Cannabis use motives and associations with personal and work characteristics among Canadian workers: a cross-sectional study
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Notice bibliographique
Résumé
BACKGROUND: Research on cannabis use motives has focused on youth. Little is known about motives among working adults, including how work may play a role. This study aimed to describe cannabis use motives and their connection to work, and identify the personal and work correlates of work-related motives among a sample of workers. METHODS: A national, cross-sectional sample of Canadian workers were queried about their cannabis use. Workers reporting past-year cannabis use (n = 589) were asked their motives for using cannabis and whether each motive was related to work or helped them manage at work (i.e., work-related). Multinomial logistic regression analyses were conducted to estimate the associations of personal and work characteristics with work-related cannabis use motives (no work-related motives, < 50% of motives work-related, ≥ 50% of motives work-related). RESULTS: Use for relaxation (59.3%), enjoyment (47.2%), social reasons (35.3%), coping (35.1%), medical reasons (30.9%), and sleep (29.9%) were the most common motives. Almost 40% of respondents reported one or more of their cannabis use motives were work-related, with coping (19.9%) and relaxation (16.3%) most commonly reported as work-related. Younger age, poorer general health, greater job stress, having a supervisory role, and hazardous work were associated with increased odds of reporting at least some cannabis use motives to be work-related, while work schedule and greater frequency of alcohol use were associated with reduced odds of motives being primarily work-related. CONCLUSIONS: Cannabis use motives among workers are diverse and frequently associated with work. Greater attention to the role of work in motivating cannabis use is warranted.
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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) | 0,000 | 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 découle