Driving Aggression and Anxiety: Intersections, Assessment, and Interventions

Driving anxiety and anxiolytics while driving: Their impacts on behaviour and cognition behind the wheel

Introduction

The interaction between road safety and drivers' mental health is an important issue to take into consideration on transportation and safety research. The present review deals specifically with the link between anxiety and driving activity from two complementary points of view.

Method

A systematic review into primary studies, following the PRISMA statement, was carried out in four databases: Scopus, Web of Science, Transport Research International Documentation and Pubmed. A total of 29 papers were retained. On the one hand, we present a systematic review of research articles exploring the cognitive and behavioural effects of driving anxiety, regardless its onset, when concerned people have to drive. The second goal of the review is to compile the available literature on the influence of legal drugs, which are used to fight against anxiety, on actual driving tasks.

Results

Eighteen papers have been retained for the first question, whose main findings show that exaggerated cautious driving, negative feelings and avoidance are associated with driving anxiety. Most of the conclusions were drawn from self-reported questionnaires and little is known about the effects in situ. Concerning the second question, benzodiazepines are the most studied legal drugs. They affect different attentional processes and could slow reaction times down depending on the population and treatment features.

Conclusions

The two standpoints included in the present work allow us to propose some possible lines of research to study certain aspects that have not been explored in depth about people who either feel apprehensive about driving or who drive under the effects of anxiolytics.

Practical applications

The study on driving anxiety may be crucial to estimate the consequences for traffic safety. Furthermore, it is relevant to design effective campaigns to raise awareness about the issues discussed. To propose standard evaluations of driving anxiety and exhaustive research works to find out the extent of anxiolytics use are also important to be considered for traffic policies.

Mental health conditions and unsafe driving behaviors: A naturalistic driving study on ADHD and depression

INTRODUCTION

Road injuries remain a persistent public health concern across the world. The task of driving is complicated by mental health conditions, which may affect drivers' executive functioning and cognitive resource allocation. This study examines whether attention-deficit/hyperactivity disorder (ADHD) and depression are associated with unsafe driving behaviors.

METHOD

Generalized linear mixed models were employed to estimate the association of self-reported ADHD and depression with 18 unsafe driving behavior types found prior to at-fault crashes and near-crashes using a large-scale naturalistic driving dataset. Driver demographics, cognitive traits, environmental factors, and driver random effects were included to reduce confounding and biases.

RESULTS

Controlling for other covariates, people with self-reported ADHD were more likely to have performed improper braking or stopping (OR = 4.89, 95% CI 1.82-13.17) prior to an at-fault crash or near-crash, while those with self-reported depression did not have a significant association with any unsafe driving behavior.

CONCLUSIONS

After accounting for demographic, cognitive, and environmental covariates, individuals with ADHD and depression were not prone to purposefully aggressive or reckless driving. Instead, drivers with self-reported ADHD may unintentionally execute unsafe driving behaviors in particular driving scenarios that require a high level of cognitive judgment.

PRACTICAL APPLICATIONS

These findings can inform the curriculum design of driver's education programs that help learners with mental health conditions gain practice in certain road scenarios, for example, more practice on preemptively reducing speed instead of making sudden brakes and smooth turning on curved roads for students with ADHD. Furthermore, specific advanced driver assistance systems may prove particularly helpful for drivers with ADHD, such as detection of leading objects and curve speed warning.

The Influence of Personality and Demographic Characteristics on Aggressive Driving Behaviors in Eastern Chinese Drivers

Purpose

Road safety research is important due to the large number of road traffic fatalities globally. This study investigated the influences of age, driving experience and other covariates on aggressive driving behavior.

Methods

A cross-sectional survey was conducted in Yixing City, Wuxi City, Jiangsu Province, China. Regression analysis was applied to explore the influences of age and driving experience and their interactions with other covariates on aggressive driving behavior. Two analyses methodologies were used to assess the simple effect of the interactions. Firstly, the Jamovi automatic analysis classification program was used to calculate the simple slope test. Second, the SPSS macro program was also used to calculate the simple slope test also.

Results

A total of 570 drivers (247 males, 282 females) participated in the survey. A negative correlation was found between age and aggressive driving behaviors, and a positive correlation was found between neuroticism and aggressive driving behaviors in the multiple regression analysis. Significant associations were also found between age, driving experience, and depression, as well as age, driving experience, and neuroticism. Simple slope tests showed that depressive symptoms could increase aggressive behaviors in the elderly and experienced drivers. When experiencing neuroticism, individuals with higher driving experience were more aggressive in driving than shorter experienced drivers.

Conclusion

Age and neuroticism influenced aggressive driving behaviors. Veteran drivers could be aggressive drivers when experiencing depressive symptoms or neuroticism. Mobile intervention could be sent to the potentially risky drivers, which would be safe and broadly feasible to prevent aggressive driving behavior in the background of COVID-19.

