The unintended impact of helmet use on bicyclists’ risk-taking behaviors

Introduction: Safety is a critical factor in promoting sustainable urban non-motorized travel modes like bicycles. Helmets have shown to be effective in reducing injury severity in bicycle crashes, however, their effects on bicyclists’ behaviors still requires deeper understanding, especially amid the emerging trend of using shared bicycles. Risk compensation effects suggest that bicyclists may offset perceived gains in safety from wearing a helmet by increasing risk-taking behaviors. A better understanding of these compensation effects can be useful in assessing various bicycle safety related programs. Method: Using a sample of 131 bicyclists from the San Francisco Bay area, this research studies how bicyclists respond with respect to risk-taking behaviors under various urban-street conditions, as a function of helmet use. Study participants were each shown 12 videos, shot in Berkeley, California, from the perspective of a bicyclist riding behind another bicyclist. A fractional factorial experiment design was used to systematically vary contextual attributes (e.g., speed, bike lane facilities, on-street parking, passing vehicles) across the videos. After each video, participants were asked to indicate if they would overtake the bicyclist in the video. With the help of data adaptive estimation techniques, targeted maximum likelihood estimation (TMLE) was applied to estimate the average risk difference between helmeted users and non-users, controlling for self-selection effects. Individual-based nonparametric bootstrap was performed to assess the uncertainty associated with the estimator. Results: Our findings suggest, on average, individuals more likely to wear a helmet are 15.6% more likely to undertake a risky overtaking maneuver. Practical Applications: This study doesn’t try to oppose mandatory helmet laws, but rather serves as a cautionary warning that road safety programs may need to consider strategies in which unintended impact of bicycle helmet use can be mitigated. Moreover, our findings also provide additional evaluation component when it comes to the cost-benefit assessment of helmet-related laws.     

Traffic safety culture and prosocial driver behavior for safer vehicle-bicyclist interactions

Introduction: Bicyclist safety is a growing concern as more adults use this form of transportation for recreation, exercise, and mobility. Most bicyclist fatalities result from a crash with a vehicle. Often, the behaviors of the driver are responsible for the crash. Method: This survey study of Montana and North Dakota residents (n = 938) examined the influence of traffic safety culture on driver behaviors that affect safe interactions with bicyclists. Results: Prosocial driver behavior was most common and appeared to be intentional. Intention was increased by positive attitudes, normative perceptions, and perceived control. However, normative perceptions appear to offer the most opportunity for change. Practical Application: Strategies that increase perceptions that prosocial driver behavior is normal may increase prosocial intentions, thereby increasing bicyclist safety.     

Identifying high-risk built environments for severe bicycling injuries

Introduction: This study is aimed at filling part of the knowledge gap on bicycling safety in the built environment by addressing two questions. First, are built environment features and bicyclist injury severity correlated; and if so, what built environment factors most significantly relate to severe bicyclist injuries? Second, are the identified associations varied substantially among cities with different levels of bicycling and different built environments? Methods: The generalized ordered logit model is employed to examine the relationship between built environment features and bicyclist injury severity. Results: Bicyclist injury severity is coded into four types, including no injury (NI), possible injury (PI), evident injury (EI), and severe injury and fatality (SIF). The findings include: (a) higher percentages of residential land and green space, and office or mixed use land are correlated with lower probabilities of EI and SIF; (b) land use mixture is negatively correlated with EI and SIF; (c) steep slopes are positively associated with bicyclist injury severity; (d) in areas with more transit routes, bicyclist injury is less likely to be severe; (e) a higher speed limit is more likely to correlate with SIF; and (f) wearing a helmet is negatively associated with SIF, but positively related to PI and EI. Practical applications: To improve bicycle safety, urban planners and policymakers should encourage mixed land use, promote dense street networks, place new bike lanes in residential neighborhoods and green spaces, and office districts, while avoiding steep slopes. To promote bicycling, a process of evaluating the risk of bicyclists involving severe injuries in the local environment should be implemented before encouraging bicycle activities.     

The potential of vehicle and road infrastructure interventions in fatal bicyclist accidents on Swedish roads—What can in-depth studies tell us?

Abstract

Objective: The objective of this article is to describe the characteristics of fatal crashes with bicyclists on Swedish roads in rural and urban areas and to investigate the potential of bicycle helmets and different vehicle and road infrastructure interventions to prevent them. The study has a comprehensive approach to provide road authorities and vehicle manufacturers with recommendations for future priorities.

