Brazilian adaptation of the driving anger expression inventory: testing its psychometrics properties and links between anger behavior,risky behavior,sensation seeking,and hostility in a sample of Brazilian undergraduate students

Introduction: In Brazil, driver aggressiveness in road traffic is a critical issue and could be an important contributing factor to the high number of traffic accidents. Because no instruments are available in Portuguese to register driving aggressiveness or driving anger in Brazil, we adapted English instruments into the Brazilian context. The aims of this study were to provide a Brazilian adaptation of the Driving Anger Expression Inventory (DAX) and to try to validate it by testing its psychometric properties and investigating its relationships with risky driving behaviors (DBQ), road accidents, driving sensation seeking, and hostility. Method: The Brazilian adaptations of the DAX, DBQ, the Driving Sensation Seeking Scale (DSSS) and the hostility Scale were administered to a sample of 512 undergraduate students (with a mean age of 23.7 years, 52.1% men). Results: Confirmatory factor analysis of the Brazilian DAX (DAX-BR) items yielded a four-factor solution with 43 items, which obtained the best goodness-of-fit to the data. Cronbach’s alpha for the DAX-BR factors ranged from 0.69 to 0.88. Other results on validity were a positive correlation (range 0.39–0.59) between the factors of the DAX-BR, DSSS, and DBQ. Conclusion: DAX-BR as the same structure as the original and is a reliable instrument for use with young drivers. Other studies should be conducted to further validate the DAX-BR in different types of populations such as older and more experienced drivers, professional drivers, and traffic regulation offenders whose driver's license has been taken away. Practical applications: This Brazilian version can be recommended for the assessment of driving anger expression in Brazil among young drivers in view of helping them driver more safely, and in particular to reduce traffic violations.     

Continuous performance assessment and improvement of integrated HSE and maintenance systems by multivariate analysis in gas transmission units

In this study, an integrated “Health, Safety, and Environment (HSE)” and maintenance systems are presented. Multivariate analysis is used for continuous performance assessment and improvement of these systems. The two subjects of “Maintenance System” and “HSE” have been individually investigated several times in different studies. However, few studies have been done to integrate these two systems and provide an integrated system for their implementation. This study evaluates current maintenance and HSE systems of a Gas Transmission Unit by Data Envelopment Analysis (DEA) and Principal Component Analysis (PCA). Moreover, decision making units (DMUs) are examined and ranked. Employees are considered as DMUs. This is done through investigating and measuring their efficiencies and identifying the inefficient and less-efficient units. Since an increase in the number of inputs does not lead to an increase in the number of outputs with the same scale, an output-oriented DEA with a Variable Returns to Scale (VRS) is used. The Fuzzy DEA (FDEA) is also used in this research to decrease uncertainty existing in qualitative indicators and human error. Finally, suggestions are given to improve those DMUs. The managers and employees of the gas transmission unit constitute the statistical population of the study. To achieve the objectives of this study, standard questionnaires with respect to HSE and Maintenance system are completed by operators. The proposed approach would help policy makers and top managers of Gas Transmission Company to have a more comprehensive and thorough understanding the working conditions with respect to the maintenance and HSE features.     

An investigation of the relationship between organizational climate and professional drivers’ driver behaviours

The aim of this study was to investigate the relationship between organizational climate and driver behaviours of professional drivers. The sample consisted of 230 male professional drivers. The participants completed a questionnaire including the Driver Behaviour Questionnaire (DBQ), Hofstede’s Organizational Culture Scale, and a background information form. Results of the factor analysis of Hofstede’s Organizational Culture Scale yielded two dimensions, which were named as “work orientation” and “employee consideration”. Analyses of Covariance (ANCOVA) revealed significant main and interaction effects of organizational climate on errors, and violations after controlling for the statistical effects of age, annual mileage and the organization types. Drivers with low scores of work orientation reported significantly higher frequencies of errors and violations than drivers with high scores of work orientation. It was also found that drivers with low scores of employee consideration reported higher frequencies of errors and violations than drivers with high scores of employee consideration. The effect of interaction between work orientation and employee consideration dimensions was only found on the frequencies of violations.     

