Healthcare practitioner perceptions on barriers impacting cannabis prescribing practices
Notice bibliographique
Résumé
BACKGROUND: Canadians seeking medical cannabis (MC) may encounter difficulties in finding a healthcare provider (HCP) who authorizes their access to it. Barriers that HCPs face in authorizing MC are unclear. The objectives of this study were to evaluate HCP opinions, knowledge, comfort, and practice in MC prescribing and counseling on recreational cannabis use, and whether the COVID-19 pandemic affected MC prescribing practices. METHODS: 2021, ninety-one healthcare associations were asked to distribute the survey to their members, and an advertisement was placed in the online Canadian Medical Association Journal. Descriptive statistics were used to analyze the results. RESULTS: Twenty-four organizations agreed to disseminate the survey and 70 individuals completed it. Of respondents, 71% were attending physicians or medical residents, while the remainder were nurses, pharmacists or other HCPs. Almost none (6%) received training in MC in professional school but 60% did receive other training (e.g., workshops, conferences). Over half (57%) received more questions regarding MC since recreational cannabis was legalized, and 82% reported having patients who use MC. However, 56% felt uncomfortable or ambivalent regarding their knowledge of MC, and 27% were unfamiliar with the requirements for obtaining MC in Canada. The most common symptoms for recommending MC were pain and nausea, whereas the most common conditions for recommending it were cancer and intractable pain. The strongest barrier to authorizing MC was uncertainty in safe and effective dosage and routes of administration. The strongest barrier to recommending or authorizing MC was the lack of research evidence demonstrating its safety and efficacy. During the pandemic, many respondents reported that a greater number of their patients used cannabis to relieve anxiety and depression. CONCLUSIONS: Our results suggest that HCPs across Canada who responded to our survey are unfamiliar with topics related to MC. The strongest barriers appear to be lack of clinical research, and uncertainty in safe and effective MC administration. Increasing research, training, and knowledge may help HCPs feel more equipped to make informed treatment/prescribing decisions, which may help to improve access to MC.
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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 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 ».