Introduction: New parents commonly experience sustained sleep disruption in the postpartum period, yet their road-safety risk remains under-examined. This study investigated sleep patterns, the prevalence of fatigued driving, risk awareness, and fatigue-management strategies among Australian parents with at least one child under 12 months. Method: A cross-sectional design using an online survey was conducted using Qualtrics. Measures included sleep quantity and quality (modified Pittsburgh Sleep Quality Index), frequency and symptoms of fatigued driving, self-reported driving behavior (Driver Behavior Questionnaire), comparative risk awareness, and use of behavioral and technological fatigue-mitigation strategies. Results: Among the 1,160 responses included in the analysis, participants reported substantial sleep disruption, averaging six hours of sleep per night with generally poor sleep quality. Over 90% reported driving while fatigued at least once in the past 30 days. Common self-observed symptoms included poor concentration, tired eyes, increased blinking, and an increased likelihood of driving errors. Participants who reported fatigued driving also reported significantly higher levels of aberrant driving behaviors (Aggressive Violations: t(1015) = -2.59, p = 0.01; Violations: t(1015) = -4.71, p < 0.001; Lapses: t(1015) = -6.23, p < 0.001; Errors: t(103) = -7.17, p < 0.001). Fatigued driving was reported more frequently than speeding, mobile phone use, or alcohol- and drug-impaired driving. Fatigue management relied primarily on short-term behavioral strategies such as caffeine intake and in-vehicle stimulation, while uptake and perceived effectiveness of fatigue-detection technologies were limited. Conclusions: New parents experience pronounced sleep disruption and frequently engage in fatigued driving associated with higher crash-risk behaviors. These findings highlight the need for greater attention to fatigue-related driving risk during early parenthood. Practical Applications: Targeted road-safety messaging, healthcare-provider advice, supportive workplace policies, and clearer communication about fatigue-detection technologies may reduce fatigue-related driving risk during early parenthood.

Introduction: While the role of personality in shaping behavior and safety has been widely documented across domains, its study among cyclists has remained limited. Traditional trait-based approaches may also fall short in predicting real behaviors, which highlights the need to explore additional factors. Aims: This research examined associations between personality traits, cycling behaviors, and self-reported crashes, and tested the predictive role of sensation seeking (SS), an emerging construct in cycling safety, on risky and protective behaviors. Methods: A cross-sectional study was conducted with 5,778 cyclists from 17 countries (58% male, 41% female, 1% non-binary; M = 34 years). Participants completed an online questionnaire assessing personality, cycling behaviors, and self-reported crashes over five years. Results: Most personality traits showed significant associations with risky behaviors, but the strongest correlations involved SS. Path analyses indicated that high sensation seekers were more likely to engage in road conflicts. SS also covaried with risk perception, which predicted both risky and protective behaviors. Cyclists reporting crashes scored higher on SS and openness, and lower on agreeableness. Conclusion: The findings suggest that personality traits are related to self-reported cycling safety outcomes, with SS showing the clearest links to risky behaviors, road conflicts, and crash involvement. The observed covariance between SS and risk perception also supports considering both factors jointly when examining cycling safety.

Forgiveness is crucial for emotional wellbeing and good mental health. It is therefore important to understand what cognitive processes may promote forgiveness to achieve optimal outcomes for individuals. There is some evidence to suggest that core self-evaluation (CSE) is related to how forgiving an individual may be. However, these studies have shown that this influence may be mediated by other cognitive processes. To date, the combined role of anger rumination and mindfulness as potential mediators has not been considered. This is despite recognized associations with constructs that underly CSE. To address this gap in knowledge, this study aimed to explore the relationship between CSE and forgiveness; considering whether this relationship is mediated by mindfulness and anger rumination. A further contribution to knowledge was that these relationships were considered across the three subtypes of forgiveness: self, others, and situation. A total of 490 participants (54

