The Driver Behaviour Questionnaire as accident predictor; A methodological re-meta-analysis

Wåhlberg, Anders af; Barraclough, Peter; Freeman, James E.

doi:10.1016/j.jsr.2015.08.003

Cited by 63 publications

(47 citation statements)

References 128 publications

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“…context, a major factor in initiating these studies was the concern that observed relationships between crash data and certain self-reported variables was inflated, in part due to CMV effects. The first phase of this series of studies involved a metaanalysis of personality traits and crash involvement, to consider the heterogeneity between studies and its possible determinants (af Wåhlberg, Barraclough, & Freeman, 2017). A second meta-analysis re-examined the relationship between the DBQ and crashes, finding that self-reported data did yield higher effect sizes although the limited number of studies that used archival records limited the impact of this finding (af Wåhlberg, Barraclough, & Freeman, 2016).…”

Section: Repeated Measures Studymentioning

confidence: 99%

Section: Other Road Safety CMV Studiesmentioning

confidence: 99%

“…More data for this debate has appeared in recent publications (deWinter, Dodou, & Stanton, 2015;Af Wåhlberg, Barraclough & Freeman, 2015). For example in a meta-analysis, af Wåhlberg, Barraclough, and Freeman (2015) measured available data on the relationship between crashes and the DBQ factors and examined responses in terms of self-report and archival data. After controlling for the number of crashes, the observed relationship was found to be stronger when all the data was drawn from a single self-reported source than when survey responses were correlated against archival driving records, indicative of CMV effects.…”

Section: Other Road Safety CMV Studiesmentioning

confidence: 99%

“…However the number of studies using archival data was insufficient for the findings to be statistically conclusive. On the other hand, in a meta-analysis of personality as a predictor of crash involvement, measurements involving archival crash data actually produced larger effect sizes than those produced solely by selfreport responses (af Wåhlberg, Barraclough & Freeman, 2017). In light of this, it should therefore not be assumed that all self-report scales are equally influenced by CMV effects.…”

Section: Other Road Safety CMV Studiesmentioning

confidence: 99%

“…The Freeman, 2015) or were limited due to the questionable validity of some of the data (af Wåhlberg, Barraclough & Freeman, 2017). Study1 in this research program will be structured in such a way as to enable meaningful conclusions to be reached in regards to measuring the results produced by the different data types.…”

Section: Contribution Of Current Research To Literaturementioning

confidence: 99%

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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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Section: Repeated Measures Studymentioning

confidence: 99%

Section: Other Road Safety CMV Studiesmentioning

confidence: 99%

Section: Other Road Safety CMV Studiesmentioning

confidence: 99%

Section: Other Road Safety CMV Studiesmentioning

confidence: 99%

Section: Contribution Of Current Research To Literaturementioning

confidence: 99%

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

Barraclough¹

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Accuracy of conversion formula for effect sizes: A Monte Carlo simulation

Poom

Wåhlberg

2022

Research Synthesis Methods

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In meta-analysis, effect sizes often need to be converted into a common metric. For this purpose conversion formulas have been constructed; some are exact, others are approximations whose accuracy has not yet been systematically tested. We performed Monte Carlo simulations where samples with prespecified population correlations between the x and y-variables were drawn from a normally distributed population. A number of commonly used effect size measures and statistics were calculated from each sample. Using several available conversion formula these statistics were converted into Pearson r and Cohen's d and compared to r and d calculated directly from the original data.Converted values were systematically lower than the directly calculated values.

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Profiles of women who have suffered occupational accidents in cleaning: perceived health, psychosocial risks, and personality variables

Suárez

López-Goñi²,

Haro³

2022

Int Arch Occup Environ Health

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Purpose The main goal was to identify the variables (sociodemographic, work, psychosocial, perceived health, and personality) associated with occupational accidents suffered in the past by women in the cleaning sector. Methods A sample of 455 women was evaluated. Results A total of 23.5% of the workers (n = 107) had suffered an occupational accident with medical leave. In general, women who had suffered some accident in their life had a worse situation in all areas evaluated. Two subsamples of women had a greater association with accidents. Specifically, the presence of work accidents was 15.9 times higher among those who presented a worse perception of their physical effort and a greater tendency towards risky behaviours and 13.5 times higher among those who had a moderate perception of physical exertion and a disability. Conclusion In general, the characteristics of female workers were found to be associated with different accident rates. Preventive actions should be designed individually.

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The Driver Behaviour Questionnaire as accident predictor; A methodological re-meta-analysis

Cited by 63 publications

References 128 publications

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

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

Accuracy of conversion formula for effect sizes: A Monte Carlo simulation

Profiles of women who have suffered occupational accidents in cleaning: perceived health, psychosocial risks, and personality variables

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