Marie Claude Ouimet

Decreased vigilance associated with drowsiness is a major cause of motor vehicle crashes, but its physiological characterization and detection remain difficult due to behavioral and environmental confounding factors. This study presents an original experimental framework combining a highly controlled sleep-deprivation protocol, repeated driving simulations, and a machine-learning-based heart rate variability (HRV) analysis to study the physiological and behavioral changes in vigilance during a prolonged period of wakefulness while driving. Twelve healthy young adults participated in a 30-h sleep-deprivation constant routine protocol that included driving simulations every two hours, with data collection: electrocardiography (ECG), subjective ratings of drowsiness, psychomotor vigilance test, and driving performance. The collected data was separated into two clearly identifiable vigilance states, a “Rested” and a “Tired” state, respectively, for the first and last driving sessions, of the protocol. Heart rate variability (HRV) features were extracted from ECG recordings, statistically analyzed, and submitted into supervised machine learning classifiers using participant-independent validation to assess their ability to distinguish between two experimentally defined states of vigilance. The accuracy of state separation was verified based on significant alterations observed in drowsiness ratings and psychomotor performance in the Tired compared to the Rested state. The variability in driving behavior, an indicator of impaired driving ability, increased significantly from the Rested compared to the Tired state. Several HRV features revealed significant differences between Rested and Tired states, with effect sizes ranging from moderate to large, observed for several metrics. Participant-independent machine learning analysis, namely Leave-One-Subject-Out Cross-Validation (LOSO-CV), showed that HRV metrics enable reliable discrimination between vigilance states, with all classifiers evaluated achieving average accuracy greater than 85%. This pilot study demonstrated that the proposed experimental framework, by reducing the major behavioral and environmental confounding factors, can generate two distinct states of vigilance at the physiological and behavioral levels, enabling reliable separation of experimental data, independent of any additional ground truths. The states separated by the framework enable the detection of decreased driving performance and efficiently label HRV data for vigilance classification. Nevertheless, the findings should be interpreted within the context of a pilot study conducted with a small cohort of healthy young adults.

Introduction In Canada, alcohol-impaired driving is a persistent public health concern in need of effective community-based prevention strategies. This study examined the association between the number of rides offered by a safe-ride program in the province of Quebec every December and alcohol-related injury crashes during the 2000–2019 period. Method Safe-ride programs in four cities were examined (Montreal, Quebec, Sherbrooke and Trois-Rivières) using an ecological approach. The data set was structured as a balanced cross-sectional time series. Random-effects negative binomial regression modelled the relationship between the number of rides provided by the safe-ride program and night-time alcohol-related crashes involving serious injuries and fatalities, with individual city population as an offset variable. Results The median number of night-time alcohol-related crashes for the months of December for the 2000–2019 period was 3.0 (IQR=1.5–4.5). The median number of rides offered was 16 894 (IQR=15 586–18 391). The association between the number of rides provided by the safe-ride program and night-time alcohol-related crashes (IRR=1.0002; 95% CI 0.9999, 1.0005) was not significant. Conclusion The role of the number of rides provided by the safe-ride program in reducing night-time alcohol-related crashes was inconclusive. Specific program features may influence the findings. Future research is needed to understand the specific characteristics of safe-ride programs that could influence their putative benefits.

Introduction Understanding the impact of non-pharmaceutical COVID-19 interventions (NPIs) on road safety has become increasingly important to uncover the unintended consequences of the pandemic. This study explores how NPIs influenced alcohol-related and speed-related traffic collisions, including fatalities and serious injuries, in five cities of the province of Québec, Canada: Montréal, Québec, Laval, Longueuil and Sherbrooke. Methods We performed Poisson interrupted time-series analyses using daily traffic fatality and injury data from 2015 to 2022, to assess the change in rate expressed per 10 000 population. A Québec COVID-19 NPIs Index was applied, incorporating 58 interventions enacted from March 2020 to March 2022 in these cities. We accounted for weather conditions and seasonal patterns and divided the pandemic period into four semesters to better understand changes over time. Results The analysis revealed a nuanced interaction between NPIs and road safety. Alcohol-related injuries decreased during stringent NPIs, particularly in Montréal, Québec city and Longueuil. In contrast, the effects on speed-related incidents were mixed, with Montréal and Laval, showing increases and the other three cities displaying no meaningful changes across the four semesters. Conclusions These findings highlight the necessity for ad hoc road safety strategies that address specific patterns of alcohol consumption and speeding risks during future pandemic-related disruptions.

