Driving and Substance Use

"Marijuana is the illicit drug most frequently found in the blood of drivers who have been involved in vehicle crashes, including fatal ones.¹⁰ Two large European studies found that drivers with THC in their blood were roughly twice as likely to be culpable for a fatal crash than drivers who had not used drugs or alcohol.^11,12 However, the role played by marijuana in crashes is often unclear because it can be detected in body fluids for days or even weeks after intoxication and because people frequently combine it with alcohol. Those involved in vehicle crashes with THC in their blood, particularly higher levels, are three to seven times more likely to be responsible for the incident than drivers who had not used drugs or alcohol. The risk associated with marijuana in combination with alcohol appears to be greater than that for either drug by itself.⁸

"Several meta-analyses of multiple studies found that the risk of being involved in a crash significantly increased after marijuana use¹³—in a few cases, the risk doubled or more than doubled.^14–16 However, a large case-control study conducted by the National Highway Traffic Safety Administration found no significant increased crash risk attributable to cannabis after controlling for drivers’ age, gender, race, and presence of alcohol.¹⁷"

"Our study suggests that, on average, MMLs are associated with reductions in traffic fatalities, particularly pronounced among those aged 25 to 44 years, a group representing a great percentage of all registered patients for medical marijuana use,²⁹ and with increased prevalence of marijuana use after the enactment of MMLs.³⁰ Although increases in marijuana use following the establishment of marijuana dispensaries could reduce the occurrence of alcohol-related mortality by reducing the number of drivers driving under the influence of alcohol, other simultaneous factors at the state and local levels also may be responsible for these changes in traffic fatalities. Our findings show great heterogeneity of the MML–traffic fatalities associations across states, suggesting the presence of these other mechanisms. This is important for policy development and for the debate of the enactment or repealing of MMLs, given that alternative local strategies such as stronger police enforcement and programs aiming to reduce impaired driving involving any substance use could be local factors linked to reductions in traffic fatalities in MML states."

"To combat drug-driving, most countries either operate a zero tolerance policy or take into account degree of impairment, sometimes in a two-tier system. Legal limits may be set low, at the limit of detection, or higher to take effects into consideration. For example, while the project set a detection limit of 1 ng/ml in whole blood for THC in the roadside surveys, it was found that 2 ng/ml THC in whole blood (3.8 ng/ml THC in serum) seems to cause impairment equivalent to 0.5 g/l BAC. Such equivalents could not be calculated for other drugs. It is not realistic to develop cut-off limits for all substances."

"We identified cohorts of individuals hospitalized in California from 1990 to 2005 with ICD-9 diagnoses of methamphetamine- (n = 74,170), alcohol- (n = 592,406), opioids- (n = 68,066), cannabis- (n = 47,048), cocaine- (n = 48,949), or polydrug-related disorders (n = 411,175), and these groups were followed for up to 16 years. Age-, sex-, and race-adjusted standardized mortality rates (SMRs) for deaths due to MVAs were generated in relation to the California general population. Standardized MVA mortality ratios were elevated across all drug cohorts: alcohol (4.5, 95% CI, 4.1–4.9), cocaine (3.8, 95% CI, 2.3–5.3), opioids (2.8, 95% CI, 2.1–3.5), methamphetamine (2.6, 95% CI, 2–3.1), cannabis (2.3, 95% CI, 1.5–3.2) and polydrug (2.6, 95% CI, 2.4–2.9). Males and females had similar MVA SMRs."

"Cannabis use impairs cognitive, memory and psycho-motor performance in ways that may impair driving.¹⁰ Recent data suggest that approximately 5% of Canadian drivers/adults report driving after cannabis use in the past year.³⁹ Large-scale epidemiological studies using different methodologies (e.g., retrospective epidemiological and case control studies) have found that cannabis use acutely increases the risk of motor vehicle accident (MVA) involvement and fatal crashes among drivers.^40,41 Recent reviews have found the increase in risk to be approximately 1.5-3.0, an increase which is substantially lower, however, than that in alcohol-impaired drivers. The impairment from concurrent alcohol and cannabis use may be multiplicative, so individuals who drive under the influence of both drugs may be at higher risk for MVAs.⁴² An expert consensus view was that a THC concentration of 7-10 nanograms per millilitre in serum would produce impairment equivalent to that of 0.05% blood alcohol content (BAC). It was suggested that this level could serve as a 'per se' limit to define cannabis-impaired driving.⁴³ Current research suggests that acute impairment from cannabis typically clears 3-4 hours after use.⁴⁴

"This time span could be recommended to users as a minimum wait period before driving. The required wait before driving would need to be longer for higher doses, and would also vary on the basis of individual variation."

"This study of crash risk found a statistically significant increase in unadjusted crash risk for drivers who tested positive for use of illegal drugs (1.21 times), and THC specifically (1.25 times). However, analyses incorporating adjustments for age, gender, ethnicity, and alcohol concentration level did not show a significant increase in levels of crash risk associated with the presence of drugs. This finding indicates that these other variables (age, gender ethnicity and alcohol use) were highly correlated with drug use and account for much of the increased risk associated with the use of illegal drugs and with THC.

"This study found a statistically significant association between driver alcohol level and crash risk both before and after adjustment for demographic factors. These findings were generally consistent with similar analyses conducted in prior crash risk studies. Findings from this study indicate that crash risk grows exponentially with increasing BrAC. The study shows that at low levels of alcohol (e.g., 0.03 BrAC) the risk of crashing is increased by 20 percent, at moderate alcohol levels (0.05 BrAC) risk increases to double that of sober drivers, and at a higher level (0.10 BrAC) the risk increases to five and a half times. At a BrAC of 0.15, the risk is 12 times, and by BrACs of 0.20+ the risk is over 23 times higher."

"Conducting case-control studies to estimate the risk of crash involvement from drug use presents many difficulties. The first challenge has been getting reliable and accurate estimates of drug use. Many studies rely on self-report (which have obvious inherent problems) rather than actual measurement of THC in blood or oral fluid.
"Also, the method of selecting truly comparable control drivers in an unbiased fashion for the crash involved drivers has varied considerably. The more carefully controlled studies, that actually measured marijuana (THC) use by drivers rather than relying on self-report, and that had more actual control of covariates that could bias the results, generally show reduced risk estimates or no risk associated with marijuana use (Elvik, 2013)."

"The prevalence of drugs detected in cases was higher than in controls across the drug categories (Table 3). Marijuana, narcotics, stimulants, and depressants were each associated with a significantly increased risk of fatal crash involvement, with estimated odds ratios ranging from 1.83 for marijuana to 4.83 for depressants (Table 3). Polydrug use, defined as use of two or more non-alcohol drugs, was associated with a 3.4-fold increased risk of fatal crash involvement (Table 3).

"About one-fifth (20.5%) of the cases tested positive for alcohol and one or more drugs, compared with 2.2% of the controls. Relative to drivers who tested positive for neither alcohol nor drugs, the estimated odds of fatal crash involvement increased over 13 folds for those who were alcohol-positive but drug-negative, more than two folds for those who were alcohol-negative but drug-positive, and 23 folds for those who were positive for both alcohol and drugs (Table 4)."

