Predicting Crashes Using Traffic Offences. A Meta-Analysis that Examines Potential Bias between Self-Report and Archival Data

Abstract

BackgroundTraffic offences have been considered an important predictor of crash involvement, and have often been used as a proxy safety variable for crashes. However the association between crashes and offences has never been meta-analysed and the population effect size never established. Research is yet to determine the extent to which this relationship may be spuriously inflated through systematic measurement error, with obvious implications for researchers endeavouring to accurately identify salient factors predictive of crashes.Methodology and Principal FindingsStudies yielding a correlation between crashes and traffic offences were collated and a meta-analysis of 144 effects drawn from 99 road safety studies conducted. Potential 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 considered and discussed. After weighting for sample size, an average correlation of r = .18 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. Consistent with common method variance effects, a within country analysis found stronger effect sizes in self-reported data even controlling for crash mean.SignificanceThe effectiveness of traffic offences as a proxy for crashes may be limited. Inclusion of elements such as independently validated crash and offence histories or accurate measures of exposure to the road would facilitate a better understanding of the factors that influence crash involvement.

Associations between Job Characteristics, Mental Health and Driving: A Secondary Analysis

“…Demographics feature heavily in the literature in terms of the connection between age and marital status and RTC causation [5]. The current analysis bears this out, as well as identifying that both demographics are associated with driver fatigue.…”

“…Marital status has also been found to have a bearing on the risk of driver injury; single drivers are estimated to be twice as likely to be involved in a RTC as their married counterparts. This again is thought to be associated with risk-taking behaviour, with single drivers adopting a 'nothing to lose' attitude to driving [5]. Moreover, risktaking has also been related to unsafe road traffic behaviour, the assumption being that risktaking attitudes correlate with risk-taking behaviour [6].…”

Experience as a Safety Factor in Driving; Methodological Considerations in a Sample of Bus Drivers

“…Such a practice is questionable, given the very weak associations between all safety proxies used, and actual crash involvement [15]. Traffic offences, for example, which is probably the most popular traffic safety proxy variable, only correlates about 0.18 with crash involvement [55].…”

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

“…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).…”

“…Indeed this aspect would be impossible to capture through state sources although some fleet vehicle records would have relevant exposure data. Some previous road safety findings have been found to be strongly influenced by exposure with those who drive more often also having a greater risk of experiencing an adverse driving event, although this relationship is not always so straight forward (af Wåhlberg, 2013;af Wåhlberg et al, 2016;Vaa, 2014).…”