Effects of chronic marijuana use on driving performance

Factors related to the low-risk perception of driving after cannabis use

INTRODUCTION

Modifying risk perceptions related to driving after cannabis use (DACU) could deter individuals from enacting this behavior, as low-risk perception is associated with DACU engagement. This study identified sociodemographic characteristics, substance use, other driving behaviors, peer norms, and psychological characteristics that are associated with lower risk perception regarding DACU.

METHODS

Canadian drivers aged 17-35 who have used cannabis in the past year (n = 1,467) completed an online questionnaire. A multivariate linear regression model allowed for identifying variables associated with the low-risk perception of DACU (i.e. believing it to be safe as one's driving ability is not impaired by cannabis or by being high).

RESULTS

Lower risk perception of DACU was associated with identifying as male, weekly to daily cannabis use, engagement in DACU, general risky driving behaviors, being a passenger of a driver who engages in DACU, number of friends who engage in DACU, and peer approval of DACU. Having driven under the influence of alcohol, living in urban areas, having received traffic tickets in the past three years, and declaring past-week irritability and cognitive problems were associated with holding a higher risk perception related to DACU.

DISCUSSION

Road education and prevention programs should target attitudes and perceptions regarding risks shaped by sociocultural norms and past risky driving experiences. They need to reach out more specifically to drivers with the identified characteristics associated with the low-risk perception of DACU. These interventions can potentially help reduce the rate of individuals who engage in this behavior.

Driving after substance use in Rhode Island adolescents: A cross-sectional analysis of surveillance data

OBJECTIVE

Existing literature on driving under the influence during adolescence is sparse, especially for driving after the use of non-medical prescription drugs (DAP). This study examines the prevalence of driving after use of alcohol (DAA), cannabis (DAC), and DAP, and examines the role of several potential risk and protective factors.

METHODS

This was a secondary analysis of the 2022 Rhode Island Study Survey, a cross-sectional survey of middle and high school students. Separate multivariable regressions were conducted for each outcome among lifetime users for each substance, controlling for current substance use, individual-, perceived parental-, and perceived friend-substance use risk perception, age, sexual/gender minority (SGM) status, race, ethnicity, school level, and town poverty level.

RESULTS

Among lifetime users of alcohol (n = 3849), cannabis (n = 2289), and non-medical prescription drugs (n = 611), the prevalence of DAA, DAC, and DAP was 4.9, 14.3, and 16.9%, respectively. Current substance use, high individual risk perception, being nonwhite, and being Hispanic were risk factors for DAA while perceiving parent's risk perception as negative and being heterosexual cisgender-female were protective. Current substance use, negative individual risk perception, and being nonwhite were risk factors for DAC while perceiving parent's risk perception as negative and being in high school were protective. Current substance use and older age were risk factors for DAP while perceiving parent's risk perception as negative and perceiving friend's risk perception as negative were protective.

CONCLUSIONS

Driving under the influence is a concern among adolescent substance users. Current substance use and perceived parental risk perception as negative are common risks and protective factors, respectively. Findings suggest substance-specific, heterogeneous interventions are needed. For example, interventions focusing on peer perceptions are most relevant for DAP, while shifting personal perceptions of harm are most relevant for DAC.

A semi-naturalistic open-label study examining the effect of prescribed medical cannabis use on simulated driving performance

BACKGROUND

Despite increasing medical cannabis use, research has yet to establish whether and to what extent products containing delta-9-tetrahydrocannabinol (THC) impact driving performance among patients. Stable doses of prescribed cannabinoid products during long-term treatment may alleviate clinical symptoms affecting cognitive and psychomotor performance.

AIM

To examine the effects of open-label prescribed medical cannabis use on simulated driving performance among patients.

METHODS

In a semi-naturalistic laboratory study, 40 adults (55% male) aged between 23 and 80 years, consumed their own prescribed medical cannabis product. Driving performance outcomes including standard deviation of lateral position (SDLP), the standard deviation of speed (SDS), mean speed and steering variability were evaluated using the Forum8 driving simulator at baseline (pre-dosing), 2.5 h and 5 -h (post-dosing). Perceived driving effort (PDE) was self-reported after each drive. Oral fluid and whole blood samples were collected at multiple timepoints and analysed for THC via liquid chromatography-mass spectrometry.