"It is difficult to establish a relationship between a person's THC blood or plasma concentration and performance impairing effects. Concentrations of parent drug and metabolite are very dependent on pattern of use as well as dose. THC concentrations typically peak during the act of smoking, while peak 11-OH THC concentrations occur approximately 9-23 minutes after the start of smoking. Concentrations of both analytes decline rapidly and are often < 5 ng/mL at 3 hours. Significant THC concentrations (7 to 18 ng/mL) are noted following even a single puff or hit of a marijuana cigarette. Peak plasma THC concentrations ranged from 46-188 ng/mL in 6 subjects after they smoked 8.8 mg THC over 10 minutes. Chronic users can have mean plasma levels of THC-COOH of 45 ng/mL, 12 hours after use; corresponding THC levels are, however, less than 1 ng/mL. Following oral administration, THC concentrations peak at 1-3 hours and are lower than after smoking. Dronabinol and THC-COOH are present in equal concentrations in plasma and concentrations peak at approximately 2-4 hours after dosing.

"It is inadvisable to try and predict effects based on blood THC concentrations alone, and currently impossible to predict specific effects based on THC-COOH concentrations. It is possible for a person to be affected by marijuana use with concentrations of THC in their blood below the limit of detection of the method. Mathematical models have been developed to estimate the time of marijuana exposure within a 95% confidence interval. Knowing the elapsed time from marijuana exposure can then be used to predict impairment in concurrent cognitive and psychomotor effects based on data in the published literature."

"The SFST was mildly sensitive to the effects of cannabis alone. A dose of 400 ?g/kg body weight THC significantly increased the percentage of participants displaying impairments in OLS compared to baseline performance from 21 to 50 %. THC also increased percentage of individuals showing impairment on HGN from 0 to 15 %, relative to baseline, but this change only approached statistical significance. WAT [Walk And Turn] and the overall score on SFST did not discriminate between THC and baseline. These findings appear in line with previous studies that have reported a relation between impairment on the SFST and presence of THC in blood. A study that assessed which signs of the Drug Evaluation and Classification evaluations predicted various drug categories (including cannabis) at best showed that OLS [One-Leg Stand] contributed significantly to the prediction, but HGN [Horizontal Gaze Nystagmus] and WAT did not (Porath-Waller et al. 2009). Papafotiou et al. (2005a) assessed SFST performance in 40 healthy participants who received low and high doses of THC in a placebo-controlled study. On average, blood THC concentrations obtained after the highest dose were comparable to serum THC concentrations achieved in the present study after smoking cannabis. Yet, THC significantly affected performance on OLS, HGN, and WAT and appeared to be more prominent as compared to the current study. For example, in that study THC produced impairments on overall SFST performance in up to 50 % of the participants (Papafotiou et al. 2005a) but in only 30 % of the participants of the present study. These differences may be explained in terms of differences in cannabis use history. In the study by Papafotiou et al. (2005a), the reported frequency of cannabis use of the participants varied from once a week to once every 2–6 months. The present study however only included heavy cannabis users, who smoked cannabis on at least four occasions per week. Previous studies demonstrated that heavy cannabis users develop tolerance to the impairing effects of THC on neurocognitive measures (Hart et al. 2001; Ramaekers et al. 2011). It is likely that many of the participants who participated in the present study, in part or in total, developed tolerance to the impairing effects of THC as well. In such a scenario, the failure of the SFST to demonstrate robust effects of THC is not necessarily an indicator of poor sensitivity, but may reflect the chronic cannabis use of the participants."

"Methods Twenty heavy cannabis users (15 males and 5 females; mean age, 24.3 years) participated in a double-blind, placebo-controlled study assessing percentage of impaired individuals on the SFST and the sensitivity of two oral fluid devices. Participants received alcohol doses or alcohol placebo in combination with 400 ?g/kg body weight THC. We aimed to reach peak blood alcohol concentration values of 0.5 and 0.7 mg/mL.

"Results Cannabis was significantly related to performance on the one-leg stand (p00.037). Alcohol in combination with cannabis was significantly related to impairment on horizontal gaze nystagmus (p 00.029). The Dräger Drug Test® 5000 demonstrated a high sensitivity for THC, whereas the sensitivity of the Securetec Drugwipe® 5 was low.

"Conclusions SFST were mildly sensitive to impairment from cannabis in heavy users. Lack of sensitivity might be attributed to tolerance and time of testing. SFST were sensitive to both doses of alcohol. The Dräger Drug Test® 5000 appears to be a promising tool for detecting THC in oral fluid as far as correct THC detection is concerned."

"Using population-based data from 1985 to 2014, we found that, first, states that enacted MMLs during the study period had lower fatality rates compared with states without MMLs. Second, on average, traffic fatalities further decreased in states post-MML, with both immediate (sudden change in fatality rate after MML enactment) and gradual (change in rate trend after MML enactment) declines over time in those aged 25 to 44 years. Third, the association between MML and traffic fatalities varied considerably across states. Fourth, the presence of operational dispensaries was also associated with reductions in traffic fatalities in those aged 25 to 44 years.
"We found that, on average during the study period, MML states had lower traffic fatality rates than non-MML states. It is possible that this is related to lower levels of alcohol-impaired driving behavior in MML states. Evidence from the Behavioral Risk Factor Surveillance Systems data from 2000²⁷ and 2012²⁸ shows that states that have enacted MMLs, compared with non-MML states, had, on average, lower proportions or rates of drivers endorsing having driven after having too much to drink. In addition, other unmeasured characteristics, including strength of public health laws related to driving, infrastructure characteristics (e.g., high-technology roads), or quality of health care systems, may partially explain these findings."

"The NRS [National Roadside Survey] surveys reveal a decreasing trend in alcohol use from the first survey in 1973 to the most recent one in 2013–2014. Figure 1 shows the percentage of weekend nighttime drivers with BrACs across three categories: BrAC of .005 to .049 g/210 L; 2 BrACs of .050 to .079; and BrACs of .080 and higher. The surveys found a decline in each BrAC category. Further, there has been a large decrease in the percentage of drivers who were alcohol positive, from 35.9 percent in 1973 to 8.3 percent in 2013–2014. For BrACs of .08 and higher, there was a decrease from 7.5 percent in 1973 to 1.5 percent in 2013–2014, revealing an impressive 80 percent reduction in the percentage of alcohol-impaired drivers on the road on weekend nights. Also of importance is the decrease from 6.1 percent to 1.6 percent from 1973 to 2013–2014 for BrACs of .050 to .079 category."

"Overall, 23,591 (90.9%) of the 25,951 drivers who died within 1 hour of a crash in these 6 states underwent toxicological testing. Drivers who were tested for drugs were similar in crash circumstances to those who were not tested, but they appeared to be slightly younger (mean age = 39.4 (standard deviation, 19.4) years vs. 43.4 (standard deviation, 27.7) years), more likely to be male (77.7% vs. 75.8%), more likely to be involved in nighttime crashes (51.4% vs. 47.0%), and more likely to have been involved in a crash in the previous 3 years (15.7% vs. 13.9%) than those who were not tested.
"Of the 23,591 drivers tested, 39.7% were positive for alcohol, and 24.8% tested positive for other drugs. The prevalence of alcohol involvement was stable at approximately 39% from 1999 to 2010 (Z = ?1.4, P = 0.16). Alcohol involvement was more prevalent in men (43.6%) than in women (26.1%), but trends were stable for both sexes (Table 1). In contrast, the prevalence of nonalcohol drugs showed a statistically significant increasing trend over the study period, rising from 16.6% (95% confidence interval (CI): 14.8, 18.4) in 1999 to 28.3% (95% CI: 26.0, 30.7) in 2010 (Z = ?10.19, P < 0.0001). The prevalence rates of non-alcohol drugs and 2 or more nonalcohol drugs increased significantly over the study period in both sexes (Table 1). The prevalence of nonalcohol drug use increased significantly across all age groups (Figure 1)."