Methods: The Swedish Transport Administration’s (STA) in-depth database of fatal crashes was used for case-by-case analysis of fatal cycling accidents (2006–2016) on rural (n?=?82) and urban (n?=?102) roads. The database consists of information from the police, medical journals, autopsy reports, accident analyses performed by STA, and witness statements. The potential of helmet use and various vehicle and road infrastructure safety interventions was determined retrospectively for each case by analyzing the chain of events leading to the fatality. The potential of vehicle safety countermeasures was analyzed based on prognoses on their implementation rates in the Swedish vehicle fleet.

Results: The most common accident scenario on rural roads was that the bicyclist was struck while cycling along the side of the road. On urban roads, the majority of accidents occurred in intersections. Most accidents involved a passenger car, but heavy trucks were also common, especially in urban areas. Most accidents occurred in daylight conditions (73%). Almost half (46%) of nonhelmeted bicyclists would have survived with a helmet. It was assessed that nearly 60% of the fatal accidents could be addressed by advanced vehicle safety technologies, especially autonomous emergency braking with the ability to detect bicyclists. With regard to interventions in the road infrastructure, separated paths for bicyclists and bicycle crossings with speed calming measures were found to have the greatest safety potential. Results indicated that 91% of fatally injured bicyclists could potentially be saved with known techniques. However, it will take a long time for such technologies to be widespread.

Conclusions: The majority of fatally injured bicyclists studied could potentially be saved with known techniques. A speedy implementation of important vehicle safety systems is recommended. A fast introduction of effective interventions in the road infrastructure is also necessary, preferably with a plan for prioritization.     

Using latent class clustering and binary logistic regression to model Australian cyclist injury severity in motor vehicle–bicycle crashes

Introduction: In recent years, Australia is seeing an increase in the total number of cyclists. However, the rise of serious injuries and fatalities to cyclists has been a major concern. Understanding the factors affecting the fatalities and injuries of bicyclists in crashes with motor vehicles is important to develop effective policy measures aimed at improving the safety of bicyclists. This study aims to identify the factors affecting motor vehicle-bicycle (MVB) crashes in Victoria, Australia and introducing effective countermeasures for the identified risk factors. Method: A data set of 14,759 MVB crash records from Victoria, Australia between 2006 and 2019 was analyzed using the binary logit model and latent class clustering. Results: It was observed that the factors that increase the risk of fatalities and serious injuries of bicyclists (FSI) in all clusters are: elderly bicyclist, not using a helmet, and darkness condition. Likewise, in areas with no traffic control, clear weather, and dry surface condition (cluster 1), high speed limits increase the risk of FSI, but the occurrence of MVB crashes in cross intersection and T-intersection has been significantly associated with a reduction in the risk of FSI. In areas with traffic control and unfavorable weather conditions (cluster 2), wet road surface increases the risk of FSI, but the areas with give way sign and pedestrian crossing signs reduce the risk of FSI. Practical Applications: Recommendations to reduce the risk of fatalities or serious injury to bicyclists are: improvement of road lighting and more exposure of bicyclists using reflective clothing and reflectors, separation of the bicycle and vehicle path in mid blocks especially in high-speed areas, using a more stable bicycle for the older people, monitoring helmet use, improving autonomous emergency braking, and using bicyclist detection technology for vehicles.     

Exploring bicyclist injury severity in bicycle-vehicle crashes using latent class clustering analysis and partial proportional odds models

Introduction: Bicyclists are more vulnerable compared to other road users. Therefore, it is critical to investigate the contributing factors to bicyclist injury severity to help provide better biking environment and improve biking safety. According to the data provided by National Highway Traffic Safety Administration (NHTSA), a total of 8,028 bicyclists were killed in bicycle-vehicle crashes from 2007 to 2017. The number of fatal bicyclists had increased rapidly by approximately 11.70% during the past 10 years (NHTSA, 2019). Methods: This paper conducts a latent class clustering analysis based on the police reported bicycle-vehicle crash data collected from 2007 to 2014 in North Carolina to identify the heterogeneity inherent in the crash data. First, the most appropriate number of clusters is determined in which each cluster has been characterized by the distribution of the featured variables. Then, partial proportional odds models are developed for each cluster to further analyze the impacts on bicyclist injury severity for specific crash patterns. Results: Marginal effects are calculated and used to evaluate and interpret the effect of each significant explanatory variable. The model results reveal that variables could have different influence on the bicyclist injury severity between clusters, and that some variables only have significant impacts on particular clusters. Conclusions: The results clearly indicate that it is essential to conduct latent class clustering analysis to investigate the impact of explanatory variables on bicyclist injury severity considering unobserved or latent features. In addition, the latent class clustering is found to be able to provide more accurate and insightful information on the bicyclist injury severity analysis. Practical Applications: In order to improve biking safety, regulations need to be established to prevent drinking and lights need to be provided since alcohol and lighting condition are significant factors in severe injuries according to the modeling results.     

