motion simulator, approximately two hours after cannabis inhalation. Driving measures of both lateral and longitudinal control were included in our analysis. Subjective measures of the effects of cannabis were collected at peak and prior to driving, using visual analog scales. Data were analyzed using the SAS GLM Select procedure with subjective effect, dosing condition (placebo vs 6.9% THC), and driving event as independent measures. The stepwise selection method was used. RESULTS: The analysis of each of the subjective effects showed significant differences between the placebo and the active cannabis dosed conditions. While we found variance in difference between group means, there was greater variability between subject values. We found that subjective measures were predictive of variance in driver inputs, such as steering frequency and steering reversal rate. Variance in SDLP and other driving performance measures, however, were predicted by dosing condition. CONCLUSIONS: Overall, some of the effects perceived by the driver were better related to changes in driver inputs rather than the presence of cannabis itself. Changes in performance measures such as SDLP are better explained by dosing condition. Thus, driver's perceptions may result in changes to driving behavior that could mitigate the effect of cannabis. For both lateral and longitudinal control, an increasing perception of stimulation produced a positive effect on performance. Our results provide a better understanding of how different strains of cannabis, which produce different subjective experiences for users, could impact driving safety. Specifically, we found drug effects that produce more stimulation results in less impact on driving, while those that produce a more stoned or high feeling results in a greater negative effect on driving.

EEG biomarkers acquired during a short, straight-line simulated drive to predict impairment from cannabis intoxication.

OBJECTIVE: As cannabis use becomes more widely accepted, there is growing interest in its effects on brain function, specifically how it may impact daily functional activities such as driving, operating machinery, and other safety-related tasks. There are currently no validated methods for quantifying impairment from acute cannabis intoxication. The objective of this study was to identify neurophysiological correlates associated with driving simulator performance in subjects who were acutely intoxicated with cannabis. These signatures could help create an EEG-based profile of impairment due to acute cannabis intoxication. METHODS: Each subject completed a three-visit study protocol. Subjects were consented and screened on the first visit. On the second and third visits, subjects were administered either 500 mg of cannabis with 6.7% delta-9-tetrahydrocannabinol (THC) or placebo using a Volcano© Digit Vaporizer in a counterbalanced fashion. EEG was acquired from subjects as they performed a series of neurocognitive tasks and an approximately 45-minute simulated drive that included a rural straight-away absent of any other cars or obstacles during the final 10 minutes.EEG data was acquired using a STAT X24 wireless sensor headset during a simulated driving scenario from 10 subjects during the THC and placebo visits. Metrics of driving performance were extracted from the driving simulator and synchronized with EEG data using a common clock. RESULTS: A within-subjects analysis showed that the standard deviation of lane position (SDLP) was significantly worse and heart rate was elevated during the dosed visit compared to the placebo visit. Consistent with our prior findings, EEG power in the Theta frequency band (4-7 Hz) in the dosed condition was significantly decreased from the placebo condition. Theta power was negatively correlated with the SDLP driving performance metric, while there were no significant correlations between any EEG measure and SDLP in the placebo condition. CONCLUSIONS: These results, in combination with prior work on the effect of cannabis intoxication during neurocognitive tasks, suggest that neurophysiological signatures associated with acute cannabis intoxication are robust and consistent across tasks, and that these signatures are significantly correlated with impaired performance in a driving simulator. Taken together, EEG data acquired during a short neurocognitive testbed and during a simulated drive may provide specific profiles of impairment associated with acute cannabis intoxication. Further research is needed to establish the impaired cognitive processes associated with these EEG biomarkers.

Correlation of EEG biomarkers of cannabis with measured driving impairment.

Objective: The objective of this study was to use electroencephalogram (EEG) biomarkers derived from a short, easily administered neurocognitive testbed to determine acute cannabis intoxication and its effect on driving performance in a driving simulator.Methods: The data analyzed were from a study examining the relationship between psychomotor task performance, EEG data, and driving performance in a simulator. EEG data were collected using a STAT® X-24 EEG Wireless Sensor Headset, which was worn during the psychomotor and driving tasks. Driving data were collected for segments of consistent driving environments, including urban driving, urban curves, interstate, interstate curves, dark rural, and rural straightaways. Dependent measures included measures of lateral and longitudinal vehicle control.Results: There was a significant relationship between impaired driving performance as indicated by increased standard deviation of lane position and EEG power in slow theta band (3-5 Hz) in parietal and occipital areas.Conclusions: These results, combined with our prior reported results, suggest that EEG and electrocardiogram (ECG) acquired concurrent with neuropsychological tests hold potential to provide a highly sensitive, specific, and dose-dependent profile of cannabis intoxication and level of impairment.

Measuring the attitudes of novice drivers with autism spectrum disorder as an indication of apprehensive driving: Going beyond basic abilities.

For some individuals with autism spectrum disorder, driving apprehension may interfere with the acquisition and application of driving privileges. The Driving Attitude Scale Parent-Report provides an indication of novice drivers' positive and negative attitudes toward driving. Responses were compared for parents of 66 autism spectrum disorder and 166 neuro-typical novice drivers. After the autism spectrum disorder drivers completed 3 months of driver training, 60 parents repeated the Driving Attitude Scale Parent-Report. Parents reported autism spectrum disorder drivers to have less positive and more negative attitudes toward driving than parents of neuro-typical drivers. Parents of autism spectrum disorder drivers who received driving training in a safe/low-threat virtual reality driving simulator demonstrated a significant increase in positive attitudes and reduction in negative attitudes, compared to parents of autism spectrum disorder drivers undergoing routine driver training. The reports of parents of autism spectrum disorder drivers suggest potential problems with learning to drive that can go beyond general abilities and include driving apprehension.

Can Youth with Autism Spectrum Disorder Use Virtual Reality Driving Simulation Training to Evaluate and Improve Driving Performance? An Exploratory Study.

Investigate how novice drivers with autism spectrum disorder (ASD) differ from experienced drivers and whether virtual reality driving simulation training (VRDST) improves ASD driving performance. 51 novice ASD drivers (mean age 17.96 years, 78% male) were randomized to routine training (RT) or one of three types of VRDST (8-12 sessions). All participants followed DMV behind-the-wheel training guidelines for earning a driver's license. Participants were assessed pre- and post-training for driving-specific executive function (EF) abilities and tactical driving skills. ASD drivers showed worse baseline EF and driving skills than experienced drivers. At post-assessment, VRDST significantly improved driving and EF performance over RT. This study demonstrated feasibility and potential efficacy of VRDST for novice ASD drivers.