"The 2013–2014 study examined the use of drugs, focusing on drugs with the potential to impair driving skills, including over-the-counter, prescription, and illegal drugs. Participants were asked to provide an oral fluid and blood sample in addition to a breath sample. The oral fluid and blood samples were tested for the presence of a large number of potentially impairing drugs including cannabinoids, stimulants, sedatives, antidepressants, and narcotic analgesics. Not all drivers provided both an oral fluid and blood sample; some drivers provided just one sample but many provided both.
"The reader is cautioned that drug presence does not necessarily imply impairment. For many drug substances, drug presence can be detected after impairment that might affect driving has passed. For example, traces of marijuana use can be detected in blood samples several weeks after heavy chronic users stop ingestion. In this study, for marijuana, we tested only for THC (delta 9 tetrahydrocannabinol), the psychoactive substance in marijuana, and 11-OH-THC, its active metabolite. When marijuana is smoked or ingested, THC is absorbed into the blood stream and is distributed into areas of the body, including the brain. There are over 100 marijuana metabolites detectable in blood that research has not associated with the psychoactive effects of marijuana use. Whereas the impairment effects for various concentration levels of alcohol in the blood or breath are well understood, there is little evidence available to link concentrations of other drugs to driver performance."

"Based on the oral fluid results, more nighttime drivers (14.4%) were drug-positive then were daytime drivers (11.0%). Based on the blood test results which were administered only at nighttime, 13.8% of the drivers were drug-positive. Using the combined results of either or both oral fluid and blood tests, 16.3% of the nighttime drivers were drug-positive.
"The most commonly detected drugs were Marijuana (THC) at 8.6%, Cocaine at 3.9%, and Methamphetamine at 1.3% of nighttime drivers."

"The recently published 2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results reported the drug prevalence (detected by oral fluid and blood samples) in 7,719 weekend drivers who served as participants in the survey (Lacey et al., 2009). The prevalence of drugs in drivers tested during the daytime was 11%.1 Specifically, 5.8% tested positive for the category of illegal drugs, 4.8% for the medication category (i.e., prescription [Rx] and over-the-counter [OTC] medications), and 0.5% for the combined illegal and medication category. The nighttime survey results showed a prevalence of 14.4% for positive drug results. In this sample, 10.5% were positive for illegal drugs, 3% positive for the medication category, and 0.9% positive for the combined illegal and medication category. In addition, for those individuals who tested positive for illegal drugs (9.8%) the rate of those who also tested positive for alcohol was 28%. One of the major conclusions and recommendations of this study is that “further research is needed to determine the effect of drug prevalence on crash risk” (p.8)."

"In 2011, 9.4 million persons or 3.7 percent of the population aged 12 or older reported driving under the influence of illicit drugs during the past year. This was a decrease from the rate in 2010 (4.2 percent) and the rate in 2002 (4.7 percent). Across age groups, the rate of driving under the influence of illicit drugs in 2011 was highest among young adults aged 18 to 25 (11.6 percent); this rate for young adults in 2011 was lower than the rate in 2010 (12.7 percent). Additionally, the rate of driving under the influence of illicit drugs during the past year decreased among adults aged 26 or older (from 2.9 percent in 2010 to 2.4 percent in 2011)."

"When time trends of nonalcohol drugs were examined by drug class, the prevalence of narcotics tripled during the study period, increasing from 1.8% in 1999 (95% CI: 1.3, 2.6) to 5.4% (95% CI: 4.4, 6.8) in 2010 (Z = ?7.07, P < 0.0001, Figure 2), and the increase occurred in both sexes (Table 1). The prevalence of depressants (excluding alcohol) and other drugs also increased significantly over the study period (Z = ?4.54, P < 0.0001, and Z = ?2.61, P = 0.01, respectively). There was not a monotonic trend in the prevalence of stimulants during the study period (Figure 2). Overall, the prevalence of cannabinol nearly tripled over the study period, increasing from 4.2% (95% CI: 3.3, 5.2) in 1999 to 12.2% (95% CI: 10.6, 14.1) in 2010 (Z = ?13.63, P < 0.0001, Figure 2), and the upward trends in the prevalence of cannabinol were similar for men and women (Table 1). By the end of the study period, cannabinol became the most prevalent nonalcohol drug detected in fatally injured drivers (Figure 2). The prevalence of cannabinol increased significantly across age groups (Figure 3). The increase in the prevalence of cannabinol was most pronounced among fatally injured drivers less than 25 years of age (Figure 3)."

"Analyses of the oral fluid samples obtained from daytime drivers indicated an overall drug use prevalence of 11 percent, and for nighttime drivers, 14.4 percent (Table 19). This includes illegal, prescription, and over-the-counter drugs combined. This overall difference between day and night is statistically significant (p < .01).
"In examining the prevalence of drugs by class (Table 31), marijuana was identified in 3.9 percent of daytime drivers and 6.1 percent of nighttime drivers. Sedatives were found in 1.6 percent of daytime drivers and in 0.6 percent of nighttime drivers. Conversely, stimulants were found in 1.6 percent of daytime drivers but in 3.2 percent of nighttime drivers."

"The estimated odds ratios of fatal motor vehicle crashes associated with different drugs reported in this population-based case-control analysis are generally consistent with previous studies (Bedard et al., 2007; Brault et al., 2004; Laumon et al., 2005; Mathijssen and Houwing, 2005; Movig et al., 2004; Mura et al., 2003). For instance, in a case-control study conducted in the Netherlands, Movig et al. (2004) found that 11.8% of the drivers who were seriously injured in crashes and 6.0% of the drivers who were not involved in crashes tested positive for marijuana, yielding an odds ratio of 2.1 (95% CI: 1.1, 4.0). A study of drivers aged 18 to 69 years of age in Norway revealed that the incidence of crashes was more than two times higher for individuals the week after benzodiazepine-like hypnotics were dispensed compared to unexposed person time (Gustavsen et al., 2008). A meta-analysis of epidemiological studies showed that motor vehicle crash risk for benzodiazepine users was 60–80% higher than for nonusers (Dassanayake et al., 2011). It is also evident that crash risk in drivers with depression is particularly high at the initiation of antidepressant treatment and when antidepressant treatment regimen changes (Orriols et al., 2012)."

