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Enregistrement W4313641795 · doi:10.1111/add.16128

Increase in cannabis‐related emergency department presentations in the period immediately before legalization requires explanation

2023· letter· en· W4313641795 sur OpenAlexaboutno aff
Bobby P. Smyth, Peter McCarron

Notice bibliographique

RevueAddiction · 2023
Typeletter
Langueen
DomaineMedicine
ThématiqueCannabis and Cannabinoid Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLegalizationCannabisGovernment (linguistics)LegislationMedicineEmergency departmentLegislaturePolitical sciencePsychiatryLaw

Résumé

récupéré en direct d'OpenAlex

Myran et al. [1] recently reported on changes in cannabis related emergency department (ED) attendances in Ontario across a period of major policy change in Canada. The conclusion that ‘cannabis related ED visits decreased following recreational cannabis legalization with strict retail controls’ is misleading. Three time periods were included, a pre-legalization phase (January 2016–September 2018), a post legalization period (October 2018–February 2020) when there was strict retail control and finally a period of commercialization (March 2020–May 2021). The authors focus on the expansion of government-regulated cannabis stores, which increased greatly during commercialization. The period of most dramatic change in cannabis-related ED attendances occurs during the pre-legalization period, where increases of 2% per month were reported. It seems highly unlikely that this constitutes a sustained secular trend as it implies a greater than 10-fold increase in attendances per decade. The use of this relatively brief period of major acceleration in ED attendances as the secular trend generates the finding that cannabis-attributable ED visits decreased following legalization. What factors may explain the rapidly increasing rate of ED attendances in the 2 years before legalization, and are these really independent of the legalization process itself? The Canadian government announced its intention to legalize cannabis in late 2015 [2]. Legalization legislation was unveiled in April 2017 [3]. The many steps involved in a legislative process can be confusing to the general public and may result in the assumption that an activity is legal once government declares its intention to legalize [4]. The incremental liberalization of cannabis policy in Canada appears to have also influenced police behaviour, with year on year declines in cannabis arrests from 2011 onwards while rates of use were relatively stable [5, 6]. This indicates incremental reduction in enforcement of laws, which were due to be repealed, and similar patterns are evident in United States [7]. Although there is some debate about the effectiveness of penalties as deterrents, they are certainly not going to have any effect if not used [8]. Perhaps the most important oversight by the authors regarding the pre-legalization phase is the existence and expansion of a vibrant grey market of cannabis dispensaries in Ontario, operating under the guise of ‘medical’ cannabis [9, 10]. In May 2016, the Mayor of Toronto stated, ‘The speed with which these storefronts are proliferating, and the concentration of dispensaries in some areas of our city, is alarming’ [11]. The importance of grey market dispensaries was highlighted in a recent study of youth attending addiction treatment in Ontario, which found that dispensaries were the most common source of cannabis before legalization [12]. The failure to provide context regarding the utilized pre-legalization phase makes it difficult for readers to know how the results might translate to other settings. During this period of preparation for legalization in Ontario, there was undermining of injunctive norms against use by the political leadership, incremental deprioritization of enforcement by police and an expanding network of cannabis dispensaries in the grey market. Legalization should be viewed as a long-term process lasting years and commencing well in advance of the date of enactment of legislation [13]. In Ontario, the process arguably started in late 2015. Future studies using time series analysis should select time periods before the process commencing, for example the period 2010 to 2015 in this case, to establish secular trends that are uncontaminated by the legalization process itself. None. None to declare. Bobby Smyth: Conceptualization; writing – original draft; writing – review and editing. Peter McCarron: Writing – original draft; writing – review and editing.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,303
Score d'incertitude au seuil0,602

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0090,001

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.

Tête enseignante Opus0,021
Tête enseignante GPT0,311
Écart entre enseignants0,290 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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