Mental health and behavioural factors involved in road traffic crashes by young adults: analysis of the Raine Study

BACKGROUND

Road traffic crashes (RTC) are a leading cause of mortality and morbidity in young people. Severe mental health and behavioural conditions increase the likelihood of RTC, as do a range of driving-risk activities.

METHOD

We used data from the Raine Study, a prebirth cohort from Perth, Australia, to assess the relationship between measures of common mental health or behavioural conditions (Child Behavior Checklist Internalising and Externalising scores) at age 17 and subsequent RTC by 27 years, controlling for substance use and driving-risk activities.

RESULTS

By 27 years of age, of 937 participants, 386 (41.2%) reported zero crashes and 551 (58.8%) reported ≥1 crashes. In the baseline Poisson model, increased Externalising scores (eg, aggression and delinquency) were associated with increased RTC (incidence rate ratio (IRR)=1.02, 95% CI 1.01 to 1.02): increased Internalising scores (eg, anxiety and depression) were associated with fewer RTC (IRR=0.99, 95% CI 0.98 to 1.00). In the fully adjusted model, the mental health measures were not significant (Externalising IRR=1.01, 95% CI 0.99 to 1.02: Internalising IRR=0.99, 95% CI 0.99 to 1.00). Risky driver activities, such as falling asleep while driving (IRR=1.34), more frequent use of a hands-free telephone (IRR=1.35) and more frequent hostility towards other drivers (IRR=1.30) increased the rate of RTC.

CONCLUSION

Measures of mental health scores at age 17 were not predictive of subsequent RTC, after adjusting for measures of driving-risk activities. We need to better understand the determinants of externalising and risky driving behaviours if we are to address the increased risk of RTC.

Driver's Personality and Behavior for Boosting Automobile Security and Sensing Health Problems Through Fuzzy Signal Detection Case Study: Mexico City

Automobile security became an essential theme over the last years, and some automakers invested much money for collision avoidance systems, but personalization of their driving systems based on the user's behavior was not explored in detail. Furthermore, efficiency gains could be had with tailored systems. In Mexico, 80% of automobile accidents are caused by human beings; the remaining 20% are related to other issues such as mechanical problems. Thus, 80% represents a significant opportunity to improve safety and explore driving efficiency gains. Moreover, when driving aggressively, it could be connected with mental health as a post-traumatic stress disorder. This paper proposes a Tailored Collision Mitigation Braking System, which evaluates the driver's personality driving treats through signal detection theory to create a cognitive map that understands the driving personality of the driver. In this way, aggressive driving can be detected; the system is then trained to recognize the personality trait of the driver and select the appropriate stimuli to achieve the optimal driving output. As a result, when aggressive driving is detected continuously, an automatic alert could be sent to the health specialists regarding particular risky behavior linked with mental problems or drug consumption. Thus, the driving profile test could also be used as a detector for health problems.

Cognitive and body manifestations of driving anxiety according to different onsets

BACKGROUND

Driving anxiety can have deleterious effects not only on driving behavior, but also on life quality. The interaction between motor vehicle collision (MVC) experiences and driving anxiety has been studied from different standpoints. However, the comparison with other events triggering it has been scarcely considered. Objectives: To analyze the body manifestations and the driving cognitions related to the accident, social and panic concerns in people suffering from different levels of driving anxiety. Method: A total of 260 participants suffering from driving anxiety were included in a survey, including Driving Cognition Questionnaire and Body Sensation Questionnaire. Results: Panic attacks and criticisms are the most relevant onsets of driving anxiety, more than MVC. Only 11.4% of MVC victims considered it as the onset. People with MVC history showed lower scores in social concerns than people without MVC experience and neither the responsibility of the MVC nor the role (driver/passenger) seemed to have an impact on the anxiety level. Conclusions: Although the most relevant body sensations, heart palpitations and sweating, were the same in people with panic attack experiences and MVC victims, a discrimination of the emotions behind the concept of "driving anxiety" is desirable to clarify the psychological effects of different onsets.

Driving Outside the Wire: Examining Factors Impacting Veterans' Postdeployment Driving

Combat Veterans (CVs) deployed to Iraq or Afghanistan experience driving difficulty, based on medical conditions and/or deployment exposures, elevating their risk of motor vehicle crash-related injury or death. To address grounded theory rigor and incorporate constructs such as the Person Environment Occupation Performance model, we revised the Hannold et al. (2013) conceptual framework. We conducted two focus groups with seven CVs. Conceptual framework revisions were based on an iterative process and thematic analysis. We elicited CVs' perspectives on deployment training, driving pre- and postdeployment, strategies, and intervention preferences. Personal, environmental, and task factors underpinned CVs' driving. Participants described triggers (e.g., stressful stimuli), use of environmental (e.g., car controls) or personal (e.g., avoiding traffic) strategies, and outcomes of appropriate or risky driving. Findings illustrated CVs' driving difficulty and informed development of a Veteran-centric driving intervention. Improving driving fitness has implications for Veterans' participation and community integration.

