The effects tailored interventions on cannabis use motives
Notice bibliographique
Résumé
Background: The motives for cannabis affect on cannabis use and cannabis use consequences. Coping with stress is among the frequent motives for cannabis use. However, non stressed youth may use cannabis for self-enhancing motives like boosting confidence. Both motives are associated with higher frequency of cannabis use and more negative consequences (e.g., effects on schoolwork quality). Interventions targeting these distinctive motives may need to be tailored to assist youth trying to reduce cannabis use. The purposes of this study were: to examine the effect of cannabis use interventions on the change in motives of use; and whether motives for use are associated with hours per week using cannabis. Methods: Participants were from a cross national study including US and Canadian youth (n= 781). Participants included in the current analysis were from two Canadian Universities (n = 397, 54% female, median age = 21) were randomized into either the Cannabis eCHECKUP TO GO or Healthy Stress Management (HSM) intervention. Both interventions were administrated online and assessed at baseline and at a 4- to 6-week follow-up. Eligible youth reported using cannabis more than once a week and wanted to reduce their cannabis use. The 19 items to the question “what do you like about cannabis” were used as an assessment of motives for use (e.g., I feel more courageous, I feel more confident, cannabis helps me reduce stress, cannabis helps me sleep). Confirmatory Factor Analysis showed that a 2-factor model of cannabis use motives (self-confidence and stress-coping) fit the data adequately (CFI = 0.795, RMSEA [90% CI] = .063 [.057, .069]) after removing 2 poorly fitting items. Results: Across conditions self-confidence motives (T1: eCHECKUP condition M = 4.05(2.55), HSM condition M = 4.13(2.43); T2: eCHECKUP condition M = 4.09(2.50), HSM condition M = 4.36(2.28)) were endorse less than stress-coping motives (T1: eCHECKUP condition M = 6.48(1.92), HSM condition M = 6.25(1.78); T2: eCHECKUP condition M = 6.20(1.99), HSM condition M = 6.32(1.96)). Stress-coping motives were significantly correlated with the time spent high (hours a week) (T1 r= .21, T2: r=.26). A repeated measures MANOVA showed a significant interaction between time and intervention condition for the stress-coping motives only (F(1)= 4.08, p = .04). Participants in the Healthy Stress Management condition reported a significant decrease in the amount of stress-coping motives at the follow-up. Conclusions: These results demonstrate that motives of cannabis use can change over the course of a short online intervention for students seeking to reduce their use. In particular, the Healthy Stress Management condition helped participants reduce their stress-coping motives at T2. Neither intervention affected self confidence motives in the short term. These may be harder to address and may fuel continued use over time, even for youth hoping to change.
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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) | 0,010 | 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 ».