OBJECTIVES:The core aim of this study was to assess secondary task engagement among Australian cyclists, considering demographic, behavioral, and psychosocial factors as potential contributors. METHODS:This study used the information provided by a sample of 1,240 Australian cyclists (24% females; 74% males; 2% non-binary) aged M = 53.6 (SD 12.9) years. They responded to an online survey on cycling-related affairs, including demographic, psychosocial (Risk Perception and Regulation Scale, RPRS), behavioral (Cycling Behavior Questionnaire, CBQ), and technology-related (Affinity for Technology Questionnaire, TAEG) factors. RESULTS:After analyzing the TAEG properties and outcomes in this Australian sample, it was found that engagement in secondary tasks while riding varies significantly according to demographic and cycling behavioral profiles. For instance, older cyclists were less likely to report engaging in secondary tasks while riding. In terms of cycling behavior, respondents who reported higher rates of violations were more likely to report high engagement with technology while riding. Moreover, the results from a multilinear regression model predicting secondary task engagement indicated associations between self-reported cycling behavior and engagement in secondary tasks, as well as a strong relationship between traffic violations and the latter. Additionally, knowledge of traffic rules and self-reported positive behaviors showed a significant negative relationship with secondary task engagement, suggesting that these respondents were less inclined to use mobile devices while riding. CONCLUSION:Overall, the findings of this study support the hypothesis that secondary task engagement can be statistically explained by demographic factors (such as age and gender), attitudinal factors, and cycling behavior. These findings highlight several challenges and implications for cycling safety practices, particularly considering the increasing normalization of technology-related secondary tasks in transport activities such as cycling.

While urban cycling is gaining ground worldwide as an active and sustainable mode of transport, various safety-related risks continue to threaten cyclists. In this regard, some studies suggest that cycling risk-related outcomes could be closely linked to development indicators beyond cycling infrastructure, including health, income, and welfare indices. This study aimed to analyze the relationships between different country-level development indicators (e.g., income level, life expectancy, internet access, healthcare coverage, and national health expenditure) and cyclists’ behavioral and safety-related outcomes in 19 countries with diverse socio-economic backgrounds. The findings of this multinational study indicate that country-level development indicators are significantly and consistently related to both cycling safety behaviors and crash records, with the situation being more pronounced in developing (LMIC) countries. Overall, these differences highlight (although not linearly) the inequity and the high vulnerability faced by cyclists in countries with low or medium levels of economic development and point to the need for targeted interventions in areas such as information access, healthcare, and road safety training. Such measures could support the promotion of cycling and other active transport modes from a user-centered perspective. All in all, this may help multidimensionally enhance the promotion of the bicycle as a sustainable means of transport, fostering increased safety and equity among countries.

With advancements in automated driving technology and the sharing economy, automated rideshare services (ARS) are entering the market. In this service, vehicles are controlled by an automated driving system, with a safety operator available to take over if needed. ARS has great potential to reduce travel costs and crashes caused by human error. However, user acceptance is essential for adoption and intention to use. To address this issue, this study examined users' a priori acceptance of ARS by extending the Technology Acceptance Model to include perceived risk, trust, social influence, and facilitating conditions (e.g., road infrastructure, communication facilities). Intentions to use ARS with an invehicle safety operator versus one provided by remote network control was also investigated. Data were collected from 580 participants (M = 32.1 years, SD = 6.8, Range = 21.0-61.0 years; Male: 60.7 %) through an online questionnaire. The structural equation model showed that higher levels of perceived trust in automated driving systems, and trust in safety operators were associated with lower perceived safety risk and subsequent increased intention to use the services. Increased perceived safety risk of manual rideshare services only promoted intentions to use ARS with remote safety operators, not those with invehicle safety operators. Perceived ease of use strongly influenced intentions for ARS with invehicle safety operators, while social influence and facilitating conditions were key factors for those with remote safety operators. These findings indicate a need for programs that enhance users' understanding of how automated driving systems and safety operators contribute to road safety. Additionally, clarifying the operational scope of different ARS will improve their perceived ease of use and acceptance.

