Risk of motor vehicle collisions and culpability among older drivers using cannabis: a meta‐analysis
Bibliographic record
Abstract
Abstract Background While the effects of cannabis use on driving have been established in younger populations, limited studies have investigated this association among older adults, who represent the fastest growing segment of drivers globally. Method We conducted a systematic review and meta‐analysis to evaluate the effect of THC exposure on (1) risk of motor vehicle collisions (MVC) and (2) risk of culpability (being responsible for the collision), among adults 50 years and older. Three reviewers screened 7,022 studies identified through MEDLINE, EMBASE, CENTRAL, and PsycINFO and published between inception and 2021. Odds Ratios (OR) were calculated with a random‐effects model using the Mantel‐Haenszel method in Review Manager 5.4.1. Heterogeneity was assessed using I2. An adapted version of the National Heart, Lung, and Blood Institute quality assessment tool was used to assess the quality of each study. Result 7 cross‐sectional studies were included. Three studies were rated ‘Good’ quality, one rated ‘Fair’, and three rated ‘Poor’. Three of the included studies evaluated culpability (NTHC+ = 239 NTHC‐ = 4609) while four evaluated MVC risk (NTHC+ = 158, NTHC‐ = 6152). We found that the pooled risk of MVC was not significantly different between older drivers exposed to THC and those who were not (OR, 95% CI 1.15 [0.40, 3.31]; I2 = 72%). In the studies assessing driver culpability, THC exposure was not significantly associated with an increased risk of being culpable for MVC among adults over the age of 50 (OR, 95% CI 1.24 [0.95, 1.61]; I2 = 0%). A visual inspection of the funnel plots did not indicate any publication bias. Conclusion Our review found that THC exposure was not associated with MVC involvement nor with culpability. However, it would be an oversimplification to conclude that cannabis use does not pose a safety risk to older drivers. Rather, our results may reflect several methodological limitations of the studies included in this review. Due to the increasing prevalence of cannabis use worldwide, we are optimistic that future research will be able to address this research question using more objective methodologies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.051 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".