Experimental evaluation of alternative conspicuity-enhancement techniques for pedestrians and bicyclists

A field experiment was conducted to determine the extent of conspicuity enhancement provided pedestrians and bicyclists at night by various commercially available retroreflective materials and lights. The conspicuous materials were designed to be worn or carried by the pedestrians and bicyclists. Detection and recognition distances for the various experimental and baseline conditions were determined using subjects driving instrumented vehicles over a predetermined route on a realistic closed-course roadway system. Field experimenters were used to model the conspicuity-enhancing materials employing natural motion associated with walking and bicycling. Comparisons of the detection and recognition distances suggested that pedestrians and bicyclists can greatly enhance their conspicuity to drivers at night by wearing certain types of apparel and by using devices that are currently available in the marketplace. Nevertheless, it was concluded that nighttime pedestrian and bicyclist activity is inherently dangerous, even with these devices, and should be avoided.     

The effects of co-presence on risk perception and intention to engage in risky behaviors

IntroductionThis study investigated the relation between co-presence and bicyclists' riding behavior. We assumed that the presence of peer riders would either facilitate or inhibit risky behaviors depending on bicyclists' perceptions of three traffic contexts conducive to risk taking (i.e., red-light, go straight, and turn to left).MethodYoung bicyclists (N = 207) were randomly assigned to two experimental conditions (alone vs. with peers). They filled in a scenario-based questionnaire about their intentions to adopt risky behaviors in three specific traffic situations as well as their risk perception of these situations and their general self-perceived efficacy as a bicyclist. We hypothesized that the presence of peer riders engaged in a risky behavior will facilitate the intention to adopt risky behaviors in situations where group risk is evaluated as lower than individual risk. In opposition, the presence of peer riders engaged in a risky behavior will inhibit the intention to adopt risky behaviors in situations where group risk is evaluated as higher than individual risk.ResultsThe results confirmed the hypotheses.Practical ApplicationsThe findings offer insights for developing new effective education and intervention programs in order to reduce the frequency of dangerous behavior among bicyclists.     

Bicyclist injury severity in traffic crashes: A spatial approach for geo-referenced crash data to uncover non-stationary correlates

Introduction: Bicyclists are among vulnerable road users with their safety a key concern. This study generates new knowledge about their safety by applying a spatial modeling approach to uncover non-stationary correlates of bicyclist injury severity in traffic crashes. Method: The approach is Geographically Weighted Ordinal Logistic Regression (GWOLR), extended from the regular Ordered Logistic Regression (OLR) by incorporating the spatial perspective of traffic crashes. The GWOLR modeling approach allows the relationships between injury severity and its contributing factors to vary across the spatial domain, to account for the spatial heterogeneity. This approach makes use of geo-referenced data. This study explored more than 7,000 geo-referenced bicycle--motor-vehicle crashes in North Carolina. Results: This study performed a series of non-stationarity tests to identify local relationships that vary substantially across the spatial domain. These local relationships are related to the bicyclist (bicyclist age, bicyclist behavior, bicyclist intoxication, bicycle direction, bicycle position), motorist (driver age, driver intoxication, driver behavior, vehicle speed, vehicle type) and traffic (traffic volume). Conclusions: Results from the regular OLR are in general consistent with previous findings. For example, an increased bicyclist injury severity is associated with older bicyclists, bicyclist being intoxicated, and higher motor-vehicle speeds. Results from the GWOLR show local (rather than global) relationships between contributing factors and bicyclist injury severity. Practical Applications: Researchers and practitioners may use GWOLR to prioritize cycling safety countermeasures for specific regions. For example, GWOLR modeling estimates in the study highlighted the west part (from Charlotte to Asheville) of North Carolina for increased bicyclist injury severity due to the intoxication of road users including both bicyclists and drivers. Therefore, if a countermeasure is concerned with the road user intoxication, there may be a priority for the region from Charlotte to Asheville (relative to other areas in North Carolina).     