模式识别在火灾调查中的汽油分类问题的应用研究

在火灾调查中,检测汽油成分并对其进行正确分类尤为重要.运用GC-MS对90#和93#两种普通汽油的共50个样本进行检测,所得的GC-MS原始数据通过PCA方法进行处理,以提取有用信息,避免冗余变量进入后续计算.在此基础上应用KNN方法对这两种汽油助燃剂进行分类.结果表明, KNN方法对这两种汽油的分类准确率达到100%,且当初始数据未经标准化预处理时也能达到同样准确的分类效果.研究表明:将模式识别方法正确地运用到助燃剂鉴定和分类工作中有助于火灾调查.     

Safety culture aboard fishing vessels

Safety at sea is a serious issue for the commercial fishing industry. Injury and fatality rates are between 25 and 40 times the national average in many European counties, Australia and the USA. A 50-item safety culture questionnaire was developed, using items from published research combined with some original items. The questionnaire was distributed to fishermen who completed the responses. A total of 209 questionnaires were collected. Principal Component Analysis (PCA) revealed nine factors, all with a Cronbach’s Alpha higher than 0.68. The factors were tested using ANOVA, t-tests, correlations and regression analysis.The findings indicate significant differences between age groups, vessel types, occupations, and whether or not a close family member is a fisherman. It was also found that the safety attitude of management had a strong influence on a company’s safety policy. Fishermen who had sought medical attention during the preceding year as a result of an accident showed a significantly less positive attitude to rules and regulations and had a less positive safety attitude in general. Fishermen who had been involved in a serious accident/incident showed a significantly more positive attitude to rules and regulations.     

Characteristics of vehicles driven by teens and adults killed in crashes, 2013–2017

Introduction: Teen drivers experience higher crash risk than their experienced adult counterparts. Legislative and community outreach methods have attempted to reduce this risk; results have been mixed. The increasing presence of vehicle safety features across the fleet has driven fatality numbers down in the past decades, but the disparity between young drivers and others remains. Method: We merged Fatality Analysis Reporting System (FARS) data on fatal crashes with vehicle characteristic data from the Highway Loss Data Institute (HLDI). The analysis compared the vehicle type, size, age, and the presence of select safety features in vehicles driven by teens (ages 15–17 years) and adult drivers (ages 35–50 years) who were killed in crashes from 2013 to 2017. Results were compared with a similar analysis conducted on data from 2007 to 2012. Results: Teen drivers were more likely than their adult counterparts to be killed while driving older, smaller vehicles that were less likely to have the option to be equipped with side airbags. Discussion: Teenage drivers remain more likely to be killed while driving older, smaller vehicles than adult drivers. Parents and guardians are mainly responsible for teen vehicle choice, and should keep vehicle size, weight, and safety features in mind when placing their teen in a vehicle. Practical Application: These findings can help guide safer vehicle choice for new teen drivers.     

Validation of not-at-fault driver representativeness assumption for quasi-induced exposure using U.S. national traffic databases

Introduction:The quasi-induced exposure (QIE) method has been widely implemented into traffic safety research. One of the key assumptions of QIE method is that not-at-fault drivers represent the driving population at the time of a crash. Recent studies have validated the QIE representative assumption using not-at-fault drivers from three-or-more vehicle crashes (excluding the first not-at-fault drivers; D3_other) as the reference group in single state crash databases. However, it is unclear if the QIE representativeness assumption is valid on a national scale and is a representative sample of driving population in the United States. The aims of this study were to assess the QIE representativeness assumption on a national scale and to evaluate if D3_other could serve as a representative sample of the U.S. driving population. Method: Using the Fatality Analysis Reporting System (FARS) and the National Occupant Protection Use Survey (NOPUS), distributions of driver gender, age, vehicle type, time, and roadway type among the not-at-fault drivers in clean two-vehicle crashes, the first not-at-fault drivers in three-or-more-vehicle crashes, and the remaining not-at-fault drivers in three-or-more vehicle crashes were compared to the driver population observed in NOPUS. Results: The results showed that with respect to driver gender, vehicle type, time, and roadway type, drivers among D3_other did not show statistical significant difference from NOPUS observations. The age distribution of D3_other driver was not practically different to NOPUS observations. Conclusions: Overall, we conclude that D3_other drivers in FARS represents the driving population at the time of the crash. Practical applications: Our study provides a solid foundation for future studies to utilize D3_other as the reference group to validate the QIE representativeness assumption and has potential to increase the generalizability of future FARS studies.     