"In the present study, the overall percentage of drivers who tested positive for ketamine in a roadside oral fluid test was 2.6%. This percentage was higher than that described by Gish et al. in samples collected at a music festival in southwest France (1.4% in 2017 and 0.4% in 2019) [17], but also higher than the prevalence previously reported in the driver population of other countries [18, 19, 20, 21] where the highest prevalence was found in Australia in 2012 (1.5%) [18]. While the nature of the musical event may partly explain the difference observed in our study (rave party) with that of Gish et al. (rock festival), regional disparities in illicit drug use may exist. The percentage of ketamine positivity observed in our study during the last 7 months of 2020 was of the same order as those previously described, but cannot be compared to earlier data from our region since ketamine in oral fluid samples was unfortunately not tested in our laboratory before May 2020. However, we report a significant increase in ketamine use in 2021 compared to 2020, which is consistent with the study led by the French Addictovigilance Network, where the number of ketamine users with a substance use disorder in the OPPIDUM programme increased 2.5‐fold between 2012 and 2021 [9]. In this study, we also observed a higher number of ketamine‐positive cases in the summer and autumn. This observation is consistent with the evolution of ketamine use from a confidential one, at high doses in free parties and in the party scene in the 2000s, to a large one, in a ‘techno and electro’ festive context during festivals, in bars or in clubs [22, 23, 24]. It is now more common to consume ketamine in trace amounts, as consumers are no longer looking for hallucinogenic properties, but rather for a more moderate stimulant effect. The higher consumption of ketamine during the summer period reported in the present study is consistent with those reported in Toulouse (southwestern France) since 2017, in relation to a diffusion of this substance from alternative parties to electronic parties. Indeed, the latter are more frequent in the summer period and the larger number of participants in outdoor events is also a source of increased diversity and availability of substances [25]. In addition to summer and autumn, a marginal use of ketamine in winter was observed in our region during a rave party in January 2023. The same situation was observed in Toulouse during techno‐house and industrial techno parties in 2018, underlining the trivialized consumption of ketamine by techno partygoers. In this study, we cannot exclude the possibility that drivers attending supervised events, such as music festivals, which require prior authorization from the prefecture and are associated with more pronounced and systematic control, were included, thus introducing a possible bias. On the contrary, it should be noted that the use of the DrugWipe®5S as a roadside screening test in accordance with French regulations did not allow for the direct detection of ketamine [11]. This may have introduced a potential underestimation and selection bias among drivers tested for drug use, but this may be limited as 95.4% of the ketamine‐positive drivers identified in this study were polydrug users, mainly using COC, THC and AMP. Interestingly, this problem could be easily overcome by using some rapid oral fluid tests such as DrugWipe® 6S, Ora‐Check®, SalivaScreen®, OratectXP®, which are able to detect ketamine at cut‐offs of 5 to 50 ng/mL for ketamine and 30 to 75 ng/mL for norketamine [26, 27]. Finally, among the ketamine users, we do not exclude the possibility of having included depressed persons using the antidepressant esketamine. Indeed, the dextrorotatory isomer of ketamine (s‐ketamine) cannot be differentiated from ketamine by our non‐chiral chromatography method, whereas major depression has been reported to favour drug of abuse consumption [28]. However, the study by Baudot et al. showed that only a small number of patients are treated with esketamine in France [29], limiting the bias introduced by our analytical method."

"The 2007 NRS found a dramatic decline in the number of drinking drivers with BACs [Blood Alcohol Content] at or above the current legal limit of 0.08 g/dL* on weekend nights compared to previous surveys (Figure 1). In 1973, 7.5% of drivers NHTSA’s National Center for Statistics and Analysis had BACs at or above 0.08 g/dL. In 2007, there were only 2.2% of drivers with a BAC at or above the current legal limit. This represents a decline of 71% in the percentage of alcohol-impaired drivers on the road on weekend nights. Similar declines were found at other BAC levels. For example, the percentage of drinking drivers (any positive BAC) declined almost as much over this time period, but one cannot infer impairment at very low BACs."

"The comparison of the BAC [Blood Alcohol Content] test results from the four NRS [National Roadside Survey] studies suggests that, during the most recent decade, there continues to be a downward trend in the proportion of drivers with positive BACs²¹ on U.S. roads on weekend nights, from 36.1 percent in 1973, 25.9 percent in 1986, 16.9 percent in 1996, to a low of 12.4 percent in 2007. Though the response rates we achieved in the 2007 NRS are somewhat lower than NRS studies conducted in previous decades, they are still well above those obtained with Random Digit-Dialing telephone surveys, which currently are typically lower than 50 percent (Battaglia, Frankel, & Link, 2008). We also obtained PAS [Passive Alcohol Sensor] readings from well over 90 percent of these drivers who did not provide actual breath tests. This allowed us to impute BAC values for nearly every driver eligible for an interview. Since the 1996 NRS, the proportion of drivers with BACs .08 g/dL or above on the road has declined substantially from 4.3 percent in 1996 to 2.2 percent in 2007.
"Across the four NRS surveys (1973, 1986, 1996, and 2007), reductions in .08 g/dL and above drivers in the NRS have been generally paralleled by reductions in fatal alcohol-related crashes involving drivers with a BAC of .08 or greater. The reduction in nighttime NRS drivers with BAC .08 g/dL or above from 1996 to 2007 appears to be greater than the reduction in FARS [Fatality Analysis Reporting System] from 1996 to 2007. Results from the FARS data analyses show that drivers with a .08 g/dL or higher in fatal crashes changed from 33.1 percent in 1996 to 32 percent in 2007, whereas the percentage of drivers at or above .08 in the 1996 NRS was 4.3 and fell to 2.2 in 2007. This is a departure from the trends observed from past NRS studies in that, from 1973 to 1986 and then from 1986 to 1996, the same pattern of reductions was observed both in fatal crashes and in the NRS."

"The percentage of male drivers with a BAC over the current legal limit of 0.08 g/dL was 42% higher than the percentage of female drivers with illegal BACs (Figure 2). A regression analysis showed that males were significantly more likely to have illegal BACs (p < .01). Over 2% of the weekend nighttime drivers had illegal BACs (>0.08g/dL) while only 0.1% of daytime drivers had illegal BACs."

"Roadside surveys conducted in 13 countries across Europe, in which blood or oral fluid samples from 50 000 drivers were analysed, revealed that alcohol was present in 3.48 %, illicit drugs in 1.90 %, medicines in 1.36 %, combinations of drugs or medicines in 0.39 % and alcohol combined with drugs or medicines in 0.37 %. However, there were large differences among the mean values in the regions of northern, eastern, southern and western Europe. Although the absolute numbers were quite low, the prevalence of alcohol, cocaine, cannabis and combined substance use was higher in southern Europe, and to some extent in western Europe, than in the other two regions, whereas medicinal opioids and ‘z-drugs’, such as zopiclone and zolpidem, were detected more in northern Europe."

"Studies of hospitalised, seriously injured car drivers were conducted in six countries, and studies of car drivers killed in accidents took place in four countries. Among the injured or killed drivers, the most commonly consumed substance was alcohol alone, followed by alcohol combined with another substance. The use of illicit drugs alone was not frequently detected. After alcohol, the most frequently found substance among injured drivers was tetrahydrocannabinol (THC) followed by benzodiazepines, whereas, among drivers killed in accidents, it was benzodiazepines."

"Using the above model of evaluation it can be seen that the DrugWipe 5 delivers the best results for sensitivity (91%) whilst also performing very highly in terms of specificity (95%). However the margins of error (95% confidence interval) displayed in Figure 43 show that this value could vary between 78-97%, this margin of error would seem to be due to the size of the study population (135 tests performed) since the device was only tested in Finland. The strong results for this device probably reflect largely on the device?s high performing individual amphetamines test in a country with a relatively high prevalence for amphetamines. However, this overall sensitivity is still higher than the individual sensitivity of the amphetamines test for DrugWipe 5 (87%) indicating that the device was successful in screening for other drugs. Both DrugTest 5000 and Rapid STAT also performed strongly in this evaluation both for sensitivity (85% and 82% respectively) and specificity (86% and 88% respectively), which is a reflection of their generally relatively good performance for each individual substance test. The sensitivity error margins are also somewhat narrower for these two devices that were tested on a greater number of subjects (220 and 342 tests performed respectively). The OrAlert device also performs at a high level of sensitivity (81%) in this evaluation, however the specificity is somewhat lower at 70% - which is the lowest score for any of the devices. The sensitivities of the other four devices included in the study range between 64% and 32%, which are quite low values. The specificities are, however, very high, or excellent, at between 93% and 100%. The relatively large error bars for the Oratect III device and BIOSENS can be attributed to the number of successful evaluations (58 and 25 respectively)."

