Healthcare provider and medical cannabis patient communication regarding referral and medication substitution: the Canadian context
Notice bibliographique
Résumé
BACKGROUND: Patients use medical cannabis for a wide array of illnesses and symptoms, and many substitute cannabis for pharmaceuticals. This substitution often occurs without physician oversight, raising patient safety concerns. We aimed to characterize substitution and doctor-patient communication patterns in Canada, where there is a mature market and national regulatory system for medical cannabis. METHODS: We conducted an anonymous, cross-sectional online survey in May 2021 for seven days with adult Canadian federally-authorized medical cannabis patients (N = 2697) registered with two global cannabis companies to evaluate patient perceptions of Primary Care Provider (PCP) knowledge of medical cannabis and communication regarding medical cannabis with PCPs, including PCP authorization of licensure and substitution of cannabis for other medications. RESULTS: Most participants (62.7%, n = 1390) obtained medical cannabis authorization from their PCP. Of those who spoke with their PCP about medical cannabis (82.2%, n = 2217), 38.6% (n = 857) reported that their PCP had "very good" or "excellent" knowledge of medical cannabis and, on average, were moderately confident in their PCP's ability to integrate medical cannabis into treatment. Participants generally reported higher ratings for secondary care providers, with 82.8% (n = 808) of participants rating their secondary care provider's knowledge about medical cannabis as "very good" or "excellent." Overall, 47.1% (n = 1269) of participants reported substituting cannabis for pharmaceuticals or other substances (e.g., alcohol, tobacco/nicotine). Of these, 31.3% (n = 397) reported a delay in informing their PCP of up to 6 months or more, and 34.8% (n = 441) reported that their PCP was still not aware of their substitution. Older, female participants had higher odds of disclosing cannabis substitution to their PCPs. CONCLUSION: Most of the surveyed Canadian medical cannabis patients considered their PCPs knowledgeable about cannabis and were confident in their PCPs' ability to integrate cannabis into treatment plans. However, many surveyed patients substituted cannabis for other medications without consulting their PCPs. These results suggest a lack of integration between mainstream healthcare and medical cannabis that may be improved through physician education and clinical experience.
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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 | 0,008 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,003 |
| 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 ».