The Motorcycle Rider Behavior Questionnaire: Psychometric properties and application amongst novice riders in Australia

Sakashita, Chika; Senserrick, Teresa; Lo, Serigne; Boufous, Soufiane; Rome, Liz de; Ivers, Rebecca

doi:10.1016/j.trf.2013.10.005

Cited by 75 publications

(77 citation statements)

References 30 publications

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“…As mentioned, the latest research about the 43-item MRBQ questionnaire had implicated that the subsequent factor model can be articulated by four essential factors, which are speed violations, errors, safety equipment, and stunts (Sakashita et al 2014). Moreover, since we know that the Q1 questionnaire additionally brings three groups of items (A i , i = 1, …, 4; C i , i = 1, …, 4; H i , i = 1, …, 3), we justifiably expect that the EFA will clearly give us the seven-factor solution.…”

Section: Exploratory Factor Analysismentioning

confidence: 99%

“…The basis for interviewing was wellknown Motorcycle Rider Behaviour Questionnaire (MRBQ), firstly introduced in the study (Elliott et al 2007), and later additionally tested in the other studies (Sakashita et al 2014;etc.). Its main purpose is to measure the riders' behavioural characteristics, such as control and traffic errors, use of safety equipment, and speed violations, as well as to identify how are the latter related to the crash risk (Elliott et al 2007).…”

Section: Introductionmentioning

confidence: 99%

“…The MRBQ consists of 43 items related to the safe or dangerous behaviour of the riders and is usually measured on six or seven points Likert scale. The latest MRBQ studies have discovered that the resulting factor model can be expressed by four significant factors, which are speed violations, errors, safety equipment, and stunts (Sakashita et al 2014).…”

Section: Introductionmentioning

confidence: 99%

“…The details about the structure of these items can be found in the scholarly literature (Elliott et al 2007;Özkan et al 2006;Sakashita et al 2014).…”

Section: Introductionmentioning

confidence: 99%

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Relationships between the motorcyclists’ behavioural perception and their actual behaviour

Topolšek

Dragan

2016

Transport

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Abstract. The paper deals with studying the relationships between the motorcyclists' thinking about proper behaviour and their actual behaviour in the traffic. The impact of some control variables, such as riders' age, experience, driving history, and engine cubature, on actual behaviour, is also addressed here. For the purpose of research, two additional questionnaires were applied besides the well-known Motorcycle Rider Behaviour Questionnaire (MRBQ). To examine the causal relations between all-important latent factors present in this study, the structural equation model was designed. Exploratory and confirmatory factor analyses were also engaged in the analysis and the statistical modelling process. The results show that the higher awareness about alcohol danger and benefits of protective equipment and helmet can noticeably contribute to the bigger traffic safety. Besides, from the results is evident that the control variables are in most cases also significantly interrelated with the actual behaviour factors. The findings of this research could be important for the planning of better traffic safety strategies for the motorcyclists to decrease the fatalities and related costs and traumas.

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Section: Exploratory Factor Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The details about the structure of these items can be found in the scholarly literature (Elliott et al 2007;Özkan et al 2006;Sakashita et al 2014).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Relationships between the motorcyclists’ behavioural perception and their actual behaviour

Topolšek

Dragan

2016

Transport

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“…A complete list of original data, country of origin, sample characteristics and other key variables from self-report studies is provided in Table 3 and for archival studies inTable 4. An additional nine effects were identified from seven studies which compared variables created utilising a combination of self-report and archival data and are shown in Table 4 ( Barkley et al, 2002;Caird & Kline, 2004;Fischer et al, 2007;Sakashita et al, 2014;Schwebel et al, 2007;D. I. Smith, 1976).…”

Section: Datamentioning

confidence: 99%

Common method variance and other sources of bias in road traffic research

Barraclough¹

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Common Method Variance and other sources of bias in road traffic research i KeywordsRoad crashes, traffic offences, common method variance, social desirability, method bias, meta-analysis, self-report data, road safety. AbstractReducing the number of fatalities and injuries due to vehicle crashes is a major focus for road safety researchers throughout the world. Research on driver behaviours, attitudes and associated crashes is often conducted using self-report surveys. When the predictor and criterion variables are drawn from a single source (such as a cross-sectional survey) as is generally the case, it has been generally acknowledged that a range of methodological issues associated with this approach have the potential to reduce the efficacy of predictive measures. Common method variance (CMV) is bias that occurs when both the predictors and the predicted variables are gathered and analysed in the same manner from the same source. CMV effects have the potential to distort findings by artificially strengthening or weakening the observed relationships between items of interest. This is of particular concern to road safety researchers, given the distinct possibility that the small associations often observed within road safety studies may in turn be inflated due to CMV biases. There is a significant need to examine the exact nature and extent of CMV effects within self-reported road safety data and to explore how best to reduce this measurement error.The current body of research was conducted with three primary aims in mind:1. Examine the existence of CMV effects.2. Explore the level of influence that CMV effects have on self-report data, including whether these effects inflate or deflate observed relationships between variable.3. Test research methods to control for the influence of CMV effects on selfreport data.Study 1 involved a meta-analysis that quantified the association between crashes and traffic offences in light of potential moderators. In reference to the exploration for CMV effects, this study examined the extent to which the relationship between self-reported traffic offences and self-reported crashes is stronger than that recorded using only official data sources. Studies yielding a correlation between crashes and traffic offences were collated and a meta-analysis of 144 effects drawn from 99 road safety studies conducted. The impact of factors such as age, time period, crash and offence rates, crash severity and data type, sourced from either self-report surveys or archival records, were examined. After weighting for sample size, an average correlation of r = .18 between crashes and traffic offences was observed over the mean time period of 3.2 years. Evidence emerged suggesting the strength of this correlation is decreasing over time. Stronger correlations between crashes and offences were generally found in studies involving younger drivers. In relation to the existence of CMV effects, a within-country analysis found stronger effect sizes in self-reported data after controlling for crash mean ...

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