Validation of the Driver Behaviour Questionnaire in a representative sample of drivers in Australia

The Driver Behaviour Questionnaire (DBQ) is a widely used measure of driving behaviours that may increase a driver's risk of crash involvement. However, there are several different versions of the DBQ varying in terms of number of items and factor structure. The aim of the current research was to assess the construct validity of the popular 28-item four-factor DBQ solution in a representative sample of drivers in Australia. A further aim was to test the factorial invariance of the measure across gender, age and also between fleet and non-fleet drivers using multigroup confirmatory factor analyses. Data on a range of attitudes towards road safety were collected using an online survey. A stratified sampling procedure was undertaken to ensure the age, gender and location distributions of participants were representative of the Australian population. A total of 2771 responses were obtained from fully licensed motor vehicle drivers (male: 46%). Confirmatory factor analysis supported the 28-item four-factor DBQ in the Australian sample. The DBQ was also found to be gender-invariant and strong partial measurement invariance was found for drivers aged from 26 to 64, but not for younger (17–25) or older (65–75) drivers. Modifications to the DBQ suggest how the DBQ can be improved for use in these two age groups.     

Elderly drivers: Future challenges?

The objective of this paper is to describe and interpret the results from a public opinion poll about elderly drivers to provide useful information regarding future challenges related to elderly drivers. The introduction describes demographic developments, factors affecting elderly drivers, crash rates of elderly drivers and characteristics of crashes of elderly drivers. This information is used to provide a context to interpret the results of the public opinion poll. A total of 1238 drivers completed the interview, which required an average of approximately 15 min per respondent. It was administered by telephone to a random sample of Canadian drivers by Opinion Search Inc., in September 2007. Criteria for inclusion were having a valid driver's license and having driven in the past 30 days. Data were weighted according to region, gender and age to avoid bias. Univariate frequency distributions, their 95% confidence intervals and Chi-square statistics were calculated taking account of the stratified and weighted sampling design. Also, multivariate logistic regression was performed, accounting for the design effects of the used sampling design. Lower levels of concern about the issue of elderly drivers were found among the public at large and especially among elderly drivers. While general support for actions to protect elderly drivers was high, elderly drivers were less supportive for a measure requiring them to complete training to maintain their driving privileges. The results from this survey are contrasted against what is known from the literature about the issue of elderly drivers and conclusions regarding future challenges are drawn.     

French validation of a new version of the Driver Behavior Questionnaire (DBQ) for drivers of all ages and level of experiences

The purpose of this study was to validate a new version of the Driver Behavior Questionnaire (DBQ) on a sample of French drivers in order to gain a better understanding of different driver behaviors, by differentiating two types of violations (aggressive and ordinary), three types of errors (dangerous, inattention and inexperience) and by taking positive behaviors into account. 525 drivers (205 men and 320 women), between 18 and 79 years of age, filled in a questionnaire on line including the 41 items in the new version of the DBQ and information relative to their mobility and their accident history. Exploratory factor analysis confirmed a six-factor structure: “dangerous errors”, “inattention errors”, “inexperience errors”, “ordinary violations”, “aggressive violations” and “positive behaviors”. A revised version with 23 items of the new version of the DBQ was produced by selecting the items that loaded most strongly on the six factors. The results also showed the link between demographic variables (age and gender), mobility (kilometers driven weekly), the DBQ scores and the involvement in an accident in the previous five years. This study permitted to validate a more detailed version of the “Driving Behavior Questionnaire” among French drivers of all age and all level of experience.     

Driver licenses as a measure of older drivers' exposure: a methodological note

The limitations of the number of driver licenses as an estimate of driving exposure were demonstrated by comparing Finnish and Swedish driver licensing practices, licensing rates and accident rates of older drivers. In Sweden, there is no screening for older license holders, and most of them keep their licenses for life. In Finland, there is a heavy and costly medico-legal control system for older license holders, leading to both screening and self-screening. Consequently, in the two countries, the numbers of driver licenses do not reflect the numbers of active older drivers in the same manner. This difference affects the comparative accident statistics: with respect to population, Finland and Sweden have similar age trends in accidents risk, but with respect to the number of driver licenses, the Finnish older drivers seem to have a higher risk of accident than the Swedish ones. It is concluded that if group comparisons of accident risk are presented using the number of driver licenses as an estimate of exposure, the licensing legislation and practice should affect all the groups in an identical manner for the comparison to be valid.     