Understanding the factors influencing children's safety practices, such as helmet use, is essential for developing effective interventions. This study investigates the relationship between parental bicycle helmet use and their children, focusing on parental attitudes and behaviours. The study was conducted in S & Oslash;r-Tr & Oslash;ndelag, Norway, with 103 parent-child dyads (children aged 10-16) using convenience sampling and a cross-sectional survey. The primary aim was to assess whether parental attitudes or behaviours more strongly predict children's helmet use and examine if child age and sex moderate these relationships. The survey evaluated cycling frequency, helmet use, perceived social norms and the costs and benefits of helmet use. Although nearly all children owned helmets, they wore them less frequently than their parents. A positive correlation was observed between parent and child helmet-wearing and cycling, indicating parental behaviour's significant role in shaping children's safety practices. An Actor-Partner Interdependence Model was used to understand the attitudes and behaviour of children in relation to helmet wearing, while accounting for the influence of the parent attitudes and behaviour. When this dyadic relationship was considered, the impact of parental attitudes on children's helmet use was indirect, mediated through children's own attitudes, and younger children mimicked parental behaviour more than older children. These findings highlight the importance of parental modelling in encouraging helmet use. Interventions should focus on enhancing parental engagement and addressing children's perceived barriers. By elucidating the dynamics of parental influence, this research aids in developing effective safety campaigns to promote helmet use and cycling safety for young cyclists.

Hypoglycemia is a major safety concern for drivers with diabetes. Continuous glucose monitoring (CGM) improves detection of low glucose levels while driving, yet evidence regarding real-world use remains limited. We conducted a national survey of 1209 Australian drivers with diabetes treated with glucose-lowering medication (mean age 55, standard deviation15 years; 47% using CGM; 39% with type 1 diabetes). Twenty-eight percent of participants reported hypoglycemia while driving in the past 12 months. CGM use was associated with higher odds of reporting hypoglycemia while driving (adjusted odds ratio 3.61 [95% confidence interval: 2.19-5.68]), likely reflecting greater detection. Two-thirds of CGM users relied on CGM vibration or audio alerts, and fewer than one in five adjusted alert thresholds for driving. Difficulty using CGM while driving (50%) and legal uncertainty (43%) were the most frequent barriers. Drivers expressed strong interest in safer in-car CGM integration and clearer legal guidance to support glucose monitoring while driving.

INTRODUCTION:Vehicle automation technology has considerable potential for reducing road crashes associated with human error, including issues related to driver drowsiness. However, before full automation becomes available on public roads, it will be essential for drivers to take back control from automated driving systems when requested. This poses a challenge for drivers, particularly as automation may further exacerbate drowsiness. This paper aims to update a systematic review published in 2022 (Merlhiot & Bueno, Accident Analysis and Prevention, 170, 106536), to discuss factors affecting driving drowsiness and takeover performance with a particular focus on those not identified in previous review. METHOD:Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, three databases: Web of Science, PubMed and Scopus were searched for studies published between March 2021 and October 2024. The following eligibility criteria were applied for study inclusion: 1) participants must have interacted with a simulated or real-world vehicle featured with driving automation Level 2 or above; 2) with at least one measurement indicator of driver drowsiness; 3) with at least one measurement indicator of takeover performance; 4) be conducted within a controlled experimental design. From an initial selection of 182 articles from databases, a total of twelve published articles were obtained after removing duplicates, title, abstracts and full texts checking. Additionally, 17 articles from the previous review were included, resulting in a total of 29 articles for this review study. RESULTS:Driver drowsiness (e.g, increased Karolinska Sleepiness Scale levels, blink frequency) tended to increase with both the duration of automated driving and automation levels. Engaging in non-driving related tasks (NDRTs) alleviates drowsiness (e.g, lower heart rate and percentage of eye closure), but reduces takeover performance (e.g., longer braking reaction times, stronger longitudinal acceleration, shorter minimal time to collision). Compared to older drivers, younger drivers were more susceptible to drowsiness, while older drivers had worse takeover performance (e.g., delayed steering reaction time, higher collision rates). Sleep inertia and circadian rhythms were also identified as factors influencing takeover performance. The road monitoring task helps prevent excessive participation in NDRTs and improves takeover performance (e.g, reduced brake reaction times and maximum steering velocity, increased the minimum time to collision). Digital voice assistants and scheduled manual driving help maintain alertness (e.g, decreased blink duration) and enhance takeover performance (e.g, shorter reaction time to resume steering). There were several limitations of the methodologies applied in the existing studies, among which were: 1) a lack of verification through real-world driving experiments; 2) insufficient diversity in the measurement of driver drowsiness; 3) singularity of takeover scenarios; 4) failure to reveal the mechanism by which drowsiness affects takeover performance. CONCLUSION:Factors such as duration of automated driving, NDRT engagement, driver age, sleep-related issues and automation levels influence the development of drowsiness and subsequent takeover performance. This literature review highlights several necessary directions for future research: 1) what underlying factors affect drowsiness and take over performance; 2) how to prevent the occurrence of driver drowsiness; 3) how to alleviate driver drowsiness once it occurs; 4) how to assist drowsy drivers to regain control of the vehicle safely and quickly.

