968 resultados para Driver Behaviour Questionnaire


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The following discussion is in response to a 2010 article published in the Journal of Safety Research by J.C.F. de Winter and D. Dodou entitled “The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis” (Volume 41, Number 6, pp. 463-470, available on sciencedirect.com). The editors are pleased to provide a forum for this exchange and welcome further comments.

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This study reports on the utilisation of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours of a large sample of Australian fleet drivers (N = 3414). Surveys were completed by employees before they commenced a one day safety workshop intervention. Factor analysis techniques identified a three factor solution similar to previous research, which was comprised of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Two items traditionally related with highway-code violations were found to be associated with aggressive driving behaviours among the current sample. Multivariate analyses revealed that exposure to the road, errors and self-reported offences predicted crashes at work in the last 12 months, while gender, highway violations and crashes predicted offences incurred while at work. Importantly, those who received more fines at work were at an increased risk of crashing the work vehicle. However, overall, the DBQ demonstrated limited efficacy at predicting these two outcomes. This paper outlines the major findings of the study in regards to identifying and predicting aberrant driving behaviours and also highlights implications regarding the future utilisation of the DBQ within fleet settings.

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The Driver Behaviour Questionnaire (DBQ) continues to be the most widely utilised self-report scale globally to assess crash risk and aberrant driving behaviours among motorists. However, the scale also attracts criticism regarding its perceived limited ability to accurately identify those most at risk of crash involvement. This study reports on the utilisation of the DBQ to examine the self-reported driving behaviours (and crash outcomes) of drivers in three separate Australian fleet samples (N = 443, N = 3414, & N = 4792), and whether combining the samples increases the tool’s predictive ability. Either on-line or paper versions of the questionnaire were completed by fleet employees in three organisations. Factor analytic techniques identified either three or four factor solutions (in each of the separate studies) and the combined sample produced expected factors of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Highway code violations (and mean scores) were comparable across the studies. However, across the three samples, multivariate analyses revealed that exposure to the road was the best predictor of crash involvement at work, rather than DBQ constructs. Furthermore, combining the scores to produce a sample of 8649 drivers did not improve the predictive ability of the tool for identifying crashes (e.g., 0.4% correctly identified) or for demerit point loss (0.3%). The paper outlines the major findings of this comparative sample study in regards to utilising self-report measurement tools to identify “at risk” drivers as well as the application of such data to future research endeavours.

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Problem The Manchester Driver Behaviour Questionnaire (DBQ) is the most commonly used self-report tool in traffic safety research and applied settings. It has been claimed that the violation factor of this instrument predicts accident involvement, which was supported by a previous meta-analysis. However, that analysis did not test for methodological effects, or include contacting researchers to obtain unpublished results. Method The present study re-analysed studies on prediction of accident involvement from DBQ factors, including lapses, and many unpublished effects. Tests of various types of dissemination bias and common method variance were undertaken. Results Outlier analysis showed that some effects were probably not reliable data, but excluding them did not change the results. For correlations between violations and crashes, tendencies for published effects to be larger than unpublished ones and for effects to decrease over time were observed, but were not significant. Also, analysis using the proxy of the mean of accidents in studies indicated that studies where effects for violations are unknown have smaller effect sizes. These differences indicate dissemination bias. Studies using self-reported accidents as dependent variables had much larger effects than those using recorded accident data. Also, zero-order correlations were larger than partial correlations that controlled for exposure. Similarly, violations/accidents effects were strong only when there was also a strong correlation between accidents and exposure. Overall, the true effect is probably very close to zero (r<.07) for violations versus traffic accident involvement, depending upon which systematic tendencies in the data are controlled for. Conclusions: Methodological factors and dissemination bias have inflated the mean effect size of the DBQ in the published literature. Strong evidence of various artefactual effects is apparent. Practical Applications A greater level of care should be taken if the DBQ continues to be used in traffic safety research. Also, validation of self-reports should be more comprehensive in the future, taking into account the possibility of common method variance.

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There has been increased research interest in Co-operative Vehicle Infrastructure Systems (CVIS) from the eld of Intelligent Transport Systems (ITS). However most of the research have focused on the engineering aspects and overlooked their relevance to the drivers' behaviour. This paper argues that the priority for cooperative systems is the need to improve drivers decision making and reduce drivers' crash risk exposure to improve road safety. Therefore any engineering solutions need to be considered in conjuction with traffic psychology theories on driver behaviour. This paper explores the advantages and limitations of existing systems and emphasizes various theoretical issues that arise in articulating cooperative systems' capabilities and drivers' behaviour.