Road accidents caused by drivers falling asleep

About 29600 Norwegian accident-involved drivers received a questionnaire about the last accident reported to their insurance company. About 9200 drivers (31%) returned the questionnaire. The questionnaire contained questions about sleep or fatigue as contributing factors to the accident. In addition, the drivers reported whether or not they had fallen asleep some time whilst driving. and what the consequences had been. Sleep or drowsiness was a contributing factor in 3.9% of all accidents, as reported by drivers who were at fault for the accident. This factor was strongly over-represented in night-time accidents (18.6%), in running-off-the-road accidents (8.3%), accidents after driving more than 150 km on one trip (8.1%), and personal injury accidents (7.3%). A logistic regression analysis showed that the following additional factors made significant and independent contributions to increasing the odds of sleep involvement in an accident: dry road, high speed limit, driving one's own car, not driving the car daily, high education, and few years of driving experience. More male than female drivers were involved in sleep-related accidents, but this seems largely to be explained by males driving relatively more than females on roads with high speed limits. A total of 10% of male drivers and 4% of females reported to have fallen asleep while driving during the last 12 months. A total of 4% of these events resulted in an accident. The most frequent consequence of falling asleep--amounting to more than 40% of the reported incidents--was crossing of the right edge-line before awaking, whereas crossing of the centreline was reported by 16%. Drivers' lack of awareness of important precursors of falling asleep--like highway hypnosis, driving without awareness, and similar phenomena--as well as a reluctance to discontinue driving despite feeling tired are pointed out as likely contributors to sleep-related accidents. More knowledge about the drivers' experiences immediately preceding such accidents may give a better background for implementing effective driver warning systems and other countermeasures.     

Measuring errors and violations on the road: A bifactor modeling approach to the Driver Behavior Questionnaire

The Driver Behavior Questionnaire (DBQ) is a self-report measure of driving behavior that has been widely used over more than 20 years. Despite this wealth of evidence a number of questions remain, including understanding the correlation between its violations and errors sub-components, identifying how these components are related to crash involvement, and testing whether a DBQ based on a reduced number of items can be effective. We address these issues using a bifactor modeling approach to data drawn from the UK Cohort II longitudinal study of novice drivers. This dataset provides observations on 12,012 drivers with DBQ data collected at .5, 1, 2 and 3 years after passing their test. A bifactor model, including a general factor onto which all items loaded, and specific factors for ordinary violations, aggressive violations, slips and errors fitted the data better than correlated factors and second-order factor structures. A model based on only 12 items replicated this structure and produced factor scores that were highly correlated with the full model. The ordinary violations and general factor were significant independent predictors of crash involvement at 6 months after starting independent driving. The discussion considers the role of the general and specific factors in crash involvement.     

The influence of driver distraction on the severity of injuries sustained by teenage drivers and their passengers

Studies show that teenage drivers are at a higher risk for crashes. Opportunities to engage in technology and non-technology based distractions appear to be a particular concern among this age group. An ordered logit model was developed to predict the likelihood of a severe injury for these drivers and their passenger using a national crash database (the 2003, U.S. DOT-General Estimate System [GES]). As one would expect, speeding substantially increases the likelihood of severe injuries for teenage drivers and their passengers. The results of the analysis also reveal that teenage drivers have an increased likelihood of more severe injuries if distracted by a cell phone or by passengers than if the source of distraction was related to in-vehicle devices or if the driver was inattentive. Additionally, passengers of teenage drivers are more likely to sustain severe injuries when their driver is distracted by devices or passengers than with a non-distracted or inattentive driver. This supports the previous literature on teenage drivers and extends our understanding of injuries for this age group related to distraction-related crashes.     

Superstition,risk-taking and risk perception of accidents among South African taxi drivers

The aim of this study was to investigate taxi drivers' superstition and risk perception of accidents as well as risk-taking in an urban area in South Africa. One hundred and thirty drivers of minibuses, so-called "taxis" were interviewed on the basis of: (1) a superstition scale; (2) a risk-taking scale; (3) a list of perceived causes of road traffic accidents. Drivers showed largely superstitious attitudes and expressed a high degree of risk-taking behavior.Superstition was positively correlated with the number of self-reported accidents the drivers had been involved in and the number of accidents they had witnessed. Path analysis revealed a direct path from superstition to accident involvement while the influence of formal education was negligible. Risk-taking was inversely correlated with driving experience and the number of accidents witnessed but not so with the number of accidents involved in. There was no clear pattern of associations between superstition and risk-taking and perceived causes of accidents. Superstition and risk-taking were slightly and inversely correlated with each other. It is concluded that superstition represents an attitude that is associated with a driver's accident risk, and further research on superstitious attitudes among South African drivers is advocated.     