Forward collision warning systems (FCWSs) monitor the road ahead and warn drivers when the time to collision reaches a certain threshold. Using a driving simulator, this study compared the effects of FCWSs between novice drivers (unlicensed drivers) and experienced drivers (holding a driving license for at least four years) on near-collision events, as well as visual and driving behaviors. The experimental drives lasted about six hours spread over six consecutive weeks. Visual behaviors (e.g., mean number of fixations) and driving behaviors (e.g., braking reaction times) were collected during unprovoked near-collision events occurring during a car-following task, with (FCWS group) or without FCWS (No Automation group). FCWS presence reduced the number of near-collision events drastically and enhanced visual behaviors during those events. Unexpectedly, brake reaction times were observed to be significantly longer with FCWS, suggesting a cognitive cost associated with the warning process. Still, the FCWS showed a slight safety benefit for novice drivers attributed to the assistance provided for the situation analysis. Outside the warning events, FCWS presence also impacted car-following behaviors. Drivers took an extra safety margin, possibly to prevent incidental triggering of warnings. The data enlighten the nature of the cognitive processes associated with FCWSs. Altogether, the findings support the general efficiency of FCWSs observed through a massive reduction in the number of near-collision events and point toward the need for further investigations.

La consommation d’alcool est liée à environ 30 % des collisions routières mortelles. Dans plusieurs juridictions, des programmes d’évaluation et de traitement de la consommation d’alcool chez les contrevenants sont mis en place afin de réduire leur consommation et leur récidive. De par sa forme brève, l’entretien motivationnel (EM) suscite l’intérêt du milieu clinique. Cette revue systématique de la documentation scientifique examine l’efficacité de l’EM dans la prévention secondaire et tertiaire de la conduite avec les capacités affaiblies par l’alcool (CCA) chez les contrevenants et chez les patients recrutés à la suite d’une collision routière, notamment chez les jeunes. La recherche de la documentation dans les banques de données CINAHL, MEDLINE, PsychINFO et PubMed a couvert la période de 1983 à 2014. Elle a permis d’identifier 11 essais contrôlés avec répartition aléatoire des participants dans les groupes expérimentaux ou témoins. Une évaluation des risques de biais a été effectuée à l’aide de la grille de la collaboration Cochrane. La disparité des résultats n’a pas permis le regroupement quantitatif des données. Bien que les études disponibles soient encore peu nombreuses (n = 6), les résultats sur l’efficacité de l’EM sont prometteurs chez les récidivistes et les patients recrutés en milieu hospitalier avec une consommation d’alcool problématique. De plus, quatre de ces études présentent des biais méthodologiques moyennement faibles ou faibles. Les résultats sont mixtes en ce qui a trait aux études (n = 5) portant sur les jeunes contrevenants et les contrevenants ayant commis une première infraction de CCA, sans consommation problématique d’alcool comme critère d’inclusion dans l’étude. Une seule de ces études présente des biais méthodologiques faibles. D’autres essais contrôlés avec répartition aléatoire, menés et rapportés selon les règles proposées par le Consolidated Standards of Reporting Trials (CONSORT) Statement, sont donc nécessaires afin de démontrer l’efficacité de l’EM dans la prévention secondaire et tertiaire de la CCA chez les jeunes contrevenants et les contrevenants à leur première infraction de CCA. Ils permettraient aussi de corroborer les résultats préliminaires obtenus auprès de récidivistes et de patients recrutés en milieu hospitalier.