The long‐term effectiveness of universal, selective and combined prevention for alcohol use during adolescence: 36‐month outcomes from a cluster randomized controlled trial
Notice bibliographique
Résumé
AIM: To compare the long-term universal outcomes of the Climate Schools programme, the selective preventure programme and their combined implementation to standard substance use education in reducing the uptake of alcohol use, engagement in binge drinking and alcohol-related harms over a 3-year period. DESIGN: A cluster-randomized controlled trial. SETTING AND PARTICIPANTS: Substance use prevention programmes delivered in Australian secondary schools. Students from 26 Australian secondary schools (n = 2190), mean age at baseline 13.3 years (standard deviation = 0.48), 57.4% male. Schools were recruited between September 2011 and February 2012. INTERVENTIONS: Schools were block-randomized to one of four groups: universal prevention (climate; 12 × 40-minute lessons); selective prevention (preventure; 2 × 90-minute sessions); combined prevention (climate and preventure; CAP); or health education as usual (control). The climate intervention delivered 12 × 40-minute lessons aimed at reducing alcohol and cannabis use and related harms. The preventure intervention delivered 2 × 90-minute group sessions to high-risk students. The CAP group implemented the climate programme to the entire year group and the preventure programme to the high-risk students. MEASUREMENTS: Participants were all consenting 8th grade students (in 2012) assessed at baseline, post-intervention (6-9 months post-baseline) and at 12, 24 and 36 months post-baseline on measures of alcohol use, knowledge and related harms. Primary outcomes were alcohol use, binge drinking (five or more standard drinks) and alcohol-related harms, obtained from all students regardless of whether or not they received intervention. Intervention effects at 36 months post-baseline were estimated from generalized multi-level mixed models using data from all time-points and accounting for school-level clustering. Exploratory analyses examined intervention effects among low- and high-risk adolescents. FINDINGS: Compared with students in the control condition, students in the climate, preventure and CAP groups demonstrated significantly slower increases in their likelihood to drink any alcohol [odds ratio (OR) = 0.64, 95% confidence interval (CI) = 0.50-0.82 for climate; OR = 0.55, 95% CI = 0.43-0.71 for preventure and OR = 0.67, 95% CI = 0.53-0.84 for CAP] to engage in binge drinking (OR = 0.60, 95% CI = 0.44-0.82 for climate; OR = 0.59, 95% CI = 0.44-0.80 for preventure and OR = 0.68, 95% CI = 0.51-0.92 for CAP) and to experience alcohol harms (OR = 0.63, 95% CI = 0.49-0.82 for climate; OR = 0.55, 95% CI = 0.43-0.71 for preventure and OR = 0.64, 95% CI = 0.50-0.81 for CAP). There was no strong evidence that the combined approach showed advantages over universal prevention. The direction and magnitude of effects were consistent in low- and high-risk adolescents. CONCLUSIONS: The universal Climate Schools programme and the selective preventure programme were effective in reducing alcohol consumption and alcohol problems compared with standard Australian health education, when trialled individually and together over a 3-year period.
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 | 0,005 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 ».