Killer crashes: Fatal road traffic accidents in the UK

Road traffic accidents are responsible for over 3000 deaths per year in the UK, according to Department for Transport (2004a) figures. Although progress is being made in a number of areas, vehicle occupant fatalities have not been falling in line with casualty reduction targets for the year 2010. A sample of 1185 fatal vehicle occupant cases was considered, from ten UK police forces, from the years 1994-2005 inclusive. The main findings were: (1) over 65% of the accidents examined involved driving at excessive speed, a driver in excess of the legal alcohol limit, or the failure to wear a seat belt by a fatality, or some combination of these. (2) Young drivers have the great majority of their accidents by losing control on bends or curves, typically at night in rural areas and/or while driving for ‘leisure’ purposes. These accidents show high levels of speeding, alcohol involvement and recklessness. (3) Older drivers had fewer accidents, but those fatalities they were involved in tended to involve misjudgement and perceptual errors in ‘right of way’ collisions, typically in the daytime on rural rather than urban roads. Blameworthy right of way errors were notably high for drivers aged over 65 years, as a proportion of total fatal accidents in that age group.     

Re-conceptualising the reckless driving behaviour of young drivers

Reckless driving is a major contributing factor to road morbidity and mortality. While further research into the nature and impact of reckless driving, particularly among young people, is urgently needed, the measurement of reckless driving behaviour also requires increased attention. Three major shortcomings apparent in established measures of driver behaviour are that they do not target the full range of reckless driving behaviours, they measure characteristics other than driving behaviours, and/or they fail to categorise and label reckless driver behaviour based on characteristics of the behaviours themselves. To combat these shortcomings, this paper reports the development and preliminary validation of a new measure of reckless driving behaviour for young drivers. Exploratory factor analysis of self-reported driving data revealed four, conceptually distinct categories of reckless driving behaviour: those that increase crash-risk due to (a) distractions or deficits in perception, attention or reaction time (labelled “distracted”), (b) driving under the influence of drugs or alcohol (labelled “substance-use”), (c) placing the vehicle in an unsafe environment beyond its design expectations (labelled “extreme”), and (d) speed and positioning of the vehicle relative to other vehicles and objects (labelled “positioning”). Confirmatory factor analysis of data collected from a separate, community sample confirmed this four-factor structure. Multiple regression analyses found differences in the demographic and psychological variables related to these four factors, suggesting that interventions in one reckless driving domain may not be helpful in others.     

Cars and distraction: How to address the limits of Driver Monitoring Systems and improve safety benefits using evidence from German young drivers

We are facing an increase in the emergence of distracting activities while driving. This is especially the case for young people who, more than other age groups, employ their cars as a place of personal fulfilment. This study proposes an interdisciplinary safe-by-design (SbD) heuristic to address this emerging risk. It harnesses a German version of the Behaviour of Young Novice Driver Scale (BYNDS) to gather representative information about young people's distracting activities. This information is then used to address to limitations of Driver Monitoring Systems (DMS) and posit safety measures in the context of young driver distraction. Our novel approach reveals three recommendations that should guide the employment of DMS in future generations of cars. We argue that the sole use of DMS Type 1 (i.e. vehicle motion data) is not sufficient to cope with the complex range of distracting activities that occur inside the car. We suggest designers and technologists employ DMS Type 2 (i.e. cameras and acoustic sensors) as this makes it possible to capture rich information about humans, objects and their interaction. In light of concerns about data privacy, policymakers must act to regulate the ethical use of data from the inside of the car and to find the necessary trade-off between data privacy and the unnecessary attrition of young human lives. This research provides a reasonable foundation for this discussion.     

Young driver accidents in the UK: the influence of age, experience, and time of day

Young drivers, especially males, have relatively more accidents than other drivers. Young driver accidents also have somewhat different characteristics to those of other drivers; they include single vehicle accidents involving loss of control; excess speed for conditions; accidents during darkness; accidents on single carriageway rural roads; and accidents while making cross-flow turns (i.e. turning right in the UK, equivalent to a left turn in the US and continental Europe). A sample of over 3000 accident cases was considered from midland British police forces, involving drivers aged 17-25 years, and covering a two year period. Four types of accident were analysed: right-turns; rear-end shunts; loss of control on curves; and accidents in darkness. Loss of control on curves and accidents in darkness were found to be a particular problem for younger drivers. It was found that cross-flow turn accidents showed the quickest improvement with increasing driver experience, whereas accidents occurring in darkness with no street lighting showed the slowest rate of improvement. 'Time of day' analyses suggested that the problems of accidents in darkness are not a matter of visibility, but a consequence of the way young drivers use the roads at night. There appears to be a large number of accidents associated with voluntary risk-taking behaviours of young drivers in 'recreational' driving.     