RESULTS

A significant main effect of time was observed for mean speed (p = 0.014) and PDE (p = 0.020), with patients displaying modest stabilisation of vehicle control, increased adherence to speed limits and reductions in PDE post-dosing, relative to baseline. SDLP (p = 0.015) and PDE (p = 0.043) were elevated for those who consumed oil relative to flower-based products. Detectable THC concentrations were observed in oral fluid at 6-h post-dosing (range = 0-24 ng/mL).

CONCLUSIONS

This semi-naturalistic study suggests that the consumption of medical cannabis containing THC (1.13-39.18 mg/dose) has a negligible impact on driving performance when used as prescribed.

Cannabis and Driving in Older Adults

Importance

Epidemiological studies have found that cannabis increases the risk of a motor vehicle collision. Cannabis use is increasing in older adults, but laboratory studies of the association between cannabis and driving in people aged older than 65 years are lacking.

Objective

To investigate the association between cannabis, simulated driving, and concurrent blood tetrahydrocannabinol (THC) levels in older adults.

Design, Setting, and Participants

Using an ecologically valid counterbalanced design, in this cohort study, regular cannabis users operated a driving simulator before, 30 minutes after, and 180 minutes after smoking their preferred legal cannabis or after resting. This study was conducted in Toronto, Canada, between March and November 2022 with no follow-up period. Data were analyzed from December 2022 to February 2023.

Exposures

Most participants chose THC-dominant cannabis with a mean (SD) content of 18.74% (6.12%) THC and 1.46% (3.37%) cannabidiol (CBD).

Main outcomes and measures

The primary end point was SD of lateral position (SDLP, or weaving). Secondary outcomes were mean speed (MS), maximum speed, SD of speed, and reaction time. Driving was assessed under both single-task and dual-task (distracted) conditions. Blood THC and metabolites of THC and CBD were also measured at the time of the drives.

Results

A total of 31 participants (21 male [68%]; 29 White [94%], 1 Latin American [3%], and 1 mixed race [3%]; mean [SD] age, 68.7 [3.5] years), completed all study procedures. SDLP was increased and MS was decreased at 30 but not 180 minutes after smoking cannabis compared with the control condition in both the single-task (SDLP effect size [ES], 0.30; b = 1.65; 95% CI, 0.37 to 2.93; MS ES, -0.58; b = -2.46; 95% CI, -3.56 to -1.36) and dual-task (SDLP ES, 0.27; b = 1.75; 95% CI, 0.21 to 3.28; MS ES, -0.47; b = -3.15; 95% CI, -5.05 to -1.24) conditions. Blood THC levels were significantly increased at 30 minutes but not 180 minutes. Blood THC was not correlated with SDLP or MS at 30 minutes, and SDLP was not correlated with MS. Subjective ratings remained elevated for 5 hours and participants reported that they were less willing to drive at 3 hours after smoking.

Conclusions and relevance

In this cohort study, the findings suggested that older drivers should exercise caution after smoking cannabis.

A systematic review of oculomotor deficits associated with acute and chronic cannabis use

