Cannabis Use During Adolescence and Young Adulthood and Academic Achievement
Notice bibliographique
Résumé
Importance: Cannabis use during adolescence and young adulthood may affect academic achievement; however, the magnitude of association remains unclear. Objective: To conduct a systematic review evaluating the association between cannabis use and academic performance. Data Sources: CINAHL, EMBASE, MEDLINE, PsycInfo, PubMed, Scopus, and Web of Science from inception to November 10, 2023. Study Selection: Observational studies examining the association of cannabis use with academic outcomes were selected. The literature search identified 17 622 unique citations. Data Extraction and Synthesis: Pairs of reviewers independently assessed risk of bias and extracted data. Both random-effects models and fixed-effects models were used for meta-analyses, and the Grading of Recommendations Assessment, Development, and Evaluation approach was applied to evaluate the certainty of evidence for each outcome. Data were analyzed from April 6 to May 25, 2024. Main Outcomes and Measures: School grades, school dropout, school absenteeism, grade retention, high school completion, university enrollment, postsecondary degree attainment, and unemployment. Results: Sixty-three studies including 438 329 individuals proved eligible for analysis. Moderate-certainty evidence showed cannabis use during adolescence and young adulthood was probably associated with lower school grades (odds ratio [OR], 0.61 [95% CI, 0.52-0.71] for grade B and above); less likelihood of high school completion (OR, 0.50 [95% CI, 0.33-0.76]), university enrollment (OR, 0.72 [95% CI, 0.60-0.87]), and postsecondary degree attainment (OR, 0.69 [95% CI, 0.62-0.77]); and increased school dropout rate (OR, 2.19 [95% CI, 1.73-2.78]) and school absenteeism (OR, 2.31 [95% CI, 1.76-3.03]). Absolute risk effects ranged from 7% to 14%. Low-certainty evidence suggested that cannabis use may be associated with increased unemployment (OR, 1.50 [95% CI, 1.15-1.96]), with an absolute risk increase of 9%. Subgroup analyses with moderate credibility showed worse academic outcomes for frequent cannabis users and for students who began cannabis use earlier. Conclusions and Relevance: Cannabis use during adolescence and young adulthood was probably associated with increases in school absenteeism and dropout; reduced likelihood of obtaining high academic grades, graduating high school, enrolling in university, and postsecondary degree attainment; and perhaps increased unemployment. Further research is needed to identify interventions and policies that mitigate upstream and downstream factors associated with early cannabis exposure.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,001 | 0,003 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, 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 ».