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Crashes at rail level crossings represent a significant problem, both in Australia and worldwide. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles, now provide researchers with the opportunity to further understand driver behaviour at rail level crossings in ways not previously possible. This paper gives an overview of a recent on-road pilot study of driver behaviour at rail level crossings in which 25 participants drove a pre-determined route, incorporating 4 rail level crossings, using MUARC's instrumented On-Road Test Vehicle (ORTeV). Drivers provided verbal commentary whilst driving the route, and a range of other data were collected, including eye fixations, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. Extracts from the wider analyses are used to examine in depth driver behaviour at one of the rail level crossings encountered during the study. The analysis presented, along with the overall analysis undertaken, gives insight into the driver and wider systems factors that shape behaviour at rail level crossings, and highlights the utility of using a multi-method, instrumented vehicle approach for gathering data regarding driver behaviour in different contexts.

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The contribution of risky behaviour to the increased crash and fatality rates of young novice drivers is recognised in the road safety literature around the world. Exploring such risky driver behaviour has led to the development of tools like the Driver Behaviour Questionnaire (DBQ) to examine driving violations, errors, and lapses [1]. Whilst the DBQ has been utilised in young novice driver research, some items within this tool seem specifically designed for the older, more experienced driver, whilst others appear to asses both behaviour and related motives. The current study was prompted by the need for a risky behaviour measurement tool that can be utilised with young drivers with a provisional driving licence. Sixty-three items exploring young driver risky behaviour developed from the road safety literature were incorporated into an online survey. These items assessed driver, passenger, journey, car and crash-related issues. A sample of 476 drivers aged 17-25 years (M = 19, SD = 1.59 years) with a provisional driving licence and matched for age, gender, and education were drawn from a state-wide sample of 761 young drivers who completed the survey. Factor analysis based upon a principal components extraction of factors was followed by an oblique rotation to investigate the underlying dimensions to young novice driver risky behaviour. A five factor solution comprising 44 items was identified, accounting for 55% of the variance in young driver risky behaviour. Factor 1 accounted for 32.5% of the variance and appeared to measure driving violations that were transient in nature - risky behaviours that followed risky decisions that occurred during the journey (e.g., speeding). Factor 2 accounted for 10.0% of variance and appeared to measure driving violations that were fixed in nature; the risky decisions being undertaken before the journey (e.g., drink driving). Factor 3 accounted for 5.4% of variance and appeared to measure misjudgment (e.g., misjudged speed of oncoming vehicle). Factor 4 accounted for 4.3% of variance and appeared to measure risky driving exposure (e.g., driving at night with friends as passengers). Factor 5 accounted for 2.8% of variance and appeared to measure driver emotions or mood (e.g., anger). Given that the aim of the study was to create a research tool, the factors informed the development of five subscales and one composite scale. The composite scale had a very high internal consistency measure (Cronbach’s alpha) of .947. Self-reported data relating to police-detected driving offences, their crash involvement, and their intentions to break road rules within the next year were also collected. While the composite scale was only weakly correlated with self-reported crashes (r = .16, p < .001), it was moderately correlated with offences (r = .26, p < .001), and highly correlated with their intentions to break the road rules (r = .57, p < .001). Further application of the developed scale is needed to confirm the factor structure within other samples of young drivers both in Australia and in other countries. In addition, future research could explore the applicability of the scale for investigating the behaviour of other types of drivers.

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International statistics indicate that occupational, or work-related driving, crashes are the most common cause of workplace injury, death, and absence from work. The majority of research examining unsafe driver behavior in the workplace has relied on general road safety questionnaires. However, past research has failed to consider the organizational context in the use of these questionnaires, and as such, there is ambiguity in the dimensions constituting occupational driving. Using a theoretical model developed by Hockey (1993, 1997), this article proposes and validates a new scale of occupational driver behavior. This scale incorporates four dimensions of driver behavior that are influenced by demanding workplace conditions; speeding, rule violation, inattention, and driving while tired. Following a content validation process, three samples of occupational drivers in Australia were used to assess the scale. Data from the first sample (n=145) were used to reduce the number of scale items and provide an assessment of the factorial validity of the scale. Data from the second sample (n=645) were then used to confirm the factor structure and psychometric properties of the scale including reliability and construct validity. Finally, data from the third sample (n=248) were used to establish criterion validity. The results indicated that the scale is a reliable and valid measure of occupational driver behavior.