Distracted driving is a leading cause of road trauma. While there is an understanding of some psychological mechanisms underlying distracted driving, there is limited knowledge on the role of executive function in the willingness to engage in non-driving tasks and even less is known about its potential role in drivers’ self-regulatory behaviour when distracted. This study investigated the relationship between executive function and driver engagement with technology. It specifically focussed on whether difficulties in everyday executive functioning impacts drivers’ ability to self-regulate behaviour when engaging with devices at the planning, decision and control levels. Twenty-five licenced drivers aged 20 to 65 years were recruited from the general driving public. Participants first completed the Behaviour Rating Inventory of Executive Function – Adult Version (BRIEF-A) and then filled in a series of trip diaries soon after driving over a four-week period. The diaries detailed their interactions with a range of on-board and portable devices during each trip. Generalised Estimated Equations were used to examine associations between executive function and drivers’ behavioural regulation when interacting with devices. Results revealed that difficulties with the behavioural regulation and metacognition aspects of executive function were associated with higher engagement with devices while driving. Executive function also had important links to drivers’ self-regulatory behaviours, particularly at the planning and decision levels. The relationship between executive function and self-regulation at the control level was less clear. These findings enhance our understanding of the mechanisms underlying distracted driving behaviour and suggest possible interventions to reduce engagement with devices and facilitate and enhance positive self-regulatory behaviours.

Driving anxiety can be common. When extreme, drivers may lose independence as they change their driving patterns or cease driving altogether. This can lead to poorer quality of life and work. It is therefore important to understand how to support people to manage this anxiety and continue to drive, should they wish to do so. The aims of the current study were to 1) understand the types of help sought by people who experience some level of driving anxiety, and 2) understand factors associated with help-seeking and what support is perceived as beneficial. A total of 1,314 people (women = 77 %; ranging in age from 18 to 89; M = 27; SD = 13 years) responded to an online survey providing responses to questions about driving anxiety levels, onset of anxiety, level and causes of shame about the anxiety, perceived driving skill and help-seeking behaviour. Fourteen various types of help-seeking were included covering non-professional help (such as talking to family or friends, vehicle technology) and professional help (such as driving training/re-training, therapy or medication). Based on responses to these, participants were classified into three help-seeking groups: those who have or are currently seeking help (55 %); those who intend to seek help (22 %) and those who have no intention of seeking help (22 %). Those not intending to seek help were mainly men and who experience low levels of anxiety that originated due to traffic concerns (such as being fined, etc). Those whose anxiety was more generalised tended to be seeking help for their driving anxiety as well. The results highlighted potential avenues to support anxious drivers. These include the support and understanding of family and friends. Further driver training, that may focus on anxiety is another potential avenue. Potential benefits of vehicle technology to support driving anxiety were also noted.