"It is disturbing that the sensitivities of the cannabis and cocaine tests were all quite low, although further testing of the cocaine tests is desirable due to the low prevalences and the low concentrations encountered in this study. There are several countries in Central and Southern Europe for which these two substance classes are of special interest. On the other hand, it seems the sensitivities of the devices are generally better for amphetamines, a frequently encountered drug class among the DUI drivers in the Nordic countries. The suitability of the device for the intended national DUI population should also be considered, for example, PCP is rarely, if ever, found in Europe, therefore at the current time utilising a PCP test is unnecessary. Since the on-site tests are relatively expensive the suitability of all the individual substance tests incorporated in the device should be considered.
"The evaluation showed that none of the evaluated tests is on a desirable level (>80% for sensitivity, specificity and accuracy) for all of the separate tests that they comprised. However, there were tests that performed already on a promising level for one or more substance classes. The DrugTest 5000 had the best overall results. The next best device was Rapid STAT, which performed at a similar level, except for the cocaine test which was somewhat less sensitive. Clearly the best device in terms of sensitivity for amphetamines was the DrugWipe 5."

"Evidence-gathering technology for drugs is not as advanced in terms of ease of use and noninvasiveness as it is for alcohol. Until recently, no simple test police officers could administer to obtain an indication of drug use similar to the preliminary breath test for alcohol has been available. Rather, samples of urine or blood typically must be sent away for laboratory analysis to determine the presence of drugs and their quantification. Screening tests using urine, which can be used by officers in the police station, have been field tested by NHTSA. The technology is also developing for using saliva, sweat, and hair samples to detect drug use (Hersch, Crouch, & Cook, 2000).
"As said earlier, NHTSA has funded the Drug Evaluation and Classification (DEC) program, which equips specially trained officers, known as Drug Recognition Experts (DREs), to observe and record behavioral evidence of drug use to assess potential drug impairment among persons suspected of drug-impaired driving, and guide chemical testing and expert testimony for DUID trials. Currently, more than 40 States have officially adopted DEC programs to train DRE personnel."

"DrugTest 5000 screening results were evaluated against Quantisal confirmation data to determine TP [True Positive], TN [True Negative], FP [False Positive], FN [False Negative], diagnostic sensitivity and specificity, and efficiency at various cutoffs (Tables 1 and 2). When compared to THC alone, the diagnostic sensitivity and specificity and efficiency were 86.2%–90.7%, 75.0%–77.8%, and 84.8%– 87.9% at the 5-μg/L cutoff and 75.9%–92.7%, 76.0%–100.0%, and 78.8%– 86.4% at the 10-μg/L DrugTest 5000 cutoffs. Overall, the DrugTest 5000 performed better with the 5-μg/L screening cutoff, with diagnostic sensitivity and efficiency above the DRUID-recommended 80%. There were few FP and FN tests, and when they occurred, concentrations were at or near the confirmation cut-off. A limitation of this study was the inclusion of a small number of TN samples, only 6 –12 with the 5-μg/L DrugTest 5000 and 1- and 2-μg/L confirmation cutoffs, to adequately evaluate diagnostic specificity. On the basis of previous reports, more TN samples were expected over the 22-h collection period. Detection rates were highest and windows of detection were longest when we confirmed for THC alone (Fig. 1 and 2). However, the recent report of THC concentrations in OF following 3 h of passive exposure to cannabis smoke advocate for the inclusion of THCCOOH in confirmation criteria, because this analyte is not present in cannabis smoke and was not found in any OF [Oral Fluid] samples following passive exposure (18)."

"It is disturbing that the sensitivities of the cannabis and cocaine tests were all quite low, although further testing of the cocaine tests is desirable due to the low prevalences and the low concentrations encountered in this study. There are several countries in Central and Southern Europe for which these two substance classes are of special interest. On the other hand, it seems the sensitivities of the devices are generally better for amphetamines, a frequently encountered drug class among the DUI drivers in the Nordic countries. The suitability of the device for the intended national DUI population should also be considered, for example, PCP is rarely, if ever, found in Europe, therefore at the current time utilising a PCP test is unnecessary. Since the on-site tests are relatively expensive the suitability of all the individual substance tests incorporated in the device should be considered.
"The evaluation showed that none of the evaluated tests is on a desirable level (>80% for sensitivity, specificity and accuracy) for all of the separate tests that they comprised. However, there were tests that performed already on a promising level for one or more substance classes. The DrugTest 5000 had the best overall results. The next best device was Rapid STAT, which performed at a similar level, except for the cocaine test which was somewhat less sensitive. Clearly the best device in terms of sensitivity for amphetamines was the DrugWipe 5+."

"The results of this investigation provide further support to the possibility of using exhaled breath as a readily available specimen for drugs of abuse testing. There is a possibility that exhaled breath will develop into a new matrix for routine drug testing and present an alternative to already used matrices like urine, blood, oral fluid, sweat and hair. Each matrix may have its specific advantages and disadvantages. Since exhaled breath may be as easy to collect as in alcohol breath testing, it may present a new, more accessible matrix than blood at the roadside and elsewhere when the sampling procedure is an obstacle. We previously observed that exhaled breath methadone increases after intake [2]. If a correlation to blood concentration can be shown for exhaled breath levels, it may become a substitute matrix for monitoring impairment. One advantage of exhaled breath may be the detection of 6-AM, which is problematic in blood."

"Risk thresholds could be formulated only for THC which was the most prevalent illicit drug in the general driving population and in injured/killed drivers. The prevalence of THC across all countries that participated in DRUID is 1.37%. This is about one third of the alcohol prevalence. The epidemiological, the experimental and the meta-analytical approaches result in rather low risk estimations. Epidemiological case-control studies assess at maximum a 2.4-fold risk for injury, experimental studies and meta-analysis rank the risk between 0.5 and 2 times than that of sober driving. So THC seems to be much less impairing and risky than most of the other examined substances. Although a relationship between THC concentration and accident risk was found in the epidemiological studies, it was only possible to set an exact THC cut-off by a meta-analysis of experimental studies. Thereby it was found that the serum concentration of 3.8ng/mL THC (?2ng/mL in whole blood) causes the same amount of impairment as 0.5g/L alcohol. This value could be an empirical basis for a threshold discussion. The meta-analysis could also be used to define limits comparable to lower BAC levels."