Driving is a critical everyday task necessitating the rapid and seamless integration of dynamic visually derived information to guide neurobehaviour. Biological markers are frequently employed to detect Δ9-tetrahydrocannabinol (THC) consumption among drivers during roadside tests, despite not necessarily indicating impairment. Characterising THC-specific alterations to oculomotor behaviour may offer a more sensitive measure for indexing drug-related impairment, necessitating discrimination between acute THC effects, chronic use and potential tolerance effects. The present review aims to synthesise current evidence on the acute and chronic effects of THC on driving-relevant oculomotor behaviour. The review was prospectively registered (10.17605/OSF.IO/A4H9W), and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines informed reporting standards. Overall, 20 included articles comprising 12 experimental acute dosing trials, 5 cross-sectional chronic use studies and 3 roadside epidemiological studies examined the effects of cannabis/THC on oculomotor parameters including saccadic activity gaze behaviour, nystagmus, smooth pursuit and eyelid/blink characteristics. Acute THC consumption selectively impacts oculomotor control, notably increasing saccadic latency and inaccuracy and impairing inhibitory control. Chronic cannabis users, especially those with early age of use onset, display enduring oculomotor deficits that affect visual scanning efficiency. The presence of eyelid tremors appears to be a reliable indicator of cannabis consumption while remaining distinct from direct impairment associated with visual attention and motor control. Cannabis selectively influences oculomotor activity relevant to driving, highlighting the role of cannabinoid systems in these processes. Defining cannabis/THC-specific changes in oculomotor control may enhance the precision of roadside impairment assessments and vehicle safety systems to detect drug-related impairment and assess driving fitness.

Driving Under the Influence of Cannabis: Impact of Combining Toxicology Testing with Field Sobriety Tests

BACKGROUND

Cannabis is increasingly used both medically and recreationally. With widespread use, there is growing concern about how to identify cannabis-impaired drivers.

METHODS

A placebo-controlled randomized double-blinded protocol was conducted to study the effects of cannabis on driving performance. One hundred ninety-one participants were randomized to smoke ad libitum a cannabis cigarette containing placebo or delta-9-tetrahydrocannabinol (THC) (5.9% or 13.4%). Blood, oral fluid (OF), and breath samples were collected along with longitudinal driving performance on a simulator (standard deviation of lateral position [SDLP] and car following [coherence]) over a 5-hour period. Law enforcement officers performed field sobriety tests (FSTs) to determine if participants were impaired.

RESULTS

There was no relationship between THC concentrations measured in blood, OF, or breath and SDLP or coherence at any of the timepoints studied (P > 0.05). FSTs were significant (P < 0.05) for classifying participants into the THC group vs the placebo group up to 188 minutes after smoking. Seventy-one minutes after smoking, FSTs classified 81% of the participants who received active drug as being impaired. However, 49% of participants who smoked placebo (controls) were also deemed impaired at this same timepoint. Combining a 2 ng/mL THC cutoff in OF with positive findings on FSTs reduced the number of controls classified as impaired to zero, 86 minutes after smoking the placebo.

CONCLUSIONS

Requiring a positive toxicology result in addition to the FST observations substantially improved the classification accuracy regarding possible driving under the influence of THC by decreasing the percentage of controls classified as impaired.

Distraction "Hangover": Characterization of the Delayed Return to Baseline Driving Risk After Distracting Behaviors

OBJECTIVE

We measured how long distraction by a smartphone affects simulated driving behaviors after the tasks are completed (i.e., the distraction hangover).

BACKGROUND

Most drivers know that smartphones distract. Trying to limit distraction, drivers can use hands-free devices, where they only briefly glance at the smartphone. However, the cognitive cost of switching tasks from driving to communicating and back to driving adds an underappreciated, potentially long period to the total distraction time.

METHOD

Ninety-seven 21- to 78-year-old individuals who self-identified as active drivers and smartphone users engaged in a simulated driving scenario that included smartphone distractions. Peripheral-cue and car-following tasks were used to assess driving behavior, along with synchronized eye tracking.

RESULTS

The participants' lateral speed was larger than baseline for 15 s after the end of a voice distraction and for up to 25 s after a text distraction. Correct identification of peripheral cues dropped about 5% per decade of age, and participants from the 71+ age group missed seeing about 50% of peripheral cues within 4 s of the distraction. During distraction, coherence with the lead car in a following task dropped from 0.54 to 0.045, and seven participants rear-ended the lead car. Breadth of scanning contracted by 50% after distraction.

CONCLUSION

Simulated driving performance drops dramatically after smartphone distraction for all ages and for both voice and texting.

APPLICATION

Public education should include the dangers of any smartphone use during driving, including hands-free.