Response to commentary on “The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis”

A commentary on our previously published meta-analysis about the predictive validity of the Driver Behaviour Questionnaire (DBQ) raised a number of points. These points do not dispute the quantitative results as such, but suggest that our introduction and discussion overly favor the DBQ and are incomplete in a number of ways. The commentary targeted the following topics: common method variance, intercorrelations of different instruments, accident data validity, correcting for measurement error,

Common method variance

Our meta-analysis provided an extensive discussion of validity threats, including ones not treated before in the DBQ literature, such as common scale anchors and publication bias. We see little added value in the commentary when it informs the readership of common method variance (CMV), as we clearly did this in our article. It is widely understood that CMV can account for a large share of the variance when self-reported data are intercorrelated (see Podsakoff, MacKenzie, Lee, & Podsakoff, 2003

Intercorrelations of different instruments

The commentary reacts to an introductory sentence in which we stated that the DBQ is strongly situated in a network of other questionnaires and tests (such as Trait Anxiety, Cognitive Failures Questionnaire, and Sensation Seeking Scale), by asserting that we seem to interpret such correlations as a positive feature of the DBQ and by pointing out that correlations between the DBQ and other self-reports may have arisen spuriously because of CMV.We dispute the assertion that we regard correlations

Accident data validity

The commentary rejects our position that not only self-reported accident data are susceptible to biases, but recorded data too. Note that our remark applied to all types of recorded accidents, including police reports, hospital data, insurance data, as well as fleet data from professional drivers, and not just company data as in the work by af Wåhlberg, Dorn, and Kline (2011), which is mentioned in the commentary. The literature discusses several sources of bias for recorded accidents that are

Correcting for unreliability

The commentary pointed out that our correction for attenuation is unusual, a surprising claim considering the established importance of correction for measurement error in theory testing (Liu and Salvendy, 2009, Schmidt and Hunter, 1999). The available DBQ research provided almost no information on measurement error, so we did not apply a correction as part of the meta-analysis. Instead, we applied one afterwards, based on the raw data of the largest DBQ study available, and illustrated that

Exposure

The commentary points out that our results were not corrected for exposure in any way. First of all, this statement is false, because our meta-analysis did include effect sizes corrected for exposure. We used a special moderator category for effect sizes other than zero-order correlations. These effect sizes were derived from regression analysis, often with mileage as one of the predictors.Second, it may be noted that af Wåhlberg himself reported that the association between exposure and

Further references

The commentary attended us to 11 studies supposedly not included in our meta-analysis. We appreciate af Wåhlberg and Dorn's close scrutiny of our reference list for potential omissions on the DBQ-accident relationship. It may be noted that missing a small fraction of studies in a meta-analysis of this scope is almost inevitable.The samples of four of the studies (Dobson et al., 1999, Elliott et al., 2007, Parker, 1999, Stradling et al., 2005) identified in the commentary were already included

Discussion

The purpose of a meta-analysis is to provide a quantitative summary of a metric of interest, correlations between the DBQ, and external criteria in our case. af Wåhlberg and Dorn's commentary does not dispute the quantitative results in themselves (except with regard to the correction for exposure), but targets the qualitative introduction and discussion of our article.The commentary raises some valid points, albeit points already discussed in our article. We too believe that common method

     

企业安全氛围测评的实证研究

安全氛围是影响企业安全生产的重要因素,首先在理论分析的基础上明确安全氛围的定义及其包含的主要研究内容,提出安全氛围构成的关键元素,开发测评工具,并构建基于主成分分析法和四分象限图分析法的测评数据分析模型。采用主成分分析法具体描述各关键元素对企业安全氛围的影响度值;应用四分象限图分析法进一步分析,根据元素的影响度值将元素划分至"优势区"、"优先改进区"、"深入改进区"和"维持优势区"4个区域,为企业改进安全氛围提供更为具体直观的参考。提出的测评工具及测评数据的定量分析模型在一定程度上克服定性评价的不足,可以在不同类型的企业应用。     

Personality of young drivers in Oman: Relationship to risky driving behaviors and crash involvement among Sultan Qaboos University students

Objective: Drivers’ behaviors such as violations and errors have been demonstrated to predict crash involvement among young Omani drivers. However, there is a dearth of studies linking risky driving behaviors to the personality of young drivers. The aim of the present study was to assess such traits within a sample of young Omani drivers (as measured through the behavioral inhibition system [BIS] and the behavioral activation system [BAS]) and determine links with aberrant driving behaviors and self-reported crash involvement.