"As with cannabis, alcohol use increased variability in lane position and headway (Casswell, 1979; Ramaekers et al., 2000; Smiley et al., 1981; Stein et al., 1983) but caused faster speeds (Casswell, 1977; Krueger & Vollrath, 2000; Peck et al., 1986; Smiley et al., 1987; Stein et al., 1983). Some studies also showed that alcohol use alone and in combination with cannabis affected visual search behavior (Lamers & Ramaekers, 2001; Moskowitz, Ziedman, & Sharma, 1976). Alcohol consumption combined with cannabis use also worsened driver performance relative to use of either substance alone. Lane position and headway variability were more exaggerated (Attwood et al., 1981; Ramaekers et al., 2000; Robbe, 1998) and speeds were faster (Peck et al., 1986).
"Both simulator and road studies showed that relative to alcohol use alone, participants who used cannabis alone or in combination with alcohol were more aware of their intoxication. Robbe (1998) found that participants who consumed 100 g/kg of cannabis rated their performance worse and the amount of effort required greater compared to those who consumed alcohol (0.05 BAC). Ramaekers et al. (2000) showed that cannabis use alone and in combination with alcohol consumption increased self-ratings of intoxication and decreased self-ratings of performance. Lamers and Ramaekers (2001) found that cannabis use alone (100 g/kg) and in combination with alcohol consumption resulted in lower ratings of alertness, greater perceptions of effort, and worse ratings of performance."

"Our primary analysis looked at the risk of a motor vehicle collision while under the influence of cannabis and included all nine studies (relating to 49 411 participants). The pooled risk of a motor vehicle collision while driving under the influence of cannabis was almost twice the risk while driving unimpaired (odds ratio 1.92 (95% confidence interval 1.35 to 2.73); P=0.0003); we noted heterogeneity among the individual study effects (I2=81%).
"We also assessed culpability and non-culpability studies separately and explored differences between motor vehicle collisions resulting in deaths and non-fatal injuries. Meta-analyses on subgroups of studies explored the potential effect of specific features related to study design and potential biases: case-control studies versus culpability studies, fatal collisions versus non-fatal collisions, and high quality studies versus medium quality studies (fig 3?).
"High quality studies had a pooled odds ratio that was higher than that for medium quality studies, although both results showed a significant association at the 0.05 level. Furthermore, case-control studies (2.79 (1.23 to 6.33); P=0.01) estimated the effect of cannabis use on crash risk to be higher than that estimated by culpability studies (1.65 (1.11 to 2.46); P=0.07). Studies of fatal collisions (2.10 (1.31 to 3.36); P=0.002) had a pooled odds ratio that was statistically significant, but studies of non-fatal collisions (1.74 (0.88 to 3.46); P=0.11) did not show significant results.
"In all studies assessing cannabis use in conjunction with alcohol, the estimated odds ratio for cannabis and alcohol combined was higher than for cannabis use alone, suggesting the presence of a synergistic effect."

"Although for the mobile phone conversation and cannabis studies the reaction times were slightly different, they were still comparable. The same visual stimulus was used and was presented in the same visual scene. When reaction times under each condition were compared with the baseline reaction times measured, alcohol gave a 12.5% increase in reaction times, cannabis a 21% increase, a hands-free mobile phone conversation increased reaction times by 26.5%, texting by 37.4%, using a smartphone for social networking by 37.6% and using a mobile phone for a hand-held mobile phone conversation increased reaction times by 45.9% compared to the baseline condition. Thus, using a smartphone for social networking resulted in a greater impairment to reaction times than alcohol, cannabis, hand held mobile phone conversations and texting, but less than a hand held mobile conversation."

"Absorption is slower following the oral route of administration with lower, more delayed peak THC levels. Bioavailability is reduced following oral ingestion due to extensive first pass metabolism. Smoking marijuana results in rapid absorption with peak THC plasma concentrations occurring prior to the end of smoking. Concentrations vary depending on the potency of marijuana and the manner in which the drug is smoked, however, peak plasma concentrations of 100-200 ng/mL are routinely encountered. Plasma THC concentrations generally fall below 5 ng/mL less than 3 hours after smoking. THC is highly lipid soluble, and plasma and urinary elimination half-lives are best estimated at 3-4 days, where the rate-limiting step is the slow redistribution to plasma of THC sequestered in the tissues. Shorter half-lives are generally reported due to limited collection intervals and less sensitive analytical methods. Plasma THC concentrations in occasional users rapidly fall below limits of quantitation within 8 to 12 h. THC is rapidly and extensively metabolized with very little THC being excreted unchanged from the body. THC is primarily metabolized to 11-hydroxy-THC which has equipotent psychoactivity. The 11-hydroxy-THC is then rapidly metabolized to the 11-nor-9-carboxy-THC (THC-COOH) which is not psychoactive. A majority of THC is excreted via the feces (~65%) with approximately 30% of the THC being eliminated in the urine as conjugated glucuronic acids and free THC hydroxylated metabolites."

"We found only limited evidence to support the claim that cannabis use increases accident risk. Participants who had driven under the influence of cannabis in the previous year appeared to be no more likely than drug-free drivers to report that they had had an accident in the previous 12 months. Prima facie, this would seem to suggest that cannabis-intoxicated driving is not a risk factor for non-fatal accidents. In this sense, the results would support those of Longo et al. (2000b) who found no relationship between recent cannabis use and driver culpability for non-fatal accidents."

"THC is the major psychoactive constituent of cannabis. Potency is dependent on THC concentration and is usually expressed as %THC per dry weight of material. Average THC concentration in marijuana is 1-5%, hashish 5-15%, and hashish oil ³ 20%. The form of marijuana known as sinsemilla is derived from the unpollinated female cannabis plant and is preferred for its high THC content (up to 17% THC). Recreational doses are highly variable and users often titer their own dose. A single intake of smoke from a pipe or joint is called a hit (approximately 1/20th of a gram). The lower the potency or THC content the more hits are needed to achieve the desired effects; 1-3 hits of high potency sinsemilla is typically enough to produce the desired effects. In terms of its psychoactive effect, a drop or two of hash oil on a cigarette is equal to a single “joint” of marijuana. Medicinally, the initial starting dose of Marinol® is 2.5 mg, twice daily."

"Cannabis use impairs cognitive, memory and psycho-motor performance in ways that may impair driving.¹⁰ Recent data suggest that approximately 5% of Canadian drivers/adults report driving after cannabis use in the past year.³⁹ Large-scale epidemiological studies using different methodologies (e.g., retrospective epidemiological and case control studies) have found that cannabis use acutely increases the risk of motor vehicle accident (MVA) involvement and fatal crashes among drivers.^40,41 Recent reviews have found the increase in risk to be approximately 1.5-3.0, an increase which is substantially lower, however, than that in alcohol-impaired drivers. The impairment from concurrent alcohol and cannabis use may be multiplicative, so individuals who drive under the influence of both drugs may be at higher risk for MVAs.⁴² An expert consensus view was that a THC concentration of 7-10 nanograms per millilitre in serum would produce impairment equivalent to that of 0.05% blood alcohol content (BAC). It was suggested that this level could serve as a 'per se' limit to define cannabis-impaired driving.⁴³ Current research suggests that acute impairment from cannabis typically clears 3-4 hours after use.⁴⁴
"This time span could be recommended to users as a minimum wait period before driving. The required wait before driving would need to be longer for higher doses, and would also vary on the basis of individual variation."

