BACKGROUND: There is a need for improved drug driving enforcement to promote greater driver compliance with drug driving laws. In Australia, Roadside Drug Testing (RDT) suffers from operational challenges that undermine its effectiveness in reducing drug driving.
OBJECTIVE: To identify potential improvements to RDT, this study investigated the extent to which drivers perceive RDT to be procedurally just and that the policing of drug driving and the associated laws are legitimate. These perceptions were then compared with those applying to Random Breath Testing (RBT) and examined in relation to their respective influence on intentions to drug and drink drive in the future.
METHODS: A sample of 1,483 licensed drivers from three Australian states completed an online survey.
RESULTS: Those participants who reported engaging in drug driving perceived RDT to be less procedurally just than non-drug drivers. Similarly, drug drivers perceived the police and associated drug driving laws to be less legitimate than non-drug drivers. Furthermore, drug drivers who had been tested at an RDT operation in the past perceived RDT to be less procedurally just and considered drug driving policing and laws to be less legitimate, compared with the corresponding perceptions of drink drivers who had been tested at an RBT operation. A regression analysis indicated that stronger intentions to drug drive in the future were associated with lower perceptions of police legitimacy and the legitimacy of drug driving laws, but not with the elements of procedural justice. However, follow-up analyses indicated that the influence of procedural justice on intentions was mediated by the two legitimacy variables, thus weakening its direct impact on intentions.
CONCLUSIONS: The results highlight the need for road safety authorities to enhance the perceived legitimacy of drug driving enforcement and associated laws. Changes to current police practices and/or drug-driving laws may also be needed to enhance the effectiveness of RDT.

UNASSIGNED: Using alcohol or psychoactive drugs before driving a motor vehicle may increase the risk of crash involvement, injury, and death. This is better documented for alcohol than for drugs. The aim of this study was to expand a previous case-control study on substance use and driver fatality by doubling the number of cases and controls, and hence improve the statistical power and enable the analysis of combined substance use.
UNASSIGNED: We collected data on alcohol and drug use from all 1197 drivers of cars and vans who were fatally injured in road traffic crashes in Norway between 2005 and 2020 (\'cases\') by analyzing blood samples or reviewing other information on substance use. We also collected data on alcohol and drug use among 17,219 drivers in random road traffic (\'controls\') by analyzing oral fluid samples. Substance use was converted to dichotomous variables (no use/use). We used unconditional logistic regression to estimate adjusted odds ratios (aORs) with 95% confidence intervals (CIs) of driver fatality for mutually exclusive substance groups, adjusted for sex, age, geographic region, urban centrality class, and time interval of the week.
UNASSIGNED: Compared to no substance use, the aOR (95% CI) for driver fatality was for alcohol 91 (61-137), stimulants (primarily amphetamines) aOR 22 (9-56), benzodiazepines and z-hypnotics (BZDs) aOR 4.0 (2.7-5.9), tetrahydrocannabinol (THC) aOR 3.4 (1.7-6.7), and opioids aOR 1.4 (0.4-4.9). The aOR for any polysubstance use was 168 (96-297). The combinations of BZDs with stimulants or THC were associated with markedly higher aORs for driver fatality than the use of single substance groups.
UNASSIGNED: Alcohol and polysubstance use are the most important predictors of fatal injury, followed by stimulants.

OBJECTIVE: The aim of the present study was to investigate the relationship between blood concentrations of four different drug classes; ethanol, benzodiazepines, amphetamines and tetrahydrocannabinol (THC) and driver impairment as assessed by a clinical test of impairment (CTI).
METHODS: Data was retrieved from a national database on CTI assessments and accompanying blood drug concentrations from apprehended drivers. All drug concentrations in blood were quantified using Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS), and compared to the results of the CTI which were categorized as either \"not impaired\", \"mildly impaired\", \"moderately impaired\", or \"considerably impaired\".
RESULTS: A total number of 15 514 individual mono drug-cases collected over 9 years was included. 89 % were men and the median age was 34 years. In addition, 3 684 individual cases with similar age and gender distribution where no drugs were detected, were included as a reference group. For ethanol and benzodiazepines the percentage of clinically impaired cases increased markedly from lower to higher concentration windows, from 60 % to 97 % for ethanol and from 38 % to 76 % for benzodiazepines. The corresponding increase for amphetamines and THC was modest, from 43 % to 58 % for amphetamines and from 41 % to 55 % for THC. The correlation between drug concentration and degree of impairment was high for ethanol (Spearman´s rho=0.548, p<0.001) and relatively high for benzodiazepines (Spearman´s rho=0.377, p<0.001), but low for amphetamines (Spearman´s rho=0.078, p<0.001) and THC (Spearman´s rho=0.100, p<0.001).
CONCLUSIONS: The percentage of impaired drivers increased with increasing blood drug concentration for all four drug classes, most pronounced for ethanol and benzodiazepines and much less for amphetamines and THC. The median blood drug concentration increased with increasing magnitude of impairment for ethanol and benzodiazepines, while this was much less pronounced for amphetamines and THC. The ranges of drug concentrations, however, were wide for all four drug classes in all impairment categories as assessed by individual clinical examination.