Children’s fear in traffic and its association with pedestrian decisions

Introduction: Research on risk for child pedestrian injury risk focuses primarily on cognitive risk factors, but emotional states such as fear may also be relevant to injury risk. The current study examined children's perception of fear in various traffic situations and the relationship between fear perception and pedestrian decisions. Method: 150 children aged 6–12-years old made pedestrian decisions using a table-top road model. Their perceived fear in the pedestrian context was assessed. Results: Children reported greater emotional fear when they faced quicker traffic, shorter distances from approaching traffic, and red rather than green traffic signals. Children who were more fearful made safer pedestrian decisions in more challenging traffic situations. However, when the least risky traffic situation was presented, fear was associated with more errors in children’s pedestrian decisions: fearful children failed to cross the street when they could have done so safely. Perception of fear did not vary by child age, although safe pedestrian decisions were more common among the older children. Conclusions: Children’s emotional fear may predict risk-taking in traffic. When traffic situations are challenging to cross within, fear may appropriately create safer decisions. However, when the traffic situation is less risky, feelings of fear could lead to excessive caution and inefficiency. Practical applications: Child pedestrian safety interventions may benefit by incorporating activities that introduce realistic fear of traffic risks into broader safety lessons.     

Fatally injured pedestrians and bicyclists in the United States with high blood alcohol concentrations

IntroductionLittle research has focused on the problem of alcohol impairment among pedestrians and bicyclists in the United States. The aim of the current study was to investigate the prevalence, trends, and characteristics of alcohol-impaired fatally injured pedestrians and bicyclists.MethodData from the Fatality Analysis Reporting System (FARS) were analyzed for fatally injured passenger vehicle drivers, pedestrians, and bicyclists 16 and older during 1982–2014. Logistic regression models examined whether personal, roadway, and crash characteristics were associated with high blood alcohol concentrations (BACs) among fatally injured pedestrians and bicyclists.ResultsFrom 1982 to 2014, the percentage of fatally injured pedestrians with high BACs (≥ 0.08 g/dL) declined from 45% to 35%, and the percentage of fatally injured bicyclists with high BACs declined from 28% to 21%. By comparison, the percentage of fatally injured passenger vehicle drivers with high BACs declined from 51% in 1982 to 32% in 2014. The largest reductions in alcohol impairment among fatally injured pedestrians and bicyclists were found among ages 16–20. During 2010–2014, fatally injured pedestrians and bicyclists ages 40–49 had the highest odds of having a high BAC, compared with other age groups.ConclusionsA substantial proportion of fatally injured pedestrians and bicyclists have high BACs, and this proportion has declined less dramatically than for fatally injured passenger vehicle drivers during the past three decades. Most countermeasures used to address alcohol-impaired driving may have only limited effectiveness in reducing fatalities among alcohol-impaired pedestrians and bicyclists.Practical applicationsEfforts should increase public awareness of the risk of walking or bicycling when impaired. Results suggest the primary target audience for educational campaigns directed at pedestrians and bicyclists is middle-age males. Further research should evaluate the effectiveness of potential countermeasures, such as lowering speeds or improving lighting in urban areas.     

Behavioral pathways in bicycle-motor vehicle crashes: From contributing factors,pre-crash actions,to injury severities

Introduction: This study performed a path analysis to uncover the behavioral pathways (from contributing factors, pre-crash actions to injury severities) in bicycle-motor vehicle crashes. Method: The analysis investigated more than 7,000 bicycle-motor vehicle crashes in North Carolina between 2007 and 2014. Pre-crash actions discussed in this study are actions of cyclists and motorists prior to the event of a crash, including “bicyclist failed to yield,” “motorist failed to yield,” “bicyclist overtaking motorist,” and “motorist overtaking bicyclist.” Results: Model results show significant correlates of pre-crash actions and bicyclist injury severity. For example, young bicyclists (18 years old or younger) are 23.5% more likely to fail to yield to motor traffic prior to the event of a crash than elder bicyclists. The “bicyclist failed to yield” action is associated with increased bicyclist injury severity than other actions, as this behavior is associated with an increase of 5.88 percentage points in probability of a bicyclist being at least evidently injured. The path analysis can highlight contributing factors related to risky pre-crash actions that lead to severe injuries. For example, bicyclists traveling on regular vehicle travel lanes are found to be more likely to involve the “bicyclist failed to yield” action, which resulted in a total 44.38% (7.04% direct effect + 37.34% indirect effect) higher likelihood of evident or severe injuries. The path analysis can also identify factors (e.g., intersection) that are not directly but indirectly correlated with injury severity through pre-crash actions. Practical Applications: This study offers a methodological framework to quantify the behavioral pathways in bicycle-motor vehicle crashes. The findings are useful for cycling safety improvements from the perspective of bicyclist behavior, such as the educational program for cyclists.     