Methods: A cross-sectional study was conducted at the Sultan Qaboos University that targeted all licensed Omani's undergraduate students. A total of 529 randomly selected students completed the self-reported questionnaire that included an assessment of driving behaviors (e.g., Driver Behaviour Questionnaire, DBQ) as well as the BIS/BAS measures.

Results: A total of 237 participants (44.8%) reported involvement in at least one crash since being licensed. Young drivers with lower BIS–Anxiety scores and higher BAS–Fun Seeking tendencies as well as male drivers were more likely to report driving violations. Statistically significant gender differences were observed on all BIS and BAS subscales (except for BAS–Fun) and the DBQ subscales, because males reported higher trait scores. Though personality traits were related to aberrant driving behaviors at the bivariate level, the constructs were not predictive of engaging in violations or errors. Furthermore, consistent with previous research, a supplementary multivariate logistic regression analysis revealed that only driving experience was predictive of crash involvement.

Conclusions: The findings highlight that though personality traits influence self-reported driving styles (and differ between the genders), the relationship with crash involvement is not as clear. This article further outlines the key findings of the study in regards to understanding core psychological constructs that increase crash risk.     

基于PCA-AHPSO-SVR的煤层瓦斯含量预测研究

为了提高煤层瓦斯含量预测的准确性和科学性,通过主成分分析方法对影响煤层瓦斯含量的7个因素进行特征提取,消除影响因素之间的相关性,减少维度;用支持向量回归机对提取的因素进行训练,并用改进的自适应混合粒子群算法对SVR的参数进行优化,提出PCA-AHPSO-SVR模型;与PCA-PSO-SVR,PSO-SVR这2个模型在相同环境下进行30次运行比较。研究结果表明:研究提出的PCA-AHPSO-SVR模型较其他2种模型平均准确率分别提高5.51%和9.32%,稳定性更佳,可满足工程实际需求。     

Alcohol is a predictor of mortality in motor vehicle collisions

IntroductionIt is well recognized that driving while intoxicated increases the probability of a motor-vehicle collision (MVC). The effect of alcohol on the chance of surviving the MVC is less clear. Method: Using data from the Fatality Analysis Reporting System (FARS) we conducted analyses for the outcome of mortality using alcohol and other variables as predictors. We also selected alcohol positive (AP) and alcohol negative (AN) persons from the same MVC and vehicle to control for confounding characteristics. Results: The odds ratio (OR) for mortality for alcohol positive drivers was 2.57, (p < 0.001 for all the following OR). Other harmful predictive factors were age OR 1.01 per year, vehicle age OR 1.05 per year, male sex OR 1.23, avoidance maneuver OR 1.09, speed related OR 2.89, rollover mechanism OR 2.75, and collision with a fixed object OR 6.70. Protective factors were proper restraint use – OR 0.19 and collision with another moving vehicle, OR 0.21. In the multivariate analysis the OR of mortality for AP vs AN was 1.46. Proper restraint use (OR 0.27) remained protective along with collision with another moving vehicle. When AP and AN persons from the same MVC and the same vehicle were compared, the adjusted OR’s for mortality were 1.46 and 2.08, respectively. Conclusions: Alcohol is an independent predictor of mortality in an MVC. Proper restraint use is the strongest protective factor. This finding allows a more complete understanding of the risks of driving while intoxicated, not only a higher probability of an MVC, but decreased survival once the MVC occurs. Practical Applications: Identification of alcohol as an independent predictor of mortality in an accident may improve risk assessment and influence drivers to avoid driving while intoxicated.     

Drivers’ visual scanning behavior at signalized and unsignalized intersections: A naturalistic driving study in China

