Elsevier

Accident Analysis & Prevention

Volume 123, February 2019, Pages 69-78
Accident Analysis & Prevention

A meta-analysis of the crash risk of cannabis-positive drivers in culpability studies—Avoiding interpretational bias

https://doi.org/10.1016/j.aap.2018.11.011Get rights and content
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Highlights

  • Odds ratios in culpability studies estimate the increased risk of a culpable crash, not the overall increased crash risk.

  • Both the increased risk of culpable and any crash can be estimated from culpability study counts using a Bayesian inference model.

  • Extensive tests on bootstrapped data finds that the Bayesian estimates performs well when recovering the increased risk of both culpable and any crashes.

  • Applied to 13 studies, the new inference model indicates that misinterpreted culpability ORs have substantially exaggerated the increased crash risk associated with cannabis.

Abstract

Background: Culpability studies, a common study design in the cannabis crash risk literature, typically report odds-ratios (OR) indicating the raised risks of a culpable accident. This parameter is of unclear policy relevance, and is frequently misinterpreted as an estimate of the increased crash risk, a practice that introduces a substantial “interpretational bias”.

Methods: A Bayesian statistical model for culpability study counts is developed to provide inference for both culpable and total crash risks, with a hierarchical effect specification to allow for meta-analysis across studies with potentially heterogeneous risk parameter values. The model is assessed in a bootstrap study and applied to data from 13 published culpability studies.

Results: The model outperforms the culpability OR in bootstrap analyses. Used on actual study data, the average increase in crash risk is estimated at 1.28 (1.16–1.40). The pooled increased risk of a culpable crash is estimated as 1.42 (95% credibility interval 1.11–1.75), which is similar to pooled estimates using traditional ORs (1.46, 95% CI: 1.24–1.72). The attributable risk fraction of cannabis impaired driving is estimated to lie below 2% for all but two of the included studies.

Conclusions: Culpability ORs exaggerate risk increases and parameter uncertainty when misinterpreted as total crash ORs. The increased crash risk associated with THC-positive drivers in culpability studies is low.

Keywords

Culpability study
Meta-analysis
Cannabis
Crash risks
Bayesian inference

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