Cannabis Consumption in People Living with HIV: Reasons for Use, Secondary Effects, and Opportunities for Health Education
Notice bibliographique
Résumé
Abstract Introduction: Rates of cannabis consumption range from 40% to 74% among people living with HIV (PLWH). Little is known about the reasons for cannabis use, related modes of administration, effectiveness for symptom relief, or undesirable effects in the modern antiretroviral therapy (ART) era. Our aim was to conduct an exploratory study to identify potential areas for further evaluation and intervention. Materials and Methods: From January to June 2018, health care providers at the Chronic Viral Illness Service in Montreal, Canada, asked their patients about cannabis use during routine visits. Patients reporting cannabis use were invited to complete a 20-min coordinator-administered questionnaire. Questions related to patterns of use, modes of administration, reasons for use, secondary effects, and HIV health-related factors (e.g., adherence to ART). Results: One hundred and four PLWH reporting cannabis use participated. Median age was 54 years (interquartile range [IQR] 46–59), 13% were female, and 42% were HIV-Hepatitis C co-infected. Median CD4 count was 590 cells/mm 3 (IQR 390–821), 95% of participants were on ART, and 88% had suppressed viral loads. Reported cannabis use was more than once daily (32%); daily (25%); weekly (22%); monthly (17%); and rarely (twice to thrice per year; 6%). The majority of participants (97%) smoked dry plant cannabis. Other modes included vaping (12%), capsules (2%), edibles (21%), and oils (12%). Common reasons for cannabis use were for pleasure (68%) and to reduce anxiety (57%), stress (55%), and pain (57%). Many participants found cannabis “quite effective” or “extremely effective” (45%) for symptom relief. Secondary effects included feeling high (74%), increased cough (45%), paranoia (22%), palpitations (20%), and increased anxiety (21%). Over two-thirds of participants indicated that secondary effects were not bothersome at all. Most participants (68%) rarely missed doses of their ART, while 27% missed occasionally (once to twice per month). The most commonly accessed sources of information about cannabis were friends (77%) and the internet (55%). Conclusion: The most common reasons for cannabis use in our population were for pleasure, followed by reduction of stress/anxiety and symptoms associated with a medical condition. Most smoke cannabis and rate cannabis as quite effective for symptom relief. While many participants experience secondary effects, most are not bothered by these symptoms. Amid widespread changes in the regulatory landscape of recreational cannabis, health care providers should be prepared to answer questions about cannabis.
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 | 0,001 | 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 | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».