The effects of cannabis intoxication on motor vehicle collision revisited and revised

Røgeberg, Ole; Elvik, Rune · 2016 · OpenAlex-citations

DOI: 10.1111/add.13347

archive: archived pipeline: cataloged verified

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Summary

This paper revisits and revises the estimated risk of motor vehicle collisions associated with acute cannabis intoxication, addressing concerns that previous meta-analyses significantly overestimated this risk due to methodological flaws. The authors were motivated by the prevailing consensus, largely based on two 2012 meta-analyses by Asbridge et al. and Li et al., which suggested cannabis-impaired driving increased crash risk by 2–3 times. The study aims to correct for issues such as incompatible study designs, sparse data bias, and inadequate control for confounders, while also updating the evidence base with recent observational studies. The research comprises two parts. Study 1 replicates the analyses of Asbridge et al. and Li et al., correcting for identified methodological errors. The authors re-extracted data from the original studies, applying corrections for sparse data bias (using Laplace correction) and adjusting for the inherent upward bias in "culpability" studies, which estimate the risk of culpable accidents rather than overall crash risk. They also prioritized confounder-adjusted estimates over crude counts. Study 2 conducts an updated meta-analysis using 28 risk estimates from 21 observational studies published between 1982 and 2015. These studies, drawn from 13 countries, utilized case-control or culpability designs. The authors employed random effects models and meta-regression techniques (PEESE) to synthesize results, while also assessing study quality based on drug measurement methods, crash severity specification, confounder control, and dose-response testing. The findings substantially revise previous risk estimates downward. In Study 1, the corrected pooled estimates for both Asbridge et al. and Li et al. were significantly lower than originally reported, with the original point estimates falling outside the revised confidence intervals. Study 2 found that acute cannabis intoxication is associated with a statistically significant but low-to-moderate increase in crash risk. The random effects model yielded an odds ratio of 1.36 (95% CI: 1.15–1.61), while the meta-regression model, which better handles small-sample bias, yielded an odds ratio of 1.22 (95% CI: 1.10–1.36). Subsample analyses indicated that higher odds ratios were associated with lower study quality, limited confounder adjustment, and failure to control for alcohol intoxication. No significant publication bias was detected. The authors conclude that while acute cannabis intoxication does increase crash risk, the magnitude is lower than previously claimed, ranging from low to medium. They caution that remaining selection effects in observational studies may limit causal interpretation. The study highlights the importance of rigorous methodological standards in meta-analyses, particularly regarding the distinction between culpability and case-control designs and the necessity of controlling for confounders like alcohol and demographic factors. These findings provide a more accurate evidence base for policymakers and researchers evaluating the safety implications of cannabis legalization.

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Topics

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• cannabis
• polydrug

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• Empirical Findings: crash risk outcomes