Examining the impact of legalization on the prevalence of driving after using cannabis: A comparison of rural and non-rural parts of Canada
Notice bibliographique
Résumé
OBJECTIVE: The purpose of this study was to examine the likelihood of driving after using cannabis, and of being a passenger with someone who is driving after using cannabis, in rural areas and non-rural areas before and after legalization. METHODS: A multi-wave analysis of Canada's National Cannabis Survey was conducted using logistic regression with interactions to predict the prevalence of driving after using cannabis, and of being a passenger with someone who is driving after using cannabis, in relation to place of residence (rural or non-rural) and in the weeks and months before and after legalization. Three time points were compared: pre-legalization, two months following legalization and 1 year after legalization. RESULTS: At the national level, there are no significant differences between the predicted estimates of driving after using cannabis for those who live in rural and non-rural areas. However, when examining the impact of legalization, we found a significant increase in driving after using cannabis among rural residents directly following legalization. Furthermore, it was observed that this increase in driving after using cannabis returns to pre-legalization rates one year after legalization. By contrast, in the weeks and months following legalization, driving after using cannabis decreased among those living in non-rural areas, and slowly increased soon thereafter. No significant differences were observed, in either time period or group, in the prevalence of being a passenger with someone who is driving after using cannabis. CONCLUSIONS: The finding of significantly higher risk of driving after use of cannabis soon after legalization in rural areas suggests a need for more attention to address immediate concerns for public safety. The increased potential for traffic injuries and deaths in other jurisdictions contemplating legalization supports the call for more and better targeted prevention efforts in rural communities that have far too often been overlooked and under-served.
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 | 0,000 | 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) | 0,000 | 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 ».