401 - Cannabis and Older Adults
Notice bibliographique
Résumé
The National Cannabis Survey results indicates that cannabis consumption among older adults has been accelerating at a much faster pace than other age groups in Canada. Internationally, an increasing number of countries and U.S. states have also legalized medical and non-medical cannabis.More than 1500 physicians, nurse practitioners, other healthcare providers, healthcare students, older adults and caregivers of older adults responded to a needs assessment survey on Cannabis and Older Adults distributed by the Canadian Coalition for Seniors’ Mental Health (CCSMH) in the fall of 2020.Responses showed that 89% of physicians and nurse practitioners and 76% of other healthcare providers are aware of older patients in their practice using cannabis. Despite this fact, only 39% of physicians and nurse practitioners and 26% of other healthcare providers feel strongly or very strongly that they have sufficient knowledge and expertise to address older patients’ and theircaregivers’ questions about cannabis.Older adults who responded to the survey indicated that their most common reasons for using cannabis were pain, sleep and anxiety. Fifty-one percent responded that they had talked to their doctor or healthcare provider about cannabis but 41% of those older adults stated that their doctor or healthcare provider were unable to answer their questions. Older adults reported they access information on cannabis from the internet (45%), physicians (40%), friends and family (34%), cannabis stores and clinics (28%), the media (24%), and other healthcare providers (16%). Fifty-four percent of older adult respondents who use cannabis do so with a prescription or medical authorization from their physician/nurse practitioner for medical/therapeutic reasons. One quarter of respondents indicated they use cannabis for non-medical reasons (for recreational use).Although there is a reported gap in knowledge regarding cannabis and older adults, physicians, nurse practitioners, other healthcare providers and healthcare students all reported they are eager to learn more about how to talk with patients, how to authorize and prescribe cannabis appropriately, how to mitigate risks and assess for cannabis use disorder in older adults. CCSMH will be launching a physician- accredited e-learning course on Cannabis and Older Adults in January 2022.
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 | 0,000 | 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) | 0,001 | 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 ».