Driving under the influence behaviours among high school students who mix alcohol with energy drinks.

Alcohol and energy drinks are commonly used substances by youth in Canada, and are often mixed (AmED). While several studies have shown that AmED can have dangerous effects, less well understood is how AmED is associated with driving under the influence of either alcohol or drugs. This study sought to determine whether youth who use AmED were more likely to engage in driving, or being a passenger of a driver, under the influence of alcohol or cannabis compared to youth who use either alcohol or energy drinks alone. This study used data from grade 10-12 students who took part in the 2014/2015 Canadian Student Tobacco, Alcohol and Drugs Survey (N=17,450). The association of past-year AmED use with past-30day: driving under the influence of alcohol or cannabis, and riding with an alcohol- or cannabis-influenced driver, was assessed using logistic regression. One in four youth had consumed AmED in the previous 12months. AmED users were more likely to engage in all risk behaviours except riding with a drinking driver, relative to youth who only consumed alcohol. No association was observed for youth who consumed alcohol and energy drinks on separate occasions. Youth who use AmED demonstrate a higher risk profile for driving under the influence of alcohol or cannabis, than youth who use alcohol alone. Future research should explore the biopsychosocial pathways that may explain why using energy drinks enhances the already heightened risk posed by alcohol on other health-related behaviours such as driving under the influence.

Reliability of roadside oral fluid testing devices for ∆9 -tetrahydrocannabinol (∆9 -THC) detection.

Driving under the influence of cannabis (DUIC) is increasing worldwide, and cannabis is the most prevalent drug after alcohol in impaired driving cases, emphasizing the need for a reliable traffic enforcement strategy. ∆9 -tetrahydrocannabinol (THC) detection in oral fluid has great potential for identifying recent cannabis use; however, additional data are needed on the sensitivities, specificities, and efficiencies of different oral fluid devices for detecting cannabinoids at the roadside by police during routine traffic safety enforcement efforts. At the roadside, 8945 oral fluid THC screening tests were performed with four devices: AquilaScan®, Dräger DrugTest®, WipeAlyser Reader®, and Druglizer®. A total of 530 samples screened positive for THC (5.9%) and were analyzed by liquid chromatography-tandem mass spectrometry at multiple cutoff concentrations (2 ng/mL, 10 ng/mL, and manufacturers' recommended device cutoffs) to investigate device performance. Results varied substantially, with sensitivities of 0%-96.8%, specificities of 89.8%-98.5%, and efficiencies of 84.3%-97.8%. The Dräger DrugTest® outperformed the other devices with a 96.8% sensitivity, 97.1% specificity, and 97.0% efficiency at a 5-ng/mL LC-MS/MS confirmation cutoff. The WipeAlyser Reader® had good performance with a 91.4% sensitivity, 97.2% specificity, and 96.4% efficiency. AquilaScan® and Druglizer® had unacceptable performance for cannabinoid detection, highlighted by sensitivity <13%. The choice of roadside oral fluid testing device must offer good analytical performance for cannabinoids because of its high prevalence of use and impact on road safety.

"Wake-and-bake" cannabis use: Predictors and cannabis-related outcomes of use shortly after waking.

BACKGROUND: Given recent historical increases in young adults frequent cannabis use and changes in cannabis policies throughout the United States, there is a need to examine high-risk patterns of use. This paper examined predictors and cannabis-related outcomes of "wake-and-bake" cannabis use, operationalized as use within 30min of waking. METHODS: Participants were 409 young adults (Mage=21.61 years, 50.8% female) enrolled in a longitudinal study on simultaneous alcohol and cannabis use (i.e., using alcohol and cannabis at the same time such that their effects overlap). Eligibility criteria included reporting alcohol use 3+ times and simultaneous alcohol and cannabis use 1+ times in the past month. Participants completed twice-daily surveys for six 14-day bursts across two calendar years. Aims were tested using multilevel models. RESULTS: Analyses were limited to cannabis use days (9406 days; 33.3% of all sampled days), and thereby to participants who reported using cannabis (384 participants; 93.9% of the sample). Wake-and-bake use was reported on 11.2% of cannabis use days and at least once by 35.4% of participants who used cannabis. On wake-and-bake use days, participants were high for more hours and had greater odds of driving under the influence of cannabis, but did not experience more negative consequences, relative to non-wake-and-bake cannabis use days. Participants who reported more cannabis use disorder symptoms and those reporting higher average social anxiety motives for cannabis use reported more frequent wake-and-bake use. CONCLUSIONS: Wake-and-bake cannabis use may be a useful marker of high-risk cannabis use, including driving under the influence of cannabis.