Measurement invariance of the Driver Behavior Questionnaire across samples of young drivers from Finland and Ireland

This article investigates the factor structure of the 27-item Driver Behavior Questionnaire (DBQ) in two samples of young drivers (18–25 years of age); one from Finland and the other from Ireland. We compare the two-, three-, and four-factor solutions using Confirmatory Factor Analysis (CFA) and show that the four-factor model (with the latent variables rule violations, aggressive violations, slips and lapses) fits the data from the two countries best. Next, we compare the fit of this model across samples by the means of a measurement invariance analysis in the CFA framework. The analysis shows that the four-factor model fails to fit both samples equally well. This is mainly because the socially-oriented latent variables (rule violations and aggressive violations) are different in nature in the two samples. The cognitively-oriented latent variables (slips and lapses) are, however, similar across countries and the mean values of slips can be compared using latent variable models. However, the common practice of calculating sum scores to represent the four latent DBQ variables and comparing them across subgroups of respondents is unfounded, at least when comparing young respondents from Finland and Ireland.     

Personality and behavioral predictors of traffic accidents: testing a contextual mediated model

A contextual mediated model was proposed to distinguish the distal (i.e. personality factors) and proximal (i.e. aberrant driving behaviors) factors in predicting traffic accident involvement. Turkish professional drivers (N=295) answered a questionnaire including various measures of personality factors, driver behaviors, and accident history. Results of the latent variable analysis with LISREL indicated that latent variables in the distal context (i.e. psychological symptoms, sensation seeking, and aggression) predicted at least one of the proximal elements (i.e. aberrant behaviors, dysfunctional drinking, and preferred speed) with relatively high path coefficients. While aberrant driver behaviors yielded a direct effect on accident involvement, psychological symptoms yielded an indirect effect mediated by driver behaviors. Further analyses revealed that personality factors had an impact on road accidents via their effects on actual driving-related behaviors although the path coefficients in predicting accidents were relatively weaker than those predicting risky driving behaviors and habits. Results were discussed considering the implications for classifying the accident correlates in a contextual framework and binominal-poisson distribution of self-reported accidents.     

Relationships between interest in motor racing and driver attitudes and behaviour amongst mature drivers: an Australian case study

Interest in motor racing is investigated as a possible source of influence on driver attitudes toward speeding and driver behaviour. Previous studies have identified links between motor racing and road accidents on public roads. One study found that the level of interest in motor racing was positively correlated with risky driving behaviours of young male drivers. This paper outlines a conceptual framework for investigating the association between interest in motor racing and speeding violations on public roads. A sample survey of households in Queanbeyan, NSW, was used to examine the relationship between the level of interest in motor racing and attitudes to speeding and driving violations in a group of mature drivers. Results indicate that the level of interest in motor racing is significantly related to attitudes towards speeding, controlling for age, education level and sensation seeking propensity. Higher levels of interest in motor racing are associated with higher pro-speeding attitudes. Unlike the previous research on young male drivers, there was no significant relationship between interest in motor racing and speeding violations for this study of mature drivers. The implications of the study for road safety interventions are discussed.     

Elderly drivers’ everyday behavior as a predictor of crash involvement—Questionnaire responses by drivers’ family members

When or whether elderly drivers stop driving is concerning not only to the drivers themselves but also to their family members. Therefore, it is important for family members to take the initiative if they wish to obtain information on the likelihood of the drivers’ involvement in crashes. On the basis of the older drivers’ Everyday Behavior Questionnaire (EBQ) developed in this paper, we attempt to predict drivers’ involvement in crashes using the responses given by their family members. The results revealed that this 14-item questionnaire has a sufficient level of internal consistency as well as a significant correlation (r = 0.29) with the experience of involvement in crashes in the last three years (p < 0.01). Although the EBQ is a proxy-reported questionnaire and does not include items directly related to driving behaviors, the correlation between the EBQ and crash involvement is stronger than that of the self-reported Driver Behavior Questionnaire reported in deWinter and Dodou (2010), who conducted a meta-analysis and estimated the overall correlation among samples of earlier studies. In addition, logistic regression analysis showed that the EBQ score and the exposure to driving risks, measured by the frequency of driving, are significant predictors of involvement in crashes.     