Introduction: Intersections are the most dangerous locations in urban traffic. The present study aims to investigate drivers’ visual scanning behavior at signalized and unsignalized intersections. Method: Naturalistic driving data at 318 green phase signalized intersections and 300 unsignalized ones were collected. Drivers’ glance allocations were manually categorized into 10 areas of interest (AOIs), based on which three feature subsets were extracted including glance allocation frequencies, durations and AOI transition probabilities. The extracted features at signalized and unsignalized intersections were compared. Features with statistical significances were integrated to characterize drivers’ scanning patterns using the hierarchical clustering method. Andrews Curve was adopted to visually illustrate the clustering results of high-dimensional data. Results: Results showed that drivers going straight across signalized intersections had more often glances at the left view mirror and longer fixation on the near left area. When turning left, drivers near signalized intersections had more frequent glances at the left view mirror, fixated much longer on the forward and rearview mirror area, and had higher transition probabilities from near left to far left. Compared with drivers’ scanning patterns in left turning maneuver at signalized intersections, drivers with higher situation awareness levels would divide more attention to the forward and right areas than at unsignalized intersections. Conclusions: This study revealed that intersection types made differences on drivers’ scanning behavior. Practical applications: These findings suggest that future applications in advanced driver assistance systems and driver training programs should recommend different scanning strategies to drivers at different types of intersections.     

Driving anger and its expressions: further evidence of validity and reliability for the Driving Anger Expression Inventory French adaptation

Introduction: The aims of this study were to provide further evidence of validity and reliability for the Driving Anger Expression Inventory (DAX) French adaptation (Villieux & Delhomme, 2008, Le Travail Humain, 71(4), 359-384) and to investigate the relationships between driving anger, how people express their anger while driving, and traffic violations among young drivers in France. Method: The French adaptations of the DAX, of the Driving Anger Scale (DAS), and of the Extended Violations Scale were administered to a sample of 314 drivers. Results: Confirmatory factor analysis of the French DAX items yielded a three factors solution with 11 items, which obtained better goodness-of-fit to the data. Cronbach α reliabilities for DAX factors ranged from .71 to .79. Aggressive forms of anger expression correlated positively with driving anger and traffic violations whereas the 'Adaptive/Constructive Expression' factor correlated negatively with these variables. Discussion: Globally, our results replicated earlier findings and showed that DAX factors are useful predictors of self reported violations and complement established measures like the DAS. Impact on Industry: Implications for driver education and interventions were examined.     

Combinations of factors contribute to young driver crashes

Introduction: Motor-vehicle crashes are a leading cause of death in adolescence and young adults. A multitude of factors, including skill level, inexperience, and risk taking behaviors are associated with young drivers’ crashes. This research investigated whether combinations of factors underlie crashes involving young drivers. Method: A retrospective longitudinal study was conducted on population-wide one- and two-car crashes in Great Britain during years 2005–2012 per driver age (17–20, 21–29, 30–39, 40–49) and sex. Reporting officers provided their assessment of the factors contributing to crashes. Principal components analysis was conducted to identify combinations of factors underlying young drivers’ crashes. Factor combinations, including challenging driving conditions, risk taking behaviors, and inexperience were implicated in young drivers’ crashes. Results: Combinations of factors reveal new insights into underlying causes of crashes involving young drivers. One combination revealed that slippery roads due to poor weather pose greater risk to young drivers who are inexperienced and likely to exceed the appropriate speed. The findings motivate new policy recommendations, such as educating young drivers about the importance of adjusting their speed to the road conditions.     

Evaluating 24/7 Sobriety Program participant reoffense risk

Objective: Our study investigated risk factors in survival among a subpopulation of drivers in North Dakota’s 24/7 Sobriety Program. Participants mandated for a second driving-under-the-influence of alcohol (DUI) arrest were studied for a three-year interval that commenced with the start date for a 360-day enrollment. Method: A Stratified Cox regression model was developed to compute the hazard ratios for survival. A subsequent DUI-related offense as event of interest. Relation to the explanatory variable array that could be construed from administrative records were investigated. Results: Older drivers were 6.31 times more likely to reoffend than the younger driver cohort of 18–35-years. The survival curve slope showed the fastest decline in the 361-day to 730-day interval. Neither gender nor residence region was a significant predictor in DUI reoffense over the three-year monitoring interval. Preliminary work suggests reoffense was more likely if an individual had program history prior to this court mandated 360-day term in the 24/7 Sobriety Program for a second DUI. The program experience finding was unexpected but could not be studied in greater detail due to data and resource limitations. Conclusions: Administrative records access created a novel opportunity to explore an evolving impaired driving prevention strategy that has shown early promise. Individual driver survival in and after the 24/7 Sobriety Program was studied for three-years. Findings show age, post-program time interval, and possibly program history as areas to explore to improve survival rates. Driver DUI offense were most common shortly after program completion. Although limited to a single state, findings increase knowledge for refining strategies designed to impact driver subpopulations at higher risk for reoffense.     