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The contribution of risky behaviour to the increased crash and fatality rates of young novice drivers is recognised in the road safety literature around the world. Exploring such risky driver behaviour has led to the development of tools like the Driver Behaviour Questionnaire (DBQ) to examine driving violations, errors, and lapses. Whilst the DBQ has been utilised in young novice driver research, some items within this tool seem specifically designed for the older, more experienced driver, whilst others appear to asses both behaviour and related motives. Therefore there is a need for a risky behaviour measurement tool that can be utilised with young drivers with a provisional (intermediate) driving licence.

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This research project examined objective measures of driver behaviour and road users' perceptions on the usefulness and effectiveness of three specific VMS (Variable Message Signs) interventions to improve speeding and headway behaviours. The interventions addressed speeding behaviour alone (intervention 1), headway behaviour alone (intervention 2) and a combination of speeding and headway behaviour (intervention 3). Six VMS were installed along a segment of the Bruce Highway, with a series of three signs for each of the northbound and southbound traffic. Speeds and headway distances were measured with loop detectors installed before and after each VMS. Messages addressing speeding and headway were devised for display on the VMS. A driver could receive a message if they were detected as exceeding the posted speed limit (of 90km/hr) or if the distance to the vehicle in front was less than 2.0s. In addition to the on-road objective measurement of speeding and headway behaviours, the research project elicited self-reported responses to the speeding and headway messages from a sample of drivers via a community-based survey. The survey sought to examine the drivers' beliefs about the effectiveness of the signs and messages, and their views about the role, use, and effectiveness of VMS more generally.

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Road crashes are one of the most significant public health problems in Pakistan; however the factors that contribute to road crashes in Pakistan are not well-researched. Traditional beliefs and values can act as a barrier to health-promoting and injury prevention behaviours, in general and especially in relation to road safety, and may also contribute to risk-taking behaviours. Such beliefs can present significant challenges for health advocates who aim to change behaviour in order to avert road crashes and diminish their consequences. Qualitative research was undertaken in Islamabad, Rawalpindi and Lahore with a range of drivers, religious orators, police and policy makers to explore cultural and religious beliefs and their association with risky road use, and to understand how they might affect development of road safety interventions. The findings highlight a range of issues, including the identification of aspects of beliefs that have complex social implications when designing safety intervention strategies. The pervasive nature of religious and superstitious beliefs in Pakistan can affect road user behaviour by reinforcing the presumption that the individual has no part to play in safety, thereby supporting continued risk taking behaviour. It is anticipated that the findings could be used to inform the design of interventions aimed at influencing broad-spectrum health attitudes and practices among the communities where such beliefs are prevalent.

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Self reported driving behaviour in the occupational driving context has typically been measured through scales adapted from the general driving population (i.e. the Manchester Driver Behaviour Questionnaire (DBQ)). However, research suggests that occupational driving is influenced by unique factors operating within the workplace environment, and thus, a behavioural scale should reflect those behaviours prevalent and unique within the driving context. To overcome this limitation, developed the Occupational Driver Behaviour Questionnaire (ODBQ) which utilises a relevant theoretical model to assess the impact of the broader workplace context on driving behaviour. Although the theoretical argument has been established, research is yet to examine whether the ODBQ or the DBQ is a more sensitive measure of the workplace context. As such, this paper identifies selected organisational factors (i.e. safety climate and role overload) as predictors of the DBQ and the ODBQ and compares the relative predictive value in both models. In undertaking this task, 248 occupational drivers were recruited from a community-oriented nursing population. As predicted, hierarchical regression analyses revealed that the organisational factors accounted for a significantly greater proportion of variance in the ODBQ than the DBQ. These findings offer a number of practical and theoretical applications for occupational driving practice and future research.

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The aim of this study was to validate the Children’s Eating Behaviour Questionnaire (CEBQ) in three ethnically and culturally diverse samples of mothers in Australia. Confirmatory factor analysis utilising structural equation modelling examined whether the established 8-factor model of the CEBQ was supported in our three populations: (i) a community sample of first-time mothers allocated to the control group of the NOURISH trial (mean child age = 24 months [SD = 1]; N = 244); (ii) a sample of immigrant Indian mothers of children aged 1–5 years (mean age = 34 months [SD = 14]; N = 203), and (iii) a sample of immigrant Chinese mothers of children aged 1–4 years (mean age = 36 months [SD = 14]; N = 216). The original 8-factor model provided an acceptable fit to the data in the NOURISH sample with minor post hoc re-specifications (two error covariances on Satiety Responsiveness and an item-factor covariance to account for a cross-loading of an item (Fussiness) on Satiety Responsiveness). The re-specified model showed reasonable fit in both the Indian and Chinese samples. Cronbach’s α estimates ranged from .73 to .91 in the Australian sample and .61–.88 in the immigrant samples. This study supports the appropriateness of the CEBQ in the multicultural Australian context.