Cannabis, Behaviours, COVID-19 and a Template For International Comparisons
Notice bibliographique
Résumé
Since its legalization in 2018, cannabis-related issues continue to be a focus for Canadian scholars. Two literature reviews are included in this issue: Bahji et al1 analyze an increase of cannabis consumption in Canadian households in both prelegalization and postlegalization times, based on 29 Statistics Canada surveys; Bahji and Gorelick,2 in a secondary analysis of lifetime and past year prevalence of cannabis withdrawal syndrome differentiate factors elicited with one or both prevalence metrics. A second topic of broad interest is the impact of coronavirus disease 2019 (COVID-19) on various behaviours. Purias et al3 report the results of an online questionnaire of shoppers during the pandemic with online shoppers demonstrating greater scores on 2 measures of problem shopping as well as associated sex difference with gaming involvement. In the second COVID-related article, Shaw et al4 analyze the impact of social lockdown on gambling activities. The third article, by Hawke et al,5 deals with the associated substance use in youth. These 3 papers are part of our COVID Chronicles series, so far 17 Editorials, Commentaries, or Research Articles have been published in the CJA over the last 2 years.6–17 At the time of writing this Editorial, a seventh COVID wave is announced, spurred mainly by the Omicron BA.5 variant. Further stress on our health system is looming once more including closures of emergency services in peripheral areas due to staff shortages from infections or burnouts after 2 years of relentless working conditions. This body of work calls for a comparison of the relative impact of the pandemic and related public health measures in our country versus others. Recently, The Canadian Medical Association Journal has published a noteworthy template for international comparisons.18 Ten comparator countries were chosen on the basis of similarities in economic and political models, per capita income levels and population size. Several data repositories were mined. The comparisons included the G7 countries plus Belgium, the Netherlands, Sweden, and Switzerland. The metrics used in the analysis included infections, related and excess deaths, percentage of population vaccinated, societal restrictions, and economic impact. Canada had among the most sustained and stringent policies based on the Oxford Stringency Index, that is, restrictions on internal movement, public events and gatherings, workplace closures, and international controls.19 In conclusion, I draw attention to this article as we debate our current and future policies including the many impacts in our field, be it opioid and/or methamphetamine use, overdoses, social isolation, limited access to treatment, use of telehealth, and recovery efforts, to name a few. We look forward for this COVID template to be a good platform to be emulated and amended for our international comparisons.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».