Unintended but Hardly Unexpected Consequences of Cannabis Legalization
Bibliographic record
Abstract
In October 2018, Canada joined the ranks of a small number of countries throughout the world, as well as 17 states across the United States, in legalizing the use, possession, and sale of nonmedical cannabis products. One year later, Canada amended its Cannabis Act to include the sale of cannabis-containing edibles. In an attempt to reduce unintentional ingestions and minimize the “appeal to youth,” Canada also required all cannabis products to display a standardized symbol: a red stop-sign shaped logo containing a cannabis leaf and the word “THC.” In addition, all cannabis-containing edibles are required to have tamper-proof and child-resistant packaging, with strict limits on the tetrahydrocannabinol amount present in single packages.In the current issue of Pediatrics, Yeung et al1 study this large national experiment to evaluate how the legalization of cannabis in Canada has affected emergency department (ED) visit volumes and codiagnosis and coingestion patterns in children and adolescents in urban Alberta. Using the National Ambulatory Care Reporting System database, a national administrative database used to capture all ED and urgent center visits throughout Canada, the authors focused on Calgary and Edmonton area hospitals. All visits for patients 0 to 17 years of age with a cannabis-related primary or secondary International Classification of Diseases diagnostic code were included for the time period of 5 full years before legalization and 17 months postlegalization, the postlegalization period coinciding and ending with the March 1, 2020, lockdown from coronavirus disease 2019. Interrupted time-series analyses provided comparisons of monthly visit volumes over the total time studied; incident-rate ratios of cannabis-related ED and urgent visits and relative risk ratios for the outcomes of diagnostic patterns, unintentional ingestions, and coingestants provided comparisons postlegalization versus prelegalization.These authors found that, although the total number of cannabis-related ED visits did not increase for the total population of 0 to 17 year olds, from the prelegalization to the postlegalization period, there was a significant increase during the postlegalization period in the relative incidence of visits for children 0 to 11 years of age for any cannabis-related concerns (incident rate ratio: 2.51; 95% confidence interval 1.62–3.88) and in the proportion of these children presenting to the ED for cannabis-related diagnoses (relative risk: 2.41, 95% confidence interval 1.61–3.61). Increased ED visit rates were not seen for either younger or older adolescents, which is in direct contrast with what has been seen in US states such as Colorado, in which higher rates of ED visits for adolescents have been well documented.2 Yeung et al1 also found that overall rates and proportions of unintentional ingestions associated with cannabis were increased for children and older adolescents but not the younger adolescents (12–14 years). The authors concluded that the increase in ED visits seen for children ≤11 years was driven by the increased role of cannabis in unintentional ingestions, a rate that was a 77% increase from the pre- to postlegalization period. With these findings, they support what has been seen by investigators across the United States.3,4One of the most interesting findings from this study was that the interrupted time-series analyses revealed that although visit rates for cannabis-related diagnoses have increased from the pre- to the postlegalization period, the rate of change did not differ across these 2 periods (or, as the authors state, “legalization is not associated with a sudden increase in visits”). Instead, the analyses revealed that ED visits rates have continued at a steadily increasing rate, suggesting that access to cannabis products by children and youth was as much a problem before legalization as it has been since legalization. This highlights the fact that even before marijuana was legalized in Canada children and adolescents had ready access to both illicit as well as licit forms of cannabis. These data may be welcome news for those who feared that legalization would result in dramatically increased access by the pediatric populations, as reflected in ED visits. However, this study should be a wake-up call for not only Canada but all states across the United States. Even in those states that have not legalized the use of nonmedical cannabis, an increased access to medicinal or illicit forms is widespread and may be what is driving the increased access and health consequences that are being seen in our pediatric populations. In addition, as what was seen in the current study, regulations around packaging and tamper-proofing have not deterred access and unintentional ingestions, although Yeung et al1 were not able to determine if licit or illicit forms of cannabis were the cause for the ED visits they reported.Clearly, effective public health messages and education efforts are needed if we are to avoid the unintended consequences of making marijuana products more available to adults: either for medicinal or recreational purposes. Without these, we can only expect that both intentional and unintentional consequences will continue to increase and affect our children and youth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".