Typologies of Canadian young adults who drive after cannabis use: A two-step cluster analysis

Young adults that drive after cannabis use (DACU) may not share all the same characteristics. This study aimed to identify typologies of Canadians who engage in DACU. About 910 cannabis users with a driver's license (17-35 years old) who have engaged in DACU completed an online questionnaire. Two-step cluster analysis identified four subgroups, based on driving-related behaviors, cannabis use and related problems, and psychological distress. Complementary comparative analysis among the identified subgroups was performed as external validation. The identified subgroups were: (1) frequent cannabis users who regularly DACU; (2) individuals with generalized deviance with diverse risky road behaviors and high levels of psychological distress; (3) alcohol and drug-impaired drivers who were also heavy frequent drinkers; and (4) well-adjusted youths with mild depressive-anxious symptoms. Individuals who engaged in DACU were not a homogenous group. When required, prevention and treatment need to be tailored according to the different profiles.

Medical Cannabis and Past-Year Cannabis Use Disorder Among Adult Recreational Users in the United States: Results From a Nationally Representative Sample

INTRODUCTION

With the increasing number of cannabis users and more jurisdictions allowing medical cannabis, more evidence-based knowledge about the prevalence of cannabis use disorder (CUD) among medical users is greatly needed.

OBJECTIVES

To examine and compare the prevalence and severity of CUD and the prevalence of different CUD criteria among two groups: those who combine recreational and medical use vs. those who exclusively use cannabis recreationally. To examine the association between CUD and sociodemographic characteristics, medical conditions, and psychiatric comorbidities between these two groups.

METHODS

The National Epidemiological Survey on Alcohol and Related Conditions III data were used, a US nationally representative in-person interview of 36,309 adults aged ≥18 years collected in 2012-2013. The statistical examination included proportion comparison hypothesis testing and linear regressions, all using complex survey design analysis procedures.

RESULTS

Recreational users who used cannabis also for medical purposes had a higher prevalence of CUD in general, as well as mild and moderate CUD than users who used cannabis only for recreational purposes. CUD is more prevalent in recreational, medical users with the following characteristics: young, male, non-white, living in the Midwest, using a greater amount of cannabis, having a concurrent mental disorder, and had CUD before the past year.

CONCLUSION

Recreational, medical cannabis users have a higher likelihood of having CUD. Although the results should be taken with caution, given the lack of established validity of CUD among medical users, health care professionals who prescribe or recommend the use of cannabis for medical purposes should take this into consideration while evaluating the risks/benefits ratio of cannabis. They need to assess patients' recreational cannabis use, screen for CUD, and educate users about the possible complications caused by cannabis use.

Lower-Risk Cannabis Use Guidelines (LRCUG) for reducing health harms from non-medical cannabis use: A comprehensive evidence and recommendations update

BACKGROUND

Cannabis use is common, especially among young people, and is associated with risks for various health harms. Some jurisdictions have recently moved to legalization/regulation pursuing public health goals. Evidence-based 'Lower Risk Cannabis Use Guidelines' (LRCUG) and recommendations were previously developed to reduce modifiable risk factors of cannabis-related adverse health outcomes; related evidence has evolved substantially since. We aimed to review new scientific evidence and to develop comprehensively up-to-date LRCUG, including their recommendations, on this evidence basis.

METHODS

Targeted searches for literature (since 2016) on main risk factors for cannabis-related adverse health outcomes modifiable by the user-individual were conducted. Topical areas were informed by previous LRCUG content and expanded upon current evidence. Searches preferentially focused on systematic reviews, supplemented by key individual studies. The review results were evidence-graded, topically organized and narratively summarized; recommendations were developed through an iterative scientific expert consensus development process.

RESULTS

A substantial body of modifiable risk factors for cannabis use-related health harms were identified with varying evidence quality. Twelve substantive recommendation clusters and three precautionary statements were developed. In general, current evidence suggests that individuals can substantially reduce their risk for adverse health outcomes if they delay the onset of cannabis use until after adolescence, avoid the use of high-potency (THC) cannabis products and high-frequency/-intensity of use, and refrain from smoking-routes for administration. While young people are particularly vulnerable to cannabis-related harms, other sub-groups (e.g., pregnant women, drivers, older adults, those with co-morbidities) are advised to exercise particular caution with use-related risks. Legal/regulated cannabis products should be used where possible.

