Impact of cannabis mass gathering events on mental health and health service utilization
Notice bibliographique
Résumé
Abstract Background The Canadian government has legalized and regulated access to cannabis as of October 2018. In this context, there is a need to analyze data that may provide insights on the effects of increased accessibility and tolerance for cannabis use. One source of data is the phenomenon known as “4/20”, a decades-old yearly mass gathering event supporting the legalization of cannabis. These events offer naturalistic epidemiologic data to ascertain specific impacts of cannabis consumption in a context of increased tolerance on health service utilization. Our study assessed the association between cannabis mass gathering events and health service utilization related to mental illness and substance use disorders at the nearest local emergency department. Methods Emergency department service utilization data (2005-2015) was used. The sample analyzed consists of emergency department visits due to mental and substance use disorders. A multiple linear regression model was used to predict the number of daily visits with year, month, day of the week, and day of income assistance distribution as independent variables. Daily residuals were averaged, and residuals for the days with the highest number of visits were compared with the mean residual number of visits. Also, correlation of number of visits with attendance to mass gathering events was explored. Results The residual number of visits for mental health and substance use disorder was the highest on April 20 th 2015 (n=51.0, z-score=11.0, p<0.001), and on days associated with subsequent cannabis mass gathering events. Moreover, this number of visits is positively correlated with the number of attendees at the “4/20” event (Pearson’s correlation coefficient: 0.76, 95% CI: 0.19 to 0.956, p=0.002), and increased over time. Conclusion Cannabis mass gathering events were associated with an increased number of emergency visits for patients with mental health and substance use diagnoses at the nearest local emergency department. In the context of legalization and regulation of cannabis use, these specific gatherings will not necessarily be discontinued. Indeed, as per news reports the recent post-legalization “4/20” drew tens of thousands of people in Vancouver. Also, in the new context other non-specific mass gatherings may also lead to foreseeable episodic surges in ER utilization. In light of this and from a public health perspective, services need to be prepared to care for predictably larger numbers of people suffering cannabis intoxication during mass gatherings, as well as to make provisions to provide all other services that are regularly needed for other emergency conditions. Also, educational campaigns about responsible use during these events will become particularly important, as well as offering on-site support, triage and basic services. This will allow for specific care to be provided in a non-stigmatizing manner, proportional to need, and without overcrowding general emergency services.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».