Mobile-based brief interventions targeting cannabis-impaired driving among youth: A Delphi study.

INTRODUCTION: Brief interventions delivered using mobile technologies have become popular to reduce youth alcohol use, however, few have been applied to cannabis use and driving under the influence of cannabis (DUIC). This Delphi study sought to create and compare consensus among a panel of experts (potential intervention developers) and a panel of youth (intervention audience) on the characteristics to prioritize in a youth DUIC mobile-based brief intervention. METHODS: A two-round two-panel Delphi study was conducted among 26 professionals with expertise in youth substance use and impaired driving and 20 youth who use cannabis. Participants ranked the importance of 45 evidence-informed intervention characteristics using a 7-point Likert scale. Characteristics that received an interquartile deviation score ≤ 1 (indicating consensus) and a median score of ≥6 (indicating importance) in both panels were considered shared priorities. Differences in panel rankings were quantified using Mann-Whitney U tests. RESULTS: Consensus was achieved for 41 characteristics in the professional panel and 34 in the youth panel, with ratings generally higher among professionals. Overall, 16 shared priorities emerged. These include critical theoretical characteristics (e.g., self-efficacy, motivation, overcoming barriers), practical characteristics (e.g., mobile availability, estimates of intervention length, ability to input behaviours) and core contents (e.g., real-life stories, education on the risks/dangers, appropriate messaging). Youth's perceptions on the dangers of DUIC received the most support for an intervention outcome. CONCLUSIONS: Findings can inform the development of mobile-based brief interventions for youth, an essential step in reducing DUIC among youth and addressing this public health concern.

A systematic review of factors associated with illegal drug driving.

Drug driving is a serious problem worldwide that can increase the risk of road crashes. This systematic review seeks to identify factors associated with drug driving (i.e., driving after consuming drugs other than alcohol) to highlight gaps in existing knowledge and inform the design of more effective countermeasures. A search of the literature was conducted for the period January 1, 2005 to July 31, 2021 using six different databases. The search protocol followed PRISMA guidelines and was registered in PROSPERO (#CRD42021234616). Studies that met inclusion criteria compared drug drivers with either non-drug drivers, alcohol-only drivers or drug drivers from an earlier time period, to identify factors specifically associated with drug driving, rather than common to all drivers. Two hundred and nineteen publications met the inclusion criteria and were included within the review. Based on the findings, a logic model was developed that presents the factors associated with drug driving. Various sociodemographic, psychosocial and legal factors emerged as the main factors associated with illegal drug driving. At the sociodemographic and psychological levels, drug drivers were more likely to be single, young males who often drive after using cannabis and who score high on sensation-seeking and impulsivity scales. The key social factor found to be associated with drug driving was peer acceptance/disapproval of the behaviour. At the legal level, the review suggested that the effectiveness of current enforcement approaches to drug driving vary among jurisdictions around the world due to differences in the level of perceived certainty of apprehension and the chances of punishment avoidance. Future research into the anticipated and actual rewards for drug driving is needed to inform the development of more effective countermeasures.

Corrigendum: The Association of Unfavorable Traffic Events and Cannabis Usage: A Meta-Analysis.

[This corrects the article on p. 99 in vol. 9, PMID: 29487531.].

The Association of Unfavorable Traffic Events and Cannabis Usage: A Meta-Analysis.

Background: In the last years were published many epidemiological articles aiming to link driving under the influence of cannabis (DUIC) with the risk of various unfavorable traffic events (UTEs), with sometimes contradictory results. Aim: The primary objective of this study was to analyze whether there is a significant association between DUIC and UTEs. Materials and Methods: We used two meta-analytical methods to assess the statistical significance of the effect size: random-effects model and inverse variance heterogeneity model. Results: Twenty-four studies were included in the meta-analysis. We obtained significant increases in the effect size for DUIC tested through blood analysis, with an odds ratio (OR) of 1.97 and a confidence interval (CI) between 1.35 and 2.87; [corrected] death as an outcome, with an OR of 1.56 and a CI between 1.16 and 2.09; and case-control as the type of study, with an OR of 1.99 and a CI between 1.05 and 3.80. Publication bias was very high. Conclusion: Our analysis suggests that the overall effect size for DUIC on UTEs is not statistically significant, but there are significant differences obtained through subgroup analysis. This result might be caused by either methodological flaws (which are often encountered in articles on this topic), the indiscriminate employment of the term "cannabis use," or an actual absence of an adverse effect. When a driver is found, in traffic, with a positive reaction suggesting cannabis use, the result should be corroborated by either objective data regarding marijuana usage (like blood analyses, with clear cut-off values), or a clinical assessment of the impairment, before establishing his/her fitness to drive.