Although most actions aimed at promoting the use of active transport means have been conducted in 'large' cities, recent studies suggest that their cycling dynamics could hinder the efforts put into infrastructural, modal share, and cycling culture improvements.Aim: The present study aimed to assess the role of city sizes on riding behavioral and crash-related cycling outcomes in an extensive sample of urban bicycle users.Methods: For this purpose, a full sample of 5705 cyclists from >300 cities in 18 countries responded to the Cycling Behavior Questionnaire (CBQ), one of the most widely used behavioral questionnaires to assess risky and positive riding behaviors. Following objective criteria, data were grouped according to small cities (S; population of 50,000 or fewer), medium cities (M; population between 50,000 and 200,000), large cities (L; population between 200,000 and one million), and megacities (XL; population larger than one million).Results: Descriptive analyses endorsed the associations between city size, cycling behavioral patterns, and mid-term self-reported crash outcomes. Also, it was observed a significant effect of the city size on cyclists' traffic violations and errors (all p < .001). However, no significant effects of the city size on positive behaviors were found. Also, it stands out that cyclists from megacities self-reported significantly more violations and errors than any of the other groups. Further, the outcomes of this study suggest that city sizes account for cycling safety outcomes through statistical associations, differences, and confirmatory predictive relationships through the mediation of risky cycling behavioral patterns.Conclusion: The results of the present study highlight the need for authorities to promote road safety education and awareness plans aimed at cyclists in larger cities. Furthermore, path analysis suggests that "size does matter", and it statistically accounts for cycling crashes, but only through the mediation of riders' risky behaviors.

BackgroundGlobally, road traffic crashes are the leading cause of death for young adults. The P Drivers Project was a trial of a behavioural change program developed for, and targeted at, young Australian drivers in their initial months of solo driving when crash risk is at its highest.MethodsIn a parallel group randomised controlled trial, drivers (N = 35,109) were recruited within 100 days of obtaining their probationary licence (allowing them to drive unaccompanied) and randomised to an intervention or control group. The intervention was a 3 to 6-week multi-stage driving behaviour change program (P Drivers Program). Surveys were administered at three time points (pre-Program, approximately one month post-Program and at 12 months after). The outcome evaluation employed an on-treatment analysis comprising the 2,419 intervention and 2,810 control participants who completed all required activities, comparing self-reported crashes and police-reported casualty crashes (primary outcome), infringements, self-reported attitudes and behaviours (secondary outcomes) between groups.ResultsThe P Drivers Program improved awareness of crash risk factors and intentions to drive more safely, relative to the controls; effects were maintained after 12-months. However, the Program did not reduce self-reported crashes or police-reported casualty crashes. In addition, self-reported violations, errors and risky driving behaviours increased in the intervention group compared to the control group as did recorded traffic infringements. This suggests that despite the Program increasing awareness of risky behaviour in novice drivers, behaviour did not improve. This reinforces the need to collect objective measures to accompany self-reported behaviour and intentions.ConclusionsThe P Drivers Program was successful in improving attitudes toward driving safety but the negative impact on behaviour, lack of effect on crashes, and the large loss to follow-up fail to support the use of a post-licensing behaviour change program to improve novice driver behaviour and reduce crashes.Trial registration: Australian New Zealand Clinical Trials Registry: 363,293 (ANZCTR, 2012).

This Data in Brief (DiB) article presents the differences in cycling behaviors related to violations, errors, and positive behaviors by region. The study data were collected by means of a structured questionnaire applied to a full sample of 7,001 participants from 19 countries, distributed over 5 continents. This paper proposes descriptive statistics, as well as common statistical tests. The aim is to enable authors to make their own analyses, not to provide precise interpretations. For further information about the macro project supporting the collection of these data, it is advised to refer to the paper titled “Cross-culturally approaching the cycling behavior questionnaire (CBQ): Evidence from 19 countries”, published in Transportation Research Part F: Traffic Psychology and Behavior.

