Reginald G. Smart’s research while affiliated with Centre for Addiction and Mental Health and other places

Background: Street racing has been identified as a significant public health concern, yet, little is known about the prevalence of this behaviour and its impact on collision risk. The current study was designed to address this dearth of knowledge by estimating the prevalence of street racing among the Ontario, Canada adult population, and examining its association to collision risk, controlling for demographics and other risk factors. Methods: Data were based on telephone interviews with 11,263 respondents derived from the 2009-2014 cycles of the CAMH Monitor, an ongoing cross-sectional survey of adults aged 18+ years. A hierarchical-entry binary logistic regression analysis of collision involvement in the previous 12 months was conducted and included measures of street racing, demographic characteristics (sex, age, marital status, education, income, region), driving exposure, and driving after use of alcohol and use of cannabis. Results: The prevalence of street racing was 0.9%. Based on univariate analyses, street racing was more prevalent among males (1.30%; p<.01) and those aged 18-25 years (2.61%; p<.001). Controlling for demographic characteristics, driving exposure, and driving after use of alcohol and use of cannabis, self-reported street racing significantly increased the odds of a crash (OR=5.23, p<.001). Discussion: A small but significant percentage of adult drivers in Ontario reported engaging in street racing. Even after adjusting for demographics, driving exposure, and driving after use of alcohol and use of cannabis, street racers faced more than a five-fold increase in the odds of a crash. Program and policy options must be considered to target this contingent.

This study reviews the existing literature concerning the association between depression and driver safety. Despite its increasing prevalence and its disabling impact on the world's population, there is surprisingly little research examining the impact of depressive disorders on driver performance. The review begins by examining the early studies of drivers deemed "mentally ill" and the subsequent epidemiological literature including case-control and prospective cohort studies of depressed drivers. The review also examines the more recent experimental investigations of depression and driver performance that have relied on naturalistic measurements and advanced driving simulation. The review concludes with a discussion of relevant issues (e.g., the impact of antidepressants on driver performance, suicide by driving), public policy implications of the research, and future research directions.

In 1998, Ontario passed legislation requiring that all drivers convicted of drinking and driving complete a remedial program, called Back on Track (BOT), before their driver’s licences could be reinstated. Based on an assessment, clients are assigned to complete either an “education” program or a “treatment” program, depending on levels of substance-related problems. Several months following completion of their program, participants complete a follow-up interview. We report substance use and related outcome measures on 22,277 BOT participants who completed follow-up between 2000 and 2005. Completion of BOT was associated with significant reductions in the frequency of alcohol and other drug use, number of drinks consumed per drinking occasion, total numbers of substance users, and negative consequences resulting from substance use. A large number of participants became “non-users” of various substances over the course of the program. These findings provide evidence that the remedial program has beneficial effects for participants in both the education and treatment components of BOT.

The relevance of cognition to anger and aggression has long been recognized in various psychosocial theories of anger and aggressive behaviour, but the contribution of cognition to driver anger and aggression has, until recently, been understudied. Anger and frustration on our roads and highways have become a common experience for motorists, and have significantly increased the risk of collisions, injuries, and fatalities. Within the recent growth of driving-related cognition research, one stream of investigation has focused on the application of attributional theory to driver anger and aggression. The current chapter will: (1) provide a basic description of attributional theory; (2) outline how attributional theory has contributed to our understanding of driver anger and aggression; (3) identify moderators of driving-related attributions, anger, and aggression, and; (4) outline potential future directions for this expanding area of research.

To gain an in-depth understanding of road rage incidents from the victims' perspectives. The data consisted of 30- to 60-min in-depth semistructured phone interviews with 29 self-identified victims of road rage. Twenty of the participants were in a motor vehicle, whereas 9 were pedestrians/cyclists. A qualitative Grounded Theory approach was used to inductively code and analyze the transcripts. Victims reported a correlation between their vulnerability and the perceived intensity/severity of the road rage incidents. The most vulnerable victims (pedestrians and cyclists) were the least likely to view road rage incidents as a random event and the most likely to feel that they were specifically targeted. Road rage incidents tended to evolve more rapidly when there was a greater real or perceived power imbalance between the victims and perpetrators. The most vulnerable victims were the most likely to have long-term physical and mental health consequences from the incident, and to significantly modify their behavior after the incident. Our analysis suggests that issues of victim vulnerability play a major role in determining the intensity, severity, and psychological consequences of road rage incidents. This seems particularly true for the most vulnerable of road users, such as pedestrians and cyclists.

No abstract available.

BACKGROUND: Individuals diagnosed with psychiatric disorder are at significantly increased risk of death and serious injury, to which motor vehicle collisions may be important contributors. This study examined the association between probable anxiety or mood disorder (AMD) and self-reported collision risk in a large representative sample of the adult population in Ontario. METHODS: Based on data from a regionally stratified general-population telephone survey of adults conducted from 2002 through 2009 (N=12,830), a logistic regression analysis examined self-reported collision involvement in the previous 12 months by measures of demographic characteristics, driving exposure, impaired driving behaviour, and probable AMD. RESULTS: Controlling for demographic variables and potential confounders, probable AMD was associated with an increased risk of collision involvement (OR=1.78, 95% CI=1.37, 2.31). LIMITATIONS: The use of self-report measures and the potential for bias created by groups excluded because they do not have access to landline telephones represent limitations to the current findings. Nevertheless, the benefits of a large sample derived from general population survey data far outweigh these limitations. CONCLUSIONS: The results suggest that the increased risk of injury and mortality associated with some psychiatric disorders is at least partially related to increased risk of collision involvement. The magnitude of the increase in risk associated with probable AMD is similar to that seen among individuals who drive after drinking or using cannabis. In view of these findings, more work to understand this risk among individuals experiencing probable AMD and how it can be avoided is necessary.

The current study assessed gender as a potential moderator of the relationship between self-reported driver aggression and various demographic variables, general and driving-related risk factors. Using data from a general-population telephone survey conducted from July 2002 through June 2005, two approaches to binary logistic regression were adopted. Based on the full dataset (n=6259), the initial analysis was a hierarchical-entry regression examining self-reported driver aggression in the last 12 months. All demographic variables (i.e., gender, age, income, education, marital status), general risk factors (i.e., psychological distress, binge drinking, cannabis use), and driving-related risk factors (i.e., driving exposure, stressful driving, exposure to busy roads, driving after drinking, driving after cannabis use) were entered in the first block, and all two-way interactions with gender were entered stepwise in the second block. The subsequent analysis involved dividing the sample by gender and conducting logistic regressions with main effects only for males (n=2921) and females (n=3338) separately. Although the prevalence of driver aggression in the current sample was slightly higher among males (38.5%) than females (32.9%), the difference was small, and gender did not enter as a significant predictor of driver aggression in the overall logistic regression. In that analysis, difficulty with social functioning and being older were associated with a reduced risk of driver aggression. Marital status and education were unrelated to aggression, and all other variables were associated with an increased risk of aggression. Gender was found to moderate the relationships between driver aggression and only three variables: income, psychological distress, and driving exposure. Separate analyses on the male and female sub-samples also found differences in the predictive value of income and driving exposure; however, the difference for psychological distress could not be detected using this separate regression approach. The secondary analysis also identified slight differences in the predictive value of four of the risk factors, where the odds ratios for both males and females were in the same direction but only one of the two was statistically significant. The results demonstrate the importance of conducting the gender analysis using both regression approaches. With few exceptions, factors that were predictive of driver aggression were generally the same for both male and female drivers.