Previous convictions or accidents and the risk of subsequent accidents of older drivers

The over-involvement of elderly drivers in collisions has a potentially adverse effect on highway safety. The question for most experts in traffic research is whether we can predict the individual risk of accidents and which variables are the best predictors, especially for this population. For a better understanding of the elderly drivers' problems, this study aimed to describe the most common types of accidents in the elderly population of drivers living in Quebec (> or = 65 years of age). The second objective of the study was to analyse the relationship between previous accidents or convictions and the risk of subsequent accidents. The results show that: (1) elderly drivers are characterised by error accidents involving more than one car, especially at intersections, (2) prior accidents are a better predictor for accident risk than prior convictions and (3) these trends steadily increase with each age group (drivers 65 years old to 80 years or more). The results are discussed in relation to the literature on risk behaviour of the elderly drivers.     

Modernization of the Driver Behaviour Questionnaire

IntroductionThe current study builds on previous versions of the Driver Behaviour Questionnaire (DBQ) by incorporating a larger sample of driving behaviors targeting inattention, distraction, aggressive driving, and health related to aging. The goals of this study were to determine if the resulting factor structure was consistent with a more contemporary view of unsafe driving behaviors, and to determine whether scores on the factors could predict self-reported collisions and police citations.MethodsThe instrument was given to a sample of 3295 drivers ranging in age from 19 to 80+ years old. It was divided in two sections, the first to provide demographic information and driving history data and the second containing 105 driver behavior questions.ResultsAn exploratory factor analysis resulted in a 65-item scale organized in four factors. The factors were labeled tentatively as Inattention Errors, Age-Related Problems, Distraction and Hurry, and Aggressive Violations. Regression analyses showed that the factors were predictors of self-reported, at-fault collisions and police citations.Practical implicationsThe factor scores found in this research are consistent with a useful theoretical framework for understanding unsafe driver actions, and demonstrate some potential to identify several individual difference variables that predict self-reported collisions and citations.     

Reliability of drivers in urban intersections

The concept of human reliability has been widely used in industrial settings by human factors experts to optimise the person-task fit. Reliability is estimated by the probability that a task will successfully be completed by personnel in a given stage of system operation. Human Reliability Analysis (HRA) is a technique used to calculate human error probabilities as the ratio of errors committed to the number of opportunities for that error. To transfer this notion to the measurement of car driver reliability the following components are necessary: a taxonomy of driving tasks, a definition of correct behaviour in each of these tasks, a list of errors as deviations from the correct actions and an adequate observation method to register errors and opportunities for these errors. Use of the SAFE-task analysis procedure recently made it possible to derive driver errors directly from the normative analysis of behavioural requirements. Driver reliability estimates could be used to compare groups of tasks (e.g. different types of intersections with their respective regulations) as well as groups of drivers’ or individual drivers’ aptitudes. This approach was tested in a field study with 62 drivers of different age groups. The subjects drove an instrumented car and had to complete an urban test route, the main features of which were 18 intersections representing six different driving tasks. The subjects were accompanied by two trained observers who recorded driver errors using standardized observation sheets. Results indicate that error indices often vary between both the age group of drivers and the type of driving task. The highest error indices occurred in the non-signalised intersection tasks and the roundabout, which exactly equals the corresponding ratings of task complexity from the SAFE analysis. A comparison of age groups clearly shows the disadvantage of older drivers, whose error indices in nearly all tasks are significantly higher than those of the other groups. The vast majority of these errors could be explained by high task load in the intersections, as they represent difficult tasks. The discussion shows how reliability estimates can be used in a constructive way to propose changes in car design, intersection layout and regulation as well as driver training.     

Driver Behaviour Questionnaire: a follow-up study

The aim of the present study was to investigate time-across stability of different factor solutions (two to six factors) of the Driver Behaviour Questionnaire (DBQ) and to examine the changes on self-reported driving pattern in a follow-up sample (n=622) after three years of the first responses. Repeated measures ANOVA indicated that there was a significant change between Time 1 and Time 2 scores in six items of the DBQ. Drivers reported less competitiveness while driving at Time 2 but more speeding, drinking and driving, driving to wrong destinations and having no recollection of the road just travelled. Significant Time x Sex x Age interactions were found in change scores of four items. Young males and middle-aged female drivers emerged as a group of drivers who changed their self-reported driving pattern over three years. Additionally, sex, age or both had main effects on scores of 21 items. Males and young drivers reported more violations than females and older drivers, whereas female drivers reported more errors and lapses. After running possible factor solutions with Tucker's Phi agreement coefficients, the results indicated that the four- and two-factor solutions were the most stable and interpretable ones. The two-factor solution showed better time-across stability than the four-factor structure did, although the factor solutions found at Time 1 and Time 2 were not as identical as expected. Separate analysis revealed that drivers who had high annual mileage at Time 1 and Time 2 showed the strongest two-factor time-across stability. The test-retest reliability was 0.50 for errors, 0.76 for violations and 0.61 for the whole scale.