Introduction: Driver anger and aggression have been linked to crash involvement and injury outcomes. Improved road safety outcomes may be achieved through understanding the causes of driver anger, and interventions designed to reduce this anger or prevent it from becoming aggression. Scales to measure anger propensities will be an important tool in this work. The measure for angry drivers (MAD; Stephens et al., 2019) is a contemporary scale designed to measure tendencies for anger across three types of driving scenarios: perceived danger from others, travel delays, and hostility or aggression from other drivers. Method: This study aimed to validate MAD using a representative sample of Australian drivers, stratified across age, gender, and location. Participants completed a 10-minute online survey that included MAD, sought demographic information (age, gender, driving purpose, crash history), as well as the frequency of aggressive driving. Multigroup confirmatory factor analyses (MGCFA) assessed how stable the structure of the MAD was across drivers of different ages, gender, purposes for driving and those who do or do not display anger aggressively. MAD was invariant across all groups, showing that all drivers interpreted and responded to MAD in the same way. Results: A comparison of latent means showed anger tendencies were higher for men compared to women, for younger drivers compared to older drivers, and for those who drive mainly for work compared to those who mainly drive for other reasons. When controlling for driver factors, driving anger was associated with increased odds of being aggressive while driving. Practical Applications: Overall, this study demonstrated that MAD is an appropriate scale to measure anger tendencies and can be used to support interventions, and evaluation of interventions, to reduce anger and aggressive driving.

Aggressive drivers pose a significant road safety threat to themselves and other road users. Therefore, understanding the relationships between certain cognitive processes and increased frequency of aggression has the potential to reduce road trauma through intervention. This study examined the relationships between anger rumination and forgiveness with trait driving anger and aggressive driving. These factors have previously been individually identified as predictors of aggression; but have yet to be considered simultaneously, despite recognised association between forgiveness and rumination tendencies outside of road safety research. Aggressive driving was measured across three facets of behaviour: verbal aggression, physical aggression, and use of the vehicle to display anger. Adaptive constructive responses to driving anger were also considered. Five hundred and one drivers (mean age = 43.7; SD = 17.7; men = 53.8%) completed an online questionnaire seeking information on these factors. Structural equation modelling showed that, after controlling for gender, 62% of the variance in aggressive driving was explained by a combination of trait driving anger, more frequent rumination and lower levels of forgiveness. Specifically, lower levels of forgiveness predicted more anger rumination (accounting for 49% of the variance), and the relationship between anger rumination and aggression was fully mediated by trait driving anger. A second model demonstrated that 17% of the variance in adaptive constructive responses to anger could be explained by higher levels of forgiveness, lower rumination and driving anger. Efforts to improve driver behaviour need to focus primarily on the reduction of driving anger. This could be achieved by reducing rumination through the promotion of forgiveness for the behaviour of other drivers.

Background: Tailgating (following a lead vehicle too closely) is a key contributor to crashes and injury. While vehicle technology has the potential to reduce the trauma resulting from tailgating, full market penetration of these technologies is some time away. In the meantime, efforts to improve road safety can focus on supporting safer driver behaviour by targeting motivations for this behaviour. Method: A mixed methods design was used to understand reasons why drivers tailgate and potential countermeasures to reduce this behaviour. Qualitative data from 247 drivers (males = 29 %; mean age = 39.86; SD = 14.39) were sought to understand circumstances when drivers are tailgated and when they report tailgating. In a second study, 736 drivers (males = 41 %; mean age = 37.69; SD = 14.27) responded to questions developed from the qualitative findings to quantify the frequency of tailgating and reasons behind it. The theory of planned behaviour (TPB) was applied to understand whether self-reported intention to tailgate could be predicted by attitudes, perceived social acceptance of the behaviour, perceived behavioural control, and past tailgating behaviour.Results: Tailgating was a common behaviour. All drivers in the first study had experienced being tailgated by other drivers, while 77% had tailgated other vehicles; albeit 55% reported this was rare. Tailgating was unintentional (due to dense traffic; or lack of knowledge of safe following distance recommendations) or intentional (due to pressure from other drivers, anger or to change others' behaviour). Structural equation modelling showed that TPB constructs of attitude, social norms, perceived behavioural control and past tailgating behaviour predicted intention to tailgate, accounting for 66% of the variance.Conclusion: TPB is a useful framework for explaining tailgating behaviour, or at least the intention to tailgate, and to develop interventions. These could focus on education of the risks of tailgating, the recommended safe following distances as well as strategies to support drivers maintaining safe following distances across different speed zones.