"A review of over a dozen of these [laboratory] experiments reveals three findings. First, after using marijuana, people drive more slowly. In addition, they increase the distance between their cars and the car in front of them. Third, they are less likely to attempt to pass other vehicles on the road. All of these practices can decrease the chance of crashes and certainly limit the probability of injury or death if an accident does occur. These three habits may explain the slightly lower risk of accidents that appears in the epidemiological studies. These results contrast dramatically to those found for alcohol. Alcohol intoxication often increases speed and passing while decreasing following distance, and markedly raises the chance of crashes.(632)"

"There is considerable evidence from laboratory studies that cannabis (marijuana) impairs reaction time, attention, tracking, hand-eye coordination, and concentration, although not all of these impairments were equally detected by all studies (Couper & Logan, 2004a; Heishman, Stitzer, & Yingling, 1989; Gieringer, 1988; Moskowitz, 1985). In reviewing the literature on marijuana, Smiley (1998) concluded that marijuana impairs performance in divided attention tasks (i.e., a poorer performance on subsidiary tasks). Jones et al. (2003) adds that Smiley’s finding is relevant to the multitasking essence of driving, in particular by making marijuana impaired drivers perhaps less able to handle unexpected events. Interestingly, there is also evidence showing that, unlike alcohol, marijuana enhances rather than mitigates the individual’s perception of impairment (Lamers & Ramaekers, 1999; Robbe & O'Hanlon, 1993; Perez-Reyes, Hicks, Bumberry, Jeffcoat, & Cook, 1988). Robbe and O'Hanlon (1993) reported that in laboratory conditions, drivers under the influence of marijuana were aware of their impairment, which led them to decrease speed, avoid passing other vehicles, and reduce other risk-taking behaviors. Such was not the case with alcohol; for the authors reported that alcohol-impaired drivers were generally not aware of impairment, and therefore did not adjust their driving accordingly."

"Cannabis is only considered a risk factor for traffic accidents if drivers operate vehicles after consuming the drug. Robbe (1994) found that 30% to 90% of his participants were willing to drive after consuming a typical dose of cannabis. This is consistent with a recent Australian survey in which more than 50% of users drove after consuming cannabis (Lenne, Fry, Dietze, & Rumbold, 2000). A self administered questionnaire given to 508 students in grades 10 to 13 in Ontario, Canada, found that 19.7% reported driving within an hour after using cannabis (Adlaf, Mann, & Paglia, 2003)."

"Participants receiving active marijuana decreased their speed more so than those receiving the placebo cigarette during a distracted section of the drive, An overall effect of marijuana was seen for the mean speed during the distracted driving (PASAT [Paced Auditory Serial-Addition Test] section), While no other changes in driving performance were found, marijuana appeared to hinder practice effects on the PASAT task, suggesting individuals may not be able to adequately use information and experience previously acquired while under the influence of marijuana, While only minimal differences in driving performance were found, this failure to benefit from prior practice may be detrimental to driving performance. Research has shown that graduated driver's licensing programs in which participants receive more on the road training results in a decrease in fatal crashes in 16-year-olds (Baker, Chen & Li 2006), If marijuana indeed impairs one's ability to use prior experience to improve performance, this will likely impair driving under pretrained conditions (e,g,, steering into a skid, allowing increased stopping time on slippery roads, etc)."

"The present study's subtle finding of decreased speed under the influence of acute marijuana is generally consistent with the literature, which has found that marijuana's effects on driving can be subtle. In Berghaus's review of the literature prior to 1995, 45% of driving simulator studies showed no impairment from marijuana within the first hour after use (Berghaus, Scheer & Schmidt 1995), More cautious driving behaviors were found in several studies (Lamers & Ramaekers 2001; Stein et al, 1983; Ellingstad, McFarling & Struckman 1973; Rafaelsen, Bech & Rafaelsen 1973; Dott 1972), while an increased reaction time for stopping was the most common finding (Liguori, Gatto & Robinson 1998; Rafaelsen, Bech & Rafaelsen 1973), Moskowitz, Ziedman and Sharma (1976) also found slowed reaction times for a visual choice-reaction time task administered while driving and Smiley, Moskowitz and Zeidman (1981) found increased variability in velocity and lateral position while following curves and while controlling the car in gusts of wind with a high dose of marijuana (200 mcg/kg THC) but not with a lower dose (100 mcg/kg THC), They also found an increase in variability of headway and lateral position while following other cars."

"The decreased speed during the simulated drive could be interpreted as an attempt to compensate for perceived cognitive impairment, Alternatively, marijuana may not have affected decision making and judgment and the reduction in speed would improve safety margins, While the clinical significance of a 3% to 5% decrease in speed may be questioned, previous research suggests such a decrease will result in approximately a 7% decrease in all injuries and a 15% decrease in fatalities (Nilsson 1981), Use of an alternate task design in which subjects are requested to drive as quickly and as safely as possible rather than following a posted speed limit may provide more insight into compensatory strategies employed while driving under the influence of marijuana, Use of a more challenging road paradigm (e.g., icy or gravel roads) which capitalizes on the use of practice effects may aid in identifying differences in driving performance under the influence of marijuana, There was significant between-subject variability in driving measures and future studies would be further strengthened by using a within-subjects design."

"Epidemiological studies have been inconclusive regarding whether cannabis use causes an increased risk of motor vehicle accidents; in contrast, unanimity exists that alcohol use increases crash risk.³⁰ In tests using driving simulation, neurocognitive impairment varies in a dose-related fashion, and symptoms are more pronounced with highly automatic driving functions than with more complex tasks that require conscious control.³¹ Cannabis smokers tend to over-estimate their impairment and compensate effectively while driving by utilizing a variety of behavioral strategies."

"When compared to alcohol, cannabis is detected far less often in accident-involved drivers. Drummer et al. (2003) cited several studies and found that alcohol was detected in 12.5% to 79% of drivers involved in accidents. With regard to crash risk, a large study conducted by Borkenstein, Crowther, Shumate, Zeil and Zylman (1964) compared BAC in approximately 6,000 accident-involved drivers and 7,600 nonaccident controls. They determined the crash risk for each BAC by comparing the number of accident-involved drivers with detected levels of alcohol at each BAC to the number of nonaccident control drivers with the same BAC. They found that crash risk increased sharply as BAC increased. More specifically, at a BAC of 0.10, drivers were approximately five times more likely to be involved in an accident.
"Similar crash risk results were obtained when data for culpable drivers were evaluated. Drummer (1995) found that drivers with detected levels of alcohol were 7.6 times more likely to be culpable. Longo et al. (2000) showed that drivers who tested positive for alcohol were 8.0 times more culpable, and alcohol consumption in combination with cannabis use produced an odds ratio of 5.4. Similar results were also noted by Swann (2000) and Drummer et al. (2003)."

"Most of the research on cannabis use has been conducted under laboratory conditions. The literature reviews by Robbe (1994), Hall, Solowij, and Lemon (1994), Border and Norton (1996), and Solowij (1998) agreed that the most extensive effect of cannabis is to impair memory and attention. Additional deficits include problems with temporal processing, (complex) reaction times, and dynamic tracking. These conclusions are generally consistent with the psychopharmacological effects of cannabis mentioned above, including problems with attention, memory, motor coordination, and alertness.
"A meta-analysis by Krüger and Berghaus (1995) profiled the effects of cannabis and alcohol. They reviewed 197 published studies of alcohol and 60 studies of cannabis. Their analysis showed that 50% of the reported effects were significant at a BAC of 0.073 g/dl and a THC level of 11 ng/ml. This implies that if the legal BAC threshold for alcohol is 0.08 g/dl, the corresponding level of THC that would impair the same percentage of tests would be approximately 11 ng/ml."

