Examining the Effects of Cannabis Use on Sleep Using Daily Diary Data
Notice bibliographique
Résumé
BACKGROUND: College students in the United States widely report using alcohol and cannabis as a sleep aid. Given the prevalence of sleep problems and insufficient sleep in this population, the high incidence in use and co-use of cannabis and alcohol is unsurprising. Current evidence does not support alcohol as an effective sleep aid and research on the relationship of cannabis to sleep is limited and inconsistent. Furthermore, the majority of current cannabis and sleep studies are limited to retrospective, person-level analyses even though there is a wide range of individual and day-level differences in reactivity to intoxication. PURPOSE: The aim of this study is to examine cannabis and alcohol use and their associations with sleep at both the between-person level (i.e., between-subjects comparison of chronic use behaviors) and within-person level (i.e., day-level comparison of use behaviors). METHOD: This study is a secondary analysis of longitudinal data obtained from a study characterizing the effects of simultaneous alcohol and cannabis use. Participants (n=341) completed surveys up to five times per day during two bursts of 4 weeks (54 days total) that occurred during two consecutive college semesters. Self-reported quantities of cannabis use (as number of uses) and alcohol use (as number of drinks), as well as bedtimes (night) and wake times (morning) were reported. Linear mixed models were conducted in SAS 9.4 to characterize between-person and within-person (person-mean centered) correlations of cannabis or alcohol use and sleep duration. RESULTS: Significant main effects of within-person cannabis (Estimate: 0.019, SE: 0.007, t=2.86, p=0.004) and alcohol (Estimate: -0.0402, SE: 0.0076, t=-5.28, p<0.001) use were found, as was a between-person main effect of average cannabis use (Estimate: 0.038, SE: 0.012, t=3.28, p=0.001) across the full study period. The between-person main effect of average alcohol use was not significant. CONCLUSIONS: The results suggested that generally heavier cannabis users sleep more than their non-using/generally light using counterparts and that they sleep more on nights following heavier use days. Interestingly, the relationship between alcohol and sleep differed between the between-person and within-person levels: alcohol use was dose-dependently associated with reduced sleep duration; however, in this sample, generally heavier alcohol users did not appear to differ in overall sleep duration compared to generally lighter alcohol users. Importantly, this sample included a wide range of substance users, none of whom were in treatment for a cannabis use disorder (CUD) or alcohol use disorder (AUD). Whether these patterns of dose-dependence would be observed over longer time periods or in individuals who meet criteria for CUD or AUD remains to be studied. Future studies will assess the effects of alcohol and cannabis co-use patterns as well as timing of consumption.
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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 | 0,003 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| 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 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 ».