People driving in excess of the posted speed limit (referred to as speeding in English or Kaahaajat in Finnish) is a common road user behaviour. In Finland, between 2000 and 2020, speeding was identified as the key contributing factor in 41% of fatal motor vehicle collisions. This may be because disregarding speed limits on motorways and on residential roads are the most common violations performed by Finnish drivers. This study identifies factors influencing speeding while driving in Finland. In particular, 703 responses from Finnish drivers of the ESRA2 (E-Survey of Road users’ Attitudes) were analysed to understand the theory of planned behaviour (TPB) factors underpinning speeding behaviours in three road environments: inside built-up areas; outside of built-up areas; and on motorways and freeways. Three binary logistic regression analyses were used to understand which elements of TPB were associated with self-reported speeding in each of these environments. Approximately two thirds of participants reported speeding in each of the three road environments. Attitudes and subjective norms were associated with speeding in built-up areas and on motorways or freeways. In addition, perceived behavioural control and age were significantly associated with speeding outside of built-up areas. The findings highlight how a systematic approach is needed to address speeding considering enforcement, engineering, legislation, and education.

This study investigated the relationship between mindfulness and nomophobia on technology engagement while driving and aberrant driving behaviours. Nine hundred and ninety participants completed an online survey (Female: 68.6%; Age: M = 51.2 years, SD = 15.7, Range = 18.0-84.0 years) that assessed mindfulness, nomophobia, technology engagement while driving, aberrant driving behaviour, and self-reported crashes and infringements during the past two years. Structural equation modelling (SEM) was used to examine the relationships between mindfulness and nomophobia, on one hand, with self-reported engagement with technology while driving and general aberrant driving behaviours (combination of errors, lapses and violations) on the other. The results of the SEM showed that, as expected, mindfulness shared negative relationships with nomophobia, engagement with technology and aberrant driving behaviours, while all other relationships were positive. In terms of engagement with technology, there were direct and indirect paths between nomophobia and mindfulness and engagement with technology. The results of this study demonstrate the positive influence mindfulness can have on nomophobia, engagement with technology while driving, and dangerous driving behaviours that have been associated with crash risk. Mindfulness practices may reduce the effect of nomophobia on engagement with technology while driving and increased dangerous behaviours as a result. This will be increasingly important as modern work and social practices encourage people to increasingly use the phone while driving, and the technology within smart devices, and connectivity of these to the vehicle, increase. More research is needed to understand whether mindfulness-based interventions can reduce nomophobia, and thereby improve driving behaviours and reduce crash rates.

Road traffic crashes are a leading cause of death for young people. Aberrant driver behaviors, such as drink driving, speeding, not wearing seatbelts, non-compliance with traffic rules and aggressive driving, are key contributors to these crashes. Gender and urban/rural differences are also risk factors. In Serbia, where this study was conducted, as well as in most European countries, younger people have the highest road crash and fatality risk. Thus, it is important to understand not only when these behaviors occur, but also the attitudes surrounding them. The latter will provide an avenue for intervention. To address this, a mixed design study was conducted, using a quantitative survey, focus groups and in-depth interviews to understand the attitudes and safety behaviors of young people (aged 16–25) in Serbia. Results across all methods showed that attitudes and perceptions regarding road safety differ across gender and location (urban/rural). Young drivers reported frequent engagement in alcohol-impaired driving, speeding, non-using seatbelts and using mobile phones while driving. Dominant attitudes underlying these behaviors related to lower perceived risk and a lack of perceived enforcements. These results show support for education campaigns in improving the risky behavior of young drivers.