Cannabis Use Among Older Adults
Notice bibliographique
Résumé
Importance: Little is known about patterns (forms, frequency, and reasons) and factors associated with cannabis use in older veterans (aged ≥65 years). Objective: To examine factors associated with past 30-day cannabis use and cannabis use disorder (CUD) in older veterans. Design, Setting, and Participants: In this cross-sectional study, community-dwelling adults aged 65 to 84 years who used Veterans Health Administration care were interviewed between February 5, 2020, and August 29, 2023. Exposure: Sociodemographic, behavioral, and health-related characteristics. Main Outcomes and Measures: Past 30-day cannabis use (smoking, vaping, dabbing, or edibles) and any CUD (≥2 criteria based on Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition]) were assessed using weighted multivariable logistic regressions. Results: Of the 4503 participants (weighted mean age, 73.3 years [95% CI, 73.0-73.5 years]; 85.4% [95% CI, 83.6%-87.2%] men), 58.2% (95% CI, 55.3%-61.0%) had ever used cannabis, 28.9% (95% CI, 26.0%-31.8%) of whom reported using cannabis for medical reasons, most commonly for pain (56.4%; 95% CI, 50.9%-61.9%), mood or mental health (18.4%; 95% CI, 14.7%-22.1%), and sleep (16.0%; 95% CI, 11.9%-20.0%). More than 1 in 10 reported past 30-day cannabis use (10.3%; 95% CI, 8.9%-11.7%), with 52.4% (95% CI, 45.4%-59.4%) of these using cannabis for 20 days or more; smoking (72.4%; 95% CI, 65.4%-79.3%) and edibles (36.9%; 95% CI, 29.8%-43.9%) were the most common forms of use. Characteristics associated with past 30-day use included younger age (65-75 years), economic hardship, tobacco and illicit drug use, and residing in a state with recreationally legal cannabis. Among those with past 30-day cannabis use, 36.3% (95% CI, 30.1%-42.6%) screened positive for CUD, with higher odds among younger respondents, those reporting anxiety, those with 1 or more deficits in activities of daily living, those with illicit drug use, those with frequent cannabis use, and those using cannabis recreationally. Past 30-day inhaled cannabis use, compared with edibles only, was associated with increased odds of any CUD (adjusted odds ratio, 3.56; 95% CI, 1.12-11.26). Conclusions and Relevance: In this cross-sectional study of cannabis use in older veterans, use was common, and more than one-third who used in the past 30 days had any CUD. The prevalence of past 30-day cannabis use was close to tobacco use prevalence, and risk factors for cannabis use were similar to those observed in other populations. Frequent and inhaled cannabis use was associated with higher odds of any CUD. Routine health screening for cannabis use in Veterans Health Administration clinical settings is necessary to identify older adults with cannabis use.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».