"The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis" Comments

A previously published meta-analysis of the predictive power of the Manchester Driver Behaviour Questionnaire (DBQ) versus road traffic crashes is criticized upon a number of counts, including the incomplete handling of common method variance, failure to control for exposure and how the correction for unreliability of the accident variable was undertaken. It is concluded that the results reported, and the conclusions drawn from these, are too favorable to the DBQ, despite the effect sizes being

Common method variance

The main problem associated with the interpretation of the DBQ/accidents association is common method variance (i.e., systematic biases in the self-reports used), which create part or all of the associations found (Chang et al., 2010, Podsakoff et al., 2003). Common method variance may be due to a number of different factors, and in some studies, substantial effects have been found (e.g., Hessing, Elffers, &; Weigel, 1988; for reviews see Cote and Buckley, 1987, Podsakoff et al., 2003). This

Conclusions

To summarize, we believe that the meta-analysis of de Winter and Dodou is somewhat too favorable to the DBQ by failing to make the above points. Yet we paradoxically agree with de Winter and Dodou in one of their conclusions and recommendations; more studies using other-source criteria are needed. The self-report-source only data are not reliable, and conclusions about the predictive power of the DBQ factors versus traffic safety are not yet possible to draw.

     

A data mining approach to deriving safety policy implications for taxi drivers

Introduction: Traffic safety issues associated with taxis are important because the frequency of taxi crashes is significantly higher than that of other vehicle types. The purpose of this study is to derive safety implications to be used for developing policies to enhance taxi safety based on analyzing intrinsic characteristics underlying the cause of traffic accidents. Method: An in-depth questionnaire survey was conducted to collect a set of useful data representing the intrinsic characteristics. A total of 781 corporate taxi drivers participated in the survey in Korea. The proposed analysis methodology consists of two-stage data mining techniques, including a random forest method, with data that represents the working condition and welfare environment of taxi drivers. In the first stage, the drivers’ intrinsic characteristics were derived to classify four types of taxi drivers: unspecified normal, work-life balanced, overstressed, and work-oriented. Next, priority was determined for classifying high-risk taxi drivers based on factors derived from the first analysis. Results: The derived policies can be categorized into three groups: ‘the development of new policies,’ ‘the improvement of existing policies,’ and ‘the elimination of negative factors.’ Establishing a driving capability evaluation system for elderly drivers, developing mental health management programs for taxi drivers, and inspecting the taxi's internal conditions were proposed as new policies. Improving the driver's wage system, supporting the improvement of rest facilities, and supporting the installation of security devices for protecting taxi drivers are methods for improving existing policies to reinforce the traffic safety of taxi drivers. Last, restricting overtime work for taxi drivers was proposed as a policy to eliminate negative factors for improving taxi traffic safety. Practical Applications: It is expected that by devising effective policies using the policy implications suggested in this study, taxi traffic accidents can be prevented and the quality of life of taxi drivers can be improved.     

Cycle Aware: Piloting a module for novice drivers

Introduction: In low-cycling countries, motor-vehicle traffic and driver behavior are well known barriers to the uptake of bicycles, particularly for utility cycling. Lack of separation between cyclists and faster-moving traffic is one key issue, while attitudes of drivers toward and/or harassment of cyclists is another. Cyclist-related driver education has been recommended as a means to improve driver-cyclist interactions. Methods: The driver licensing process provides an opportunity for such education. The Cycle Aware module was developed to test and enhance novice drivers’ knowledge of interacting safely with cyclists. It was piloted across three Australian jurisdictions targeting both novice and experienced drivers. Participants were asked to complete the Cycle Aware module and an accompanying survey. A total of 134 novice and 97 experienced drivers completed the survey with 42 novice and 50 experienced drivers going on to complete the module. Results: Both groups of drivers scored equally well in the module but the very youngest and very oldest participants were more likely to have some incorrect responses. We did not find any relationship between correct module scores and attitudes toward cyclists. Survey results showed both novice and experienced drivers had somewhat positive attitudes toward cyclists. The two cohorts differed on several attitude questions. Sixty percent (60%) of novices compared to 30% of experienced drivers reported feeling concerned when sharing the road with cyclists, and novices were less likely to agree that cyclists had a right to use the roads. Conclusions and practical applications: The analysis suggests novices need to be better equipped to share roads confidently with cyclists and to recognize cyclists as legitimate traffic participants.