Perceived stress,mental health,organizational factors,and self-reported risky driving behaviors among truck drivers circulating in France

Introduction: The growth of the European market for road-freight transport has recently led to important changes. The growing number of foreign pavilion drivers transiting in France, which plays a bridging role among European countries, has influenced the lives of truck drivers by increasing competition, pressure on day-to-day activities, and constraints related to delivery deadlines. Adding this new pressure to those inherent in the road-freight transport sector has raised concerns, especially ones linked to levels of perceived stress by truck drivers. Method: With safety concerns in mind, we devised a questionnaire aimed at understanding how French truck drivers and non-French truck drivers, passing through four highway rest areas in France perceive stress, organizational factors, mental health, and risky driving behaviors. A sample of 515 truck drivers took part in the survey (260 French nationals), 97.9% of whom were male. Results: The results of a structural equation model indicated that perceived stress can increase self-reported risky driving behaviors among truck drivers. Furthermore, organizational factors and mental health were closely linked to perceived stress. Finally, some differences were found between French and non-French truck drivers with respect to mind-wandering and mental health, and to perceive driving difficulties to overcome and driving skills. Practical Applications: Several recommendations based on the findings are provided to policymakers and organizations.     

A study of pedestrian and bicyclist exposure to head injury in passenger car collisions based on accident data and simulations

The objective was to assess head injury risks and kinematics of adult pedestrians and bicyclists in primary impact to the passenger cars and secondary impact to the ground using real world accident data and computer reconstructions of the accidents. For this purpose, a subsample of 402 pedestrians and 940 bicyclists from the GIDAS database, Germany, was used for the statistical analysis, from which 22 pedestrian and 18 bicyclist accidents were further selected for reconstruction. PC-Crash was used to calculate impact conditions, such as vehicle impact velocity, vehicle kinematic sequence, and thrown distance. These conditions were employed to identify the initial conditions in reconstruction in MADYMO program. A comparable analysis was conducted based on the results from accident analysis and computer reconstructions for the impact configurations and the resulting injury patterns of pedestrians and bicyclists in view of head injury risks. Differences in HIC, head-relative impact velocity, linear acceleration, maximum angular velocity and acceleration, contact force, thrown distance, Wrap Around Distance (WAD), and head contact time were evaluated. Injury risk curves were generated by using a logistic regression model for vehicle impact velocity. The results indicate that bicyclists suffered less severe injuries compared with severity of pedestrian injuries. In the selected samples, the AIS 2+ and AIS 3+ head injury risks for pedestrians are 50% probability at impact speed of 38.87 km/h and 54.39 km/h respectively, while for bicyclists at 53.66 km/h and 58.89 km/h respectively. The findings of high injury risks suggested that in the area with high frequency car-pedestrian accidents, the vehicle speed limit should be 40 km/h, while in the area with high frequency car-cyclist accidents the vehicle speed limit should be 50 km/h.     

Exploring the severity of bicycle–vehicle crashes using latent class clustering approach in India