"Several studies have examined cannabis use in driving simulator and on-road situations. The most comprehensive review was done by Smiley in 1986 and then again in 1999. Several trends are evident and can be described by three general performance characteristics:

"1. Cannabis increased variability of speed and headway as well as lane position (Attwood, Williams, McBurney, & Frecker, 1981; Ramaekers, Robbe, & O'Hanlon, 2000; Robbe, 1998; Sexton et al., 2000; Smiley, Moskowitz, & Zeidman, 1981; Smiley, Noy, & Tostowaryk, 1987). This was more pronounced under high workload and unexpected conditions, such as curves and wind gusts.

"2. Cannabis increased the time needed to overtake another vehicle (Dott, 1972 [as cited in Smiley, 1986]) and delayed responses to both secondary and tracking tasks (Casswell, 1977; Moskowitz, Hulbert, & McGlothlin,
1976; Sexton et al., 2000; Smiley et al., 1981).

"3. Cannabis resulted in fewer attempts to overtake another vehicle(Dott, 1972) and larger distances required to pass (Ellingstad et al., 1973 [as cited in Smiley, 1986]). Evidence of increased caution also included slower speeds (Casswell, 1977; Hansteen, Miller, Lonero, Reid, & Jones, 1976; Krueger & Vollrath, 2000; Peck, Biasotti, Boland, Mallory, & Reeve, 1986; Sexton et al., 2000; Smiley et al., 1981; Stein, Allen, Cook, & Karl, 1983) and larger headways (Robbe, 1998; Smiley et al., 1987)."

"Both simulator and road studies showed that relative to alcohol use alone, participants who used cannabis alone or in combination with alcohol were more aware of their intoxication. Robbe (1998) found that participants who consumed 100 g/kg of cannabis rated their performance worse and the amount of effort required greater compared to those who consumed alcohol (0.05 BAC). Ramaekers et al. (2000) showed that cannabis use alone and in combination with alcohol consumption increased self-ratings of intoxication and decreased self-ratings of performance. Lamers and Ramaekers (2001) found that cannabis use alone (100 g/kg) and in combination with alcohol consumption resulted in lower ratings of alertness, greater perceptions of effort, and worse ratings of performance."

"Both Australian studies suggest cannabis may actually reduce the responsibility rate and lower crash risk. Put another way, cannabis consumption either increases driving ability or, more likely, drivers who use cannabis make adjustments in driving style to compensate for any loss of skill (Drummer, 1995). This is consistent with simulator and road studies that show drivers who consumed cannabis slowed down and drove more cautiously (see Ward & Dye, 1999; Smiley, 1999. This compensation could help reduce the probability of being at fault in a motor vehicle accident since drivers have more time to respond and avoid a collision. However, it must be noted that any behavioral compensation may not be sufficient to cope with the reduced safety margin resulting from the impairment of driver functioning and capacity."

"Another paradigm used to assess crash risk is to use cross-sectional surveys of reported nonfatal accidents that can be related to the presence of risk factors, such as alcohol and cannabis consumption. Such a methodology was employed in a provocative dissertation by Laixuthai (1994). This study used data from two large surveys that were nationally representative of high school students in the United States during 1982 and 1989. Results showed that cannabis use was negatively correlated with nonfatal accidents, but these results can be attributed to changes in the amount of alcohol consumed. More specifically, the decriminalization of cannabis and the subsequent reduction in penalty cost, as well as a reduced purchase price of cannabis, made cannabis more appealing and affordable for young consumers. This resulted in more cannabis use, which substituted for alcohol consumption, leading to less frequent and less heavy drinking. The reduction in the amount of alcohol consumed resulted in fewer nonfatal accidents."

"The following conclusions can be drawn:
"• It is advised to establish legal risk thresholds for illicit drugs on the basis of solid empirical data, i.e. experimental and epidemiological results. If the empirical basis is too weak, pharmacokinetic substance characteristics could help to define a lower effect limit.
"• The risk thresholds for drugs should reflect the impairment equal to that of 0.5g/L BAC or to any other legally relevant BAC.
"• The risk threshold for THC should be set adequate to 0.5 BAC at 3.8 ng/mL serum plus an added value for measurement error and confidence interval.
"• For all other illicit drugs a zero-tolerance should be implemented, as the empirical database does not allow a definition of risk thresholds yet. In order to determine the limit of effect, all information regarding the drug effects and its pharmacokinetics should be considered by national expert teams. Those teams could use the comprehensive data provided by DRUID. Thereby it could be avoided that further development of the analyzing methods leads to a constant decline of the limits of quantification."

"Any threshold discussion should address the question if the DRUID approach to determine risk threshold as equivalents to 0.5g/L alcohol is feasible. From a scientific point of view it can only be justified to accept the same risk for all psychoactive substances (including alcohol). From a political point of view the determination of risk thresholds as equivalents to 0.5g/L alcohol might be questionable, because a BAC of 0.5g/L is not a legal limit in all European countries. Some Member States have lower alcohol limits and therefore risk threshold calculations for THC would have to be adapted accordingly. Besides, in European countries in which presently a certain risk is accepted, a discussion continues concerning alcohol zero tolerance approach."

"Drug per se laws are not quite analogous to the alcohol impaired-driving per se laws now in effect in every State make it illegal to operate a motor vehicle with a blood alcohol concentration (BAC) of .08 grams per deciliter or greater. Alcohol-impaired driving per se laws are based on evidence that all drivers are impaired at .08 BAC. Drug per se laws are more analogous to zero-tolerance laws that make it illegal to drive with certain drugs in the system."

"According to a European study, the prevalence in the Netherlands of the use of alcohol by car drivers is 2.2%, compared to 3.5% average in Europe. The use of cannabis by car drivers (1.7%) is above the European average of 1.3% (SWOV factsheet 2011). According to the Road Traffic Act it is forbidden to drive under the influence of a (illegal) substance affecting one's driving ability. The Ministers of Security and Justice and Transport are preparing a bill to change this Act in order to be better able to detect these drivers. Part of the bill is to give police investigators the authority to use an oral fluid screener as pre-selection method to detect drug use of traffic participants. The legal evidence will remain a blood test. The use of GHB is only detectable with a blood test. Like with driving under the influence of alcohol, threshold values will be defined for driving under the influence of drugs (e.g. 50 microgram per litre for amphetamine and cocaine and 3 microgram per litre for THC). A special commission has proposed limiting blood values per drug in accordance with international practices. Because some substances are occurring in the body and measuring instruments are not sensitive enough, zero limits are not feasible. The present bill uses behaviour-related limits, meaning that a limit is set above which driving skills are affected. There are fewer traffic casualties due to the use of drugs and medicines than to alcohol consumption (T.K. 29398-236; T.K. 32859-3; TK32859-7)."

"According to a survey of State motor vehicle agencies and a review of State statutes conducted for this study, all 50 States and the District of Columbia have laws that permit the State motor vehicle agency and/or the courts to withdraw driving privileges for at least some non-driving reasons. Common non-driving reasons for suspension include: failure to comply with a child support order; failure to maintain proper insurance; failure to appear in court to satisfy a summons; fraudulent application for driver’s license or vehicle registration documents; altered or unlawful use of a driver’s license; alcohol and drug-related offenses by minors other than DUI; convictions for drug-related offenses other than DUI; and failure to pay a motor vehicle and/or court fines, fees, and surcharges Other less common non-driving reasons for suspension include: truancy; fuel theft; delinquent conduct by a minor; use of fictitious license plates, registration, or inspection sticker; failure to appear in court to satisfy a parking ticket; making terrorist threats; graffiti; failure to register as a sex offender; and attempting to purchase tobacco by a minor."