Importance

Expanding cannabis medicalization and legalization increases the urgency to understand the factors associated with acute driving impairment.

Objective

To determine, in a large sample of regular cannabis users, the magnitude and time course of driving impairment produced by smoked cannabis of different Δ9-tetrahydrocannabinol (THC) content, the effects of use history, and concordance between perceived impairment and observed performance.

Design, setting, and participants

This double-blind, placebo-controlled parallel randomized clinical trial took place from February 2017 to June 2019 at the Center for Medicinal Cannabis Research, University of California San Diego. Cannabis users were recruited for this study, and analysis took place between April 2020 and September 2021.

Interventions

Placebo or 5.9% or 13.4% THC cannabis smoked ad libitum.

Main outcomes and measures

The primary end point was the Composite Drive Score (CDS), which comprised key driving simulator variables, assessed prior to smoking and at multiple time points postsmoking. Additional measures included self-perceptions of driving impairment and cannabis use history.

Results

Of 191 cannabis users, 118 (61.8%) were male, the mean (SD) age was 29.9 (8.3) years, and the mean (SD) days of use in the past month was 16.7 (9.8). Participants were randomized to the placebo group (63 [33.0%]), 5.9% THC (66 [34.6%]), and 13.4% THC (62 [32.5%]). Compared with placebo, the THC group significantly declined on the Composite Drive Score at 30 minutes (Cohen d = 0.59 [95% CI, 0.28-0.90]; P < .001) and 1 hour 30 minutes (Cohen d = 0.55 [95% CI, 0.24-0.86]; P < .001), with borderline differences at 3 hours 30 minutes (Cohen d = 0.29 [95% CI, -0.02 to 0.60]; P = .07) and no differences at 4 hours 30 minutes (Cohen d = -0.03 [95% CI, -0.33 to 0.28]; P = .87). The Composite Drive Score did not differ based on THC content (likelihood ratio χ24 = 3.83; P = .43) or use intensity (quantity × frequency) in the past 6 months (likelihood ratio χ24 = 1.41; P = .49), despite postsmoking blood THC concentrations being higher in those with the highest use intensity. Although there was hesitancy to drive immediately postsmoking, increasing numbers (81 [68.6%]) of participants reported readiness to drive at 1 hour 30 minutes despite performance not improving from initial postsmoking levels.

Conclusions and relevance

Smoking cannabis ad libitum by regular users resulted in simulated driving decrements. However, when experienced users control their own intake, driving impairment cannot be inferred based on THC content of the cigarette, behavioral tolerance, or THC blood concentrations. Participants' increasing willingness to drive at 1 hour 30 minutes may indicate a false sense of driving safety. Worse driving performance is evident for several hours postsmoking in many users but appears to resolve by 4 hours 30 minutes in most individuals. Further research is needed on the impact of individual biologic differences, cannabis use history, and administration methods on driving performance.

Trial registration

ClinicalTrials.gov Identifier: NCT02849587.

Digital health technologies can provide continuous monitoring and objective, real-world measures of Parkinsons disease (PD), but have primarily been evaluated in small, single-site studies. In this 12-month, multicenter observational study, we evaluated whether a smartwatch and smartphone application could measure features of early PD. 82 individuals with early, untreated PD and 50 age-matched controls wore research-grade sensors, a smartwatch, and a smartphone while performing standardized assessments in the clinic. At home, participants wore the smartwatch for seven days after each clinic visit and completed motor, speech and cognitive tasks on the smartphone every other week. Features derived from the devices, particularly arm swing, the proportion of time with tremor, and finger tapping, differed significantly between individuals with early PD and age-matched controls and had variable correlation with traditional assessments. Longitudinal assessments will inform the value of these digital measures for use in future clinical trials.