IntroductionBicyclists are vulnerable users in the shared asset like roadways. However, people still prefer to use bicycles for environmental, societal, and health benefits. In India, the bicycle plays a role in supporting the mobility to more people at lower cost and are often associated with the urban poor. Bicyclists represents one of the road user categories with highest risk of injuries and fatalities. According to the report by the Ministry of Road Transport and Highways (Accidents, 2017) in India, there is a sharp increase in the number of fatal victims for bicyclists in 2017 over 2016. The number of cyclists killed jumped from 2,585 in 2016 to 3,559 in 2017, a 37.7% increase. Method: Few studies have only investigated the crash risk perceived by the bicyclists while interacting with other road users. The present paper investigates the injury severity of bicyclists in bicycle-vehicle crashes that occurred in the state of Tamilnadu, India during the nine year period (2009–2017). The analyses demonstrate that dividing bicycle-vehicle collision data into five clusters helps in reducing the systematic heterogeneity present in the data and identify the hidden relationship between the injury severity levels of bicyclists and cyclists demographics, vehicle, environmental, temporal cause for the crashes. Results: Latent Class Clustering (LCC) approach was used in the present study as a preliminary tool for the segmentation of 9,978 crashes. Later, logistic regression analysis was used to identify the factors that influence bicycle crash severity for the whole dataset as well as for the clusters that were obtained from the LCC model. Results of this study show that combined use of both techniques reveals further information that wouldn’t be obtained without prior segmentation of the data. Few variables such as season, weather conditions, and light conditions were significant for certain clusters that were hidden in the whole dataset. This study can help domain experts or traffic safety researchers to segment traffic crashes and develop targeted countermeasures to mitigate injury severity.     

Implicit attitudes towards risky driving behaviors: Evidence of validity for the implicit association test

Introduction: Attitudes toward risky driving behaviors are commonly evaluated through direct self-report measures. Nevertheless, these instruments have limitations, such as socially-desirable responding. This study examines the validity of the Implicit Association Test (IAT) as an indirect measure of attitudes towards risky driving. An IAT with “risky” vs. “safe” driving behaviors categories was evaluated. Method: A sample of 100 participants (ranging from 18 to 70 years of age) completed the IAT and measures of attitudes, driving styles, personality traits, risk-taking (IOWA Gambling Task), and social desirability (Driver Social Desirability Scale). Results: A high level of internal consistency was found for IAT scores. The IAT was correlated with driving styles (risky, dissociative, and careful dimensions), risk-related personality traits (impulsive/sensation seeking and aggression/hostility) and risk-taking measures. IAT scores were also associated with self-reported risky driving behaviors (r = 0.33). As expected, a higher level of negative implicit attitudes was found among young drivers. The driver social desirability scale was correlated with most self-report measures, but not with the IAT. Conclusion: The present study provides reliability and validity evidence for the IAT as an indirect measure of attitudes towards risky driving. The IAT can serve as an important complement to conventional self-report measures of driving attitudes. Practical Applications: Potential use of global measure of implicit attitudes toward risky driving behaviors in the evaluation, education, and training of drivers are discussed.     

“They’re lunatics on the road”: Exploring the normative influences of parents,friends, and police on young novices’ risky driving decisions

PurposeYoung novice drivers experience significantly greater risk of being injured or killed in car crashes than older more experienced drivers. This research utilised a qualitative approach guided by the framework of Akers’ social learning theory. It explored young novice drivers’ perspectives on risky driving including rewards and punishments expected from and administered by parents, friends, and police, imitation of parents’ and friends’ driving, and advantages and disadvantages of risky driving.MethodsTwenty-one young drivers (12 females, 9 males) aged 16–25 years (M = 17.71 years, SD = 2.15) with a Learner (n = 11) or Provisional (n = 10) driver licence participated in individual or small group interviews.Findings and conclusionsContent analysis supported four themes: (1) rewards and (2) punishments for risky driving, and the influence of (3) parents and (4) friends. The young novice drivers differed in their vulnerability to the negative influences of friends and parents, with some novices advising they were able to resist risky normative influences whilst others felt they could not. The authority of the police as enforcers of road rules was either accepted and respected or seen as being used to persecute young novices. These findings suggest that road safety interventions should consider the normative influence of parents and friends on the risky and safe behaviour of young novices. Police were also seen as influential upon behaviour. Future research should explore the complicated relationship between parents, friends, the police, young novices, and their risky driving behaviour.     

Higher-order cycling skills among 11- to 13-year-old cyclists and relationships with cycling experience,risky behavior,crashes and self-assessed skill