Testing the Effectiveness of a Mixed-Method Pilot Intervention in Reducing Risky Driving Due to Aggression and Stress

The study aimed at testing the effectiveness of a mixed-method pilot intervention in reducing risky self-reported driving performance, upon addressing stress and aggression while driving. The study recruited individuals who had performed these behaviors during the year preceding the study and allocated them into an intervention (n = 10) and a control group (n = 30). A pre-and postintervention evaluation design was employed to explore changes in risky self-reported driving behaviors, 12 months after the intervention. The intervention involved 2 h of experiential instruction and 1 h of cognitive restructuring using a driving simulator and scenarios appropriate for the processing of driving stress, aggression, and risk. The intervention group displayed significant improvements in the scales of “Hazard Monitoring” (p = 0.037) and “Covered Violations” (p = 0.049) at the postintervention level. No statistically significant differences were identified in terms of self-reported driving performance between the intervention and the control group at postintervention level. Launching large-scale experimental surveys with broadened cognitive restructuring approaches seems important to deepen our understanding of the behavioral change processes and increase the effectiveness of future interventions.

Predictive factors associated with driving under the influence among Brazilian drug-using drivers

The incidence of driving under the influence of psychoactive substances (DUI) and its recidivism can be curtailed by the proper identification of specific and predictive characteristics among drug users. In this sense, interpersonal violence (IV), psychiatric comorbidity and impulsivity seem to play an important role in DUI engagement according to previous studies. There are, however, limited data originated from low and middle income countries. In the present study, drug-using Brazilian drivers reporting DUI (n = 75) presented a higher prevalence of bipolar disorders (BD; DUI: 8% vs. non-DUI: 0%, p < 0.001), lower prevalence of obsessive-compulsive disorder (OCD; DUI: 0% vs. non-DUI: 12.6%, p < 0.001), and higher prevalence of childhood trauma (DUI: 65.3% vs. non-DUI: 46.8%, p = 0.022) than those not reporting DUI (n = 79). The evaluation of impulsivity though the Barratt Impulsivity Scale, which give impulsivity scores ranging from 30 to 120, showed higher impulsivity scores in the DUI group (80.4 ± 8) than in the non-DUI group (77.2 ± 10, p = 0.045). In general, subjects were young adults (mean age of 36 ± 9 years), Caucasians (58.4%), not married (61.0%), and with elementary schooling (40.3%) with no significant differences in demographic characteristics between drivers with and without DUI behavior. A multiple Poisson regression model showed that individuals reporting IV as perpetrators and history of childhood trauma were more likely to report DUI (PR: 1.66, 95%CI 1.22-2.7; PR: 1.57, 95%CI 1.02-2.42, respectively). The overlapping of violent situations (childhood trauma, IV and DUI) in some individuals presented here corroborates literature data suggesting that DUI can be an externalizing expression of a range of risky behavior, such as impulsiveness and aggressiveness. Moreover, while BD and higher impulsivity scores seem to act as risk factors for DUI, OCD was shown as a protective factor. These results corroborate the hypothesis that individuals with high risk for DUI could probably be identified by multidimensional assessment of cognitive, risky taking, and personality traits, which perhaps could facilitate the development of focused interventions.

Which drivers are at risk? Factors that determine the profile of the reoffender driver

Finding appropriate assessment tools to predict recidivism is a difficult aim, which may lead to actions with unintended consequences. Aims don't have consequences. At times, the research has been used to justify penalising reoffenders with punitive measures rather than treating them with effective psychological interventions. This study aims to contribute to untangling and assessing the potential predictors of reoffender drivers. In this study, 296 drivers: 86 reoffenders (7 women and 79 men) and 206 non-reoffenders (105 women and 101 men) responded to a battery of assessment questionnaires in which they were asked for demographic data (i.e. gender and age), alcohol consumption habits, driving styles, general estimation of risk in everyday life, sensitivity to reward and punishment and anger while driving. The results provided a logistical regression model capable of predicting reoffending and explaining 34% of variability, successfully classifying 77.6% of participants. In this model, the best predictor of reoffending is higher consumption of alcohol (Alcohol Use Disorders, AUD), followed by incautious driving (since cautious driving style correlates negatively with reoffending) and to a lesser extent, infraestimation of recreational risk and a greater sensitivity to reward. Relying on results to predict recidivism could be important to plan better interventions to prevent it.