CONCLUSIONS

Cannabis use can result in adverse health outcomes, mostly among sub-groups with higher-risk use. Reducing the risk factors identified can help to reduce health harms from use. The LRCUG offer one targeted intervention component within a comprehensive public health approach for cannabis use. They require effective audience-tailoring and dissemination, regular updating as new evidence become available, and should be evaluated for their impact.

Mechanisms of cannabis impairment: Implications for modeling driving performance

Past research on cannabis has been limited in scope to THC potencies lower than legally available and efforts to integrate the effects into models of driving performance have not been attempted to date. The purpose of this systematic review is to understand the implications for modeling driving performance and describe future research needs. The risk of motor vehicle crashes increases 2-fold after smoking marijuana. Driving during acute cannabis intoxication impairs concentration, reaction time, along with a variety of other necessary driving-related skills. Changes to legislation in North America and abroad have led to an increase in cannabis' popularity. This has given rise to more potent strains, with higher THC concentrations than ever before. There is also rising usage of novel ingestion methods other than smoking, such as oral cannabis products (e.g., brownies, infused drinks, candies), vaping, and topicals. The PRISMA guidelines were followed to perform a systematic search of the PubMed database for peer-reviewed literature. Search terms were combined with keywords for driving performance: driving, performance, impairment. Grey literature was also reviewed, including congressional reports, committee reports, and roadside surveys. There is a large discrepancy between the types of cannabis products sold and what is researched. Almost all studies that used inhalation as the mode of ingestion with cannabis that is around 6% THC. This pales in comparison to the more potent strains being sold today which can exceed 20%. Which is to say nothing of extracts, which can contain 60% or more THC. Experimental protocol is another gap in research that needs to be filled. Methodologies that involve naturalistic (real world) driving environments, smoked rather than vaporized cannabis, and non-lab certified products introduce uncontrollable variables. When considering the available literature and the implications of modeling the impacts of cannabis on driving performance, two critical areas emerge that require additional research: The first is the role of cannabis potency. Second is the route of administration. Does the lower peak THC level result in smaller impacts on performance? How long does potential impairment last along the longer time-course associated with different pharmacokinetic profiles. It is critical for modeling efforts to understand the answers to these questions, accurately model the effects on driver performance, and by extension understand the risk to the public.

Risk Factors Associated With Driving After Cannabis Use Among Canadian Young Adults

This study identifid the most prominent risk factors associated with driving after cannabis use (DACU). 1,126 Canadian drivers (17–35 years old) who have used cannabis in the past 12 months completed an online questionnaire about sociodemographic information, substance use habits, cannabis effect expectancies, driving behaviours and peers’ behaviours and attitudes concerning DACU. A hierarchical logistic regression allowed identifying variables that were associated with DACU. Income (CA$30,000–CA$69,000), weekly-to-daily cannabis use, higher level of cannabis-related problems, expectation that cannabis facilitates social interactions, drunk driving, belief that DACU is safe, general risky driving behaviours, having a few friends who had DACU and injunctive norms predicted past 12-month DACU. Older age, holding negative expectations concerning cannabis, driving aggressively and perceived accessibility of public transportation decreased the probability of DACU. With restricted resources, programmes will be more efficient by targeting Canadian young adults most inclined to DACU by focussing on these risk factors.

