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

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  • Peter Barraclough
  • Anders af Wåhlberg
  • James Freeman
  • Barry Watson
  • Angela Watson

Abstract

Background: Traffic 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 Findings: 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. 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. Significance: The 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.

Suggested Citation

  • Peter Barraclough & Anders af Wåhlberg & James Freeman & Barry Watson & Angela Watson, 2016. "Predicting Crashes Using Traffic Offences. A Meta-Analysis that Examines Potential Bias between Self-Report and Archival Data," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-32, April.
  • Handle: RePEc:plo:pone00:0153390
    DOI: 10.1371/journal.pone.0153390
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    References listed on IDEAS

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    1. Charles Scialfa & Jennifer Ference & Jessica Boone & Richard Tay & Carl Hudson, 2010. "Predicting Older Adults' Driving Difficulties Using the Roadwise Review," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 65(4), pages 434-437.
    2. Robert W. Whissell & Brian J. Bigelow, 2003. "The Speeding Attitude Scale and the Role of Sensation Seeking in Profiling Young Drivers at Risk," Risk Analysis, John Wiley & Sons, vol. 23(4), pages 811-820, August.
    3. Donald Edmondson & Safiya Richardson & Louise Falzon & Karina W Davidson & Mary Alice Mills & Yuval Neria, 2012. "Posttraumatic Stress Disorder Prevalence and Risk of Recurrence in Acute Coronary Syndrome Patients: A Meta-analytic Review," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-10, June.
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    Cited by:

    1. Wafa Elias, 2021. "The Effectiveness of Different Incentive Programs to Encourage Safe Driving," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
    2. Andrei C. Holman & Simona A. Popușoi, 2020. "How You Deal with Your Emotions Is How You Drive. Emotion Regulation Strategies, Traffic Offenses, and the Mediating Role of Driving Styles," Sustainability, MDPI, vol. 12(12), pages 1-13, June.
    3. Karoline Gomes-Franco & Mario Rivera-Izquierdo & Luis Miguel Martín-delosReyes & Eladio Jiménez-Mejías & Virginia Martínez-Ruiz, 2020. "Explaining the Association between Driver’s Age and the Risk of Causing a Road Crash through Mediation Analysis," IJERPH, MDPI, vol. 17(23), pages 1-12, December.
    4. Antoni Wontorczyk & Stanislaw Gaca, 2021. "Study on the Relationship between Drivers’ Personal Characters and Non-Standard Traffic Signs Comprehensibility," IJERPH, MDPI, vol. 18(5), pages 1-19, March.

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