IntroductionIn the Netherlands, young cyclists are extremely vulnerable in traffic, which may partly be due to their still underdeveloped higher-order cycling skill. So far, knowledge on their actual level of skill is lacking. Using a computerized test battery mimicking real-life risky traffic conditions, this study assessed the level of higher-order cycling skill in children 11 and 12 years of age and tested the hypothesis that these skills show caveats. Furthermore, factors potentially influencing the development and impact of these skills were studied, such as cycling experience, risky road behavior, crash involvement, and self-assessed skill.MethodA total of 335 students (49% female) completed computerized tests on hazard perception, gap acceptance, blind spot strategies, and priority decisions in traffic, and completed questionnaires on cycling experience, risky cycling behavior, crashes, and self-assessment of cycling skill.ResultsOn the hazard perception test, one-third of the participants missed at least half of the number of hazards. They made errors in about 50% of the priority decisions, accepted critical gaps when crossing the road, and conversely rejected safe gaps; only 1% of the participants identified all blind spots of a truck correctly, while 69% made unsafe decisions when interacting with trucks in traffic scenarios. Overall, in complex traffic situations performance was worse than in simple ones. The hypothesis of lack of skills was therefore accepted. However, the study failed to demonstrate consistent relationships between subtest performance and cycling experience, risky behavior, crashes, and self-assessed skill, which weakens the theoretical assumptions concerning the subtests.ConclusionsThe results suggest that children at the end of primary school are still lacking elementary skills for safe cycling, calling for measures to accelerate skill development.Practical applicationsTest batteries are essential tools for systematically monitoring skill development in cyclists, evaluating education programs, and for guiding the development of effective road safety education. The next step is the validation of such batteries.     

Social environment versus cycling competency predicting risk-taking in 11- to 13-year-old cyclists in The Netherlands

Abstract

Objectives: From age 12 onwards, cycling injuries begin rising in The Netherlands. A known contributing factor is younger children’s underdeveloped competency to deal with complex and hazardous traffic situations, and their exposure to such situations strongly increases after transitioning to secondary school. Little is known about intentional risk-taking as a contributing factor. In this developmental stage, children become increasingly vulnerable because of intentional risk-taking, affecting their safety and health. The incidence, predictors in the child’s social environment, and trends of such risks are systematically monitored; for instance, for alcohol use, smoking, and cyber bullying. Such monitors do not include risky road behavior. This exploratory field study examined the frequency of intentional risky cycling, its relationship with the perceived social environment, and relative to cycling competency measured as the ability to detect emerging hazards quickly.

Methods: Three hundred thirty-five students between 11 and 13 years of age (51% male) completed computerized tests of hazard perception skill and surveys on crashes, risk-taking, peer pressure, perceived risk-taking by parents or friends, and exposure to risky driving as passenger.

Results: Frequent risk-taking was associated with higher crash frequency. Stepwise regression confirmed that children who more often took risks on the road were also more sensitive to peer pressure, had more often been passengers of risky drivers, had parents and friends who exhibited risky behaviors in traffic more often, and perceived hazards as less dangerous but, in contrast to expectations, did not do worse on the detection of hazards. The predictors explained 28% of the variance in total risk-taking but varied from 6 to 20% depending on the specific risk-taking behavior concerned.

Conclusions: At least 20% of children sometimes or more often take risks in traffic. Children who feel peer pressure to behave in a risky manner, observe parents and friends behaving in a risky manner in traffic, and have been exposed as passengers to risky driving more often take risks in traffic themselves. These results provide support for including items on risky road behavior in health monitors and to design interventions that address the risk factors in the child’s perceived social environment.     

Actual and perceived social norms of children’s road crossing behavior

This study compared the actual and perceived social norms regarding road crossing behaviors, and aimed at uncovering a misperception of group norms. The basic notion underlying the study was that if children perceived the behaviors and attitudes of their friends regarding road crossing as more negative than they actually are, this might lead the children to adopt riskier behavior when crossing the road. The participants were comprised of 123 elementary school children (ages from 6 to 13; 78 boys - 65% and 42 girls - 35%) from Beitar-Ilit, a religious city in Israel. A questionnaire especially constructed for the study was administered to the participants. A t-test yielded a significant difference between the child’s own attitudes score and the perceived peers’ attitudes score. On average, children perceive their friends’ attitudes with regard to road crossing behaviors as being more negative compared to their own attitudes. A second t-test yielded a significant difference between the child’s own behavior score and the perceived peers’ behavior score. Children perceived the road crossing behavior of their friends as riskier relative to their own crossing behavior. A regression test revealed that the variables, perceived peers’ attitudes and perceived peers’ behaviors, contributed significantly to the explained variance: the more risky the perceived peers’ attitudes and behaviors with regard to road crossing, the more risky the child’s own behavior when crossing the road. It is hoped that an interventional educational program based on positive norms in the social group will encourage children to exhibit safe behavior in the roads.