Steering clear: Traffic violations among emerging adults who engage in habitual or casual cannabis use

While some research has shown that cannabis use can impair driving ability, evidence to the degree and impact of impairment are lacking. This study examined the association between habitual or casual cannabis use and past-year traffic violations among emerging adults (EAs). Data come from the 2012 Canadian Community Health Survey-Mental Health. Respondents (n = 5630) were categorized as: early (15-19 y), middle (20-24 y), and late (25-29 y) EAs. Traffic violations were measured using self-report and cannabis use was measured using the WHO Composite International Diagnostic Interview. The prevalence of traffic violations was higher for males (19.2 %) vs females (9.9 %) and middle (16.2 %) and late (19.4 %) EAs vs early (8.8 %) EAs. The odds of reporting traffic violations were higher for EAs who engaged in habitual [OR = 1.77 (1.17-2.67)] or casual [OR = 1.79 (1.27-2.51)] cannabis use when compared to non-users. Age moderated the association such that higher odds of traffic violations were reported in early EAs who were casual cannabis users and middle EAs who were habitual or casual cannabis users when compared to non-users. Use of other drugs was also a moderator-in the absence vs. presence of other drug use, odds of traffic violations were higher in those who engaged in either habitual or casual use of cannabis. When accounting for the moderating effects of age and drug use, habitual and casual cannabis use resulted in increased odds of a traffic violation. Future research is warranted to explore the robustness of our findings.

Cannabis, Impaired Driving, and Road Safety: An Overview of Key Questions and Issues

The road safety impact of cannabis has been a topic of much discussion and debate over the years. These discussions have been revitalized in recent years by initiatives in several jurisdictions to legalize non-medical cannabis. Canada became the second country to legalize non-medical cannabis use in October, 2018, preceded by Uruguay in December 2013. Road safety concerns were key issues in the Canadian government's deliberations on the issue. In this paper, we identify several key questions related to the impact of cannabis on road safety, and provide a consideration of the relevant literature on these questions. These questions cover several perspectives. From an epidemiological perspective, perhaps the central question is whether cannabis use contributes to the chances of being involved in a collision. The answer to this question has evolved in recent years as the ability to conduct the relevant studies has evolved. A related question is the extent to which cannabis plays an important role in road safety, and recent research has made progress in estimating the collisions, injuries, and deaths that may be attributed to cannabis use. Several questions relate to the behavioral and pharmacological effects of cannabis. One central question is whether cannabis affects driving skills in ways that can increase the chances of being involved in a collision. Another important question is whether the effects of the drug on the driving behavior of medical users is similar to, or different from, the effects on non-medical users and whether there are sex differences in the pharmacological and behavioral effects of cannabis. Other important questions are the impact of tolerance to the effects of cannabis on road safety as well as different routes of administration (e.g., edibles, vaped). It remains unclear if there is a dose-response relationship of cannabis to changes in driving. These and other key questions and issues are identified and discussed in this paper.

Risk factors associated with driving under the influence of drugs in the USA

BACKGROUND

Driving under the influence of drugs (DUID) is a burgeoning public health concern in the USA. Because little is known about individuals who engage in DUID, the purpose of this study was to analyse potential sociodemographic characteristics and behavioural risk factors associated with the behaviour.

METHODS

Self-reported data from drivers ≥18 years of age who ever used drugs and participated in the 2018 National Survey on Drug Use and Health were used. Characteristics of those who reported to engage and not engage in DUID were compared via frequencies, percentages and logistic regression analyses, which accounted for the multistage survey design.

RESULTS

Among eligible respondents, 10.4% (weighted n=117 275 154) reported DUID. DUID was higher among those aged 18-25 year (34%), males (65%), unmarried individuals (61%), lesbian/gay/bisexuals (13%), those whom abused or were drug dependent (45%), engaged in numerous risky lifestyle behaviours (12%) and those taking medication for a mental health issue (22%). Nearly 20% and 6% of respondents engaged in DUID abused or were dependent on marijuana or methamphetamine, respectively. The adjusted odds of DUID were greatest among those 18-25 years of age (OR 3.7; 95% CI 2.8 to 5.0), those never/not married (OR 1.8; 95% CI 1.5 to 2.2), those who abused or were drug dependent (OR 4.0; 95% CI 3.5 to 4.7), exhibited riskier lifestyle behaviours (OR 8.0; 95% CI 5.9 to 11.0), were employed (OR 1.3; 95% CI 1.1 to 1.6) or lesbian/gay/bisexuals (OR 1.4; 95% CI 1.1 to 1.7).

CONCLUSIONS

DUID was common among some population sub-groups who may benefit from intervention.