OBJECTIVE: To examine the relationship between schizophrenia, antipsychotic medication adherence and driver responsibility for motor vehicle crash.
METHODS: Retrospective observational cohort study using 20 years of population-based administrative health and driving data.
METHODS: British Columbia, Canada.
METHODS: Licensed drivers who were involved in a police-attended motor vehicle crash in British Columbia over a 17-year study interval (2000-16).
METHODS: Incident schizophrenia was identified using hospitalisation and physician services data. Antipsychotic adherence was estimated using prescription fill data to calculate the \'medication possession ratio\' (MPR) in the 30 days prior to crash.
METHODS: We deemed drivers \'responsible\' or \'non-responsible\' for their crash by applying a validated scoring tool to police-reported crash data. We used logistic regression to evaluate the association between crash responsibility and exposures of interest.
RESULTS: Our cohort included 808 432 drivers involved in a police-attended crash and for whom crash responsibility could be established. In total, 1689 of the 2551 drivers with schizophrenia and 432 430 of the 805 881 drivers without schizophrenia were deemed responsible for their crash, corresponding to a significant association between schizophrenia and crash responsibility (66.2% vs 53.7%; adjusted OR (aOR), 1.67; 95% CI, 1.53 to 1.82; p<0.001). The magnitude of this association was modest relative to established crash risk factors (eg, learner license, age ≥65 years, impairment at time of crash). Among the 1833 drivers with schizophrenia, near-optimal antipsychotic adherence (MPR ≥0.8) in the 30 days prior to crash was not associated with lower crash responsibility (aOR, 1.04; 95% CI, 0.83 to 1.30; p=0.55).
CONCLUSIONS: Crash-involved drivers with schizophrenia are more likely to be responsible for their crash, but the magnitude of risk is similar to socially acceptable risk factors such as older age or possession of a learner license. Contemporary driving restrictions for individuals with schizophrenia appear to adequately mitigate road risks, suggesting more stringent driving restrictions are not warranted.

Using data from a developing country, the current study develops a copula-based joint modeling framework to study crash type and driver injury severity as two dimensions of the severity process. To be specific, a copula-based multinomial logit model (for crash type) and generalized ordered logit model (for driver severity) is estimated in the study. The data for our analysis is drawn from Bangladesh for the years of 2000 to 2015. Given the presence of multiple years of data, we develop a novel spline variable generation approach that facilitates easy testing of variation in parameters across time in crash type and severity components. A comprehensive set of independent variables including driver and vehicle characteristics, roadway attributes, environmental and weather information, and temporal factors are considered for the analysis. The model results identify several important variables (such as driving under the influence of drug and alcohol, speeding, vehicle type, maneuvering, vehicle fitness, location type, road class, road geometry, facility type, surface quality, time of the day, season, and light conditions) affecting crash type and severity while also highlighting the presence of temporal instability for a subset of parameters. The superior model performance was further highlighted by testing its performance using a holdout sample. Further, an elasticity exercise illustrates the influence of the exogenous variables on crash type and injury severity dimensions. The study findings can assist policy makers in adopting appropriate strategies to make roads safer in developing countries.

Alcohol-impaired driving is a formidable public health problem in the United States, claiming the lives of 37 individuals daily in alcohol-related crashes. Alcohol-impaired driving is affected by a multitude of interconnected factors, coupled with long delays between stakeholders\' actions and their impacts, which not only complicate policy-making but also increase the likelihood of unintended consequences. We developed a system dynamics simulation model of drinking and driving behaviors among adolescents and young adults. This was achieved through group model building sessions with a team of multidisciplinary subject matter experts, and a focused literature review. The model was calibrated with data series from multiple sources and replicated the historical trends for male and female individuals aged 15 to 24 from 1982 to 2020. We simulated the model under different scenarios to examine the impact of a wide range of interventions on alcohol-related crash fatalities. We found that interventions vary in terms of their effectiveness in reducing alcohol-related crash fatalities. In addition, although some interventions reduce alcohol-related crash fatalities, some may increase the number of drinkers who drive after drinking. Based on insights from simulation experiments, we combined three interventions and found that the combined strategy may reduce alcohol-related crash fatalities significantly without increasing the number of alcohol-impaired drivers on US roads. Nevertheless, related fatalities plateau over time despite the combined interventions, underscoring the need for new interventions for a sustained decline in alcohol-related crash deaths beyond a few decades. Finally, through model calibration we estimated time delays between actions and their consequences in the system which provide insights for policymakers and activists when designing strategies to reduce alcohol-related crash fatalities.

Drug-impaired driving is a growing problem in the U.S. States regulate drug-impaired driving in different ways. Some do not name specific drugs or amounts. Others do identify specific drugs and may regulate cannabis separately. We provide up-to-date information about these state laws.

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BACKGROUND: Worldwide, almost 1.2 million people drive under the influence of alcohol. However, early identification of alcohol use disorder (AUD) in subjects driving under the influence (DUI) of alcohol is seldom achieved.
OBJECTIVE: The aim of our retrospective study is to investigate the presence of AUD in a population of DUI subjects who had their driving license suspended, and if they were following a specific rehabilitation program.
RESULTS: 750 subjects were retrospectively enrolled from 2018 to 2021. DSM-V to assess AUD was used. Forty-eight (6.4%) subjects presented a diagnosis of AUD, after one month they showed a statistically significant reduction of carbohydrate-deficient transferrin (CDT) (p<0.0001); however, none were following a program for the treatment of AUD.
CONCLUSIONS: This outpatient setting may be considered a place of primary and secondary prevention where DUI subjects with a diagnosis of AUD may be entrusted to a Centre in order to follow rehabilitation treatment.

Drugged driving, the act of driving a vehicle under the influence of illicit drugs, by adolescents is a serious public health concern. Many factors contribute to this risk behavior, but much less is known regarding the role of parenting behaviors in this phenomenon. The purpose of this study was to examine specific parenting behaviors and their influence among a nationally representative sample of adolescents. Pooled data from the 2016-2019 National Survey on Drug Use and Health (NSDUH) among 17,520 adolescents ages 16-17 years old were analyzed. Differences were found in specific parenting behaviors and adolescent drugged/drunk driving, with parents not checking homework and not telling their children they are proud of them being the most influential. Findings from the present study may inform drugged driving prevention programs for parents and adolescents and enhance road safety interventions.