Clusters of Contemporary Risk and Their Relationship to Mental Well-Being Among 15-Year-Old Adolescents Across 37 Countries
Notice bibliographique
Résumé
PURPOSE: Adolescents' mental well-being has become a growing public health concern. Adolescents' daily lives and their engagement in risks have changed dramatically in the course of the 21st century, leading to a need to update traditional models of risk to include new exposures and behaviors. To date, studies have examined the relationship between (mainly traditional) risk behaviors and adolescent mental well-being or looked at risk factors that jeopardize mental well-being such as lack of social support but have not combined them together to highlight the most significant risks for adolescent mental well-being today. The present study included new and traditional risk behaviors and risk factors, robustly derived an empirically based model of clusters of risk, and examined the relative association of these clusters to adolescent mental well-being. METHODS: Data from the 2017-2018 Health Behaviours in School-aged Children study were used. The sample included 32,884 adolescents (51.7% girls) aged 15 years from 37 countries and regions. The principal component analysis was used to determine the existence of clusters of risk, using 21 items related to adolescent mental well-being that included both risk behaviors (e.g., substance use) and risk factors (e.g., peer support). Analysis was conducted in both a randomly split training and test set and in gender separate models. Mixed-effects logistic regressions examined the association between clusters of risk and mental well-being indices (low life satisfaction and psychosomatic complaints). RESULTS: Seven clusters of risk were identified: substance use and early sex, low social support, insufficient nutrition, bullying, sugary foods and drinks, physical health risk, and problematic social media use (SMU). Low social support and SMU were the strongest predictors of low life satisfaction (odds ratios = 2.167 and 1.330, respectively) and psychosomatic complaints (odds ratio = 1.687 and 1.386, respectively). Few gender differences in predictors were found. Exposure to bullying was somewhat more associated with psychosomatic complaints for girls, whereas physical health risk was associated with reduced relative odds of low life satisfaction among boys. Split-sample validation and out-of-sample prediction confirmed the robustness of the results. CONCLUSIONS: The results highlight the importance of contemporary clusters of risk, such as low social support and SMU in the mental well-being of young people and the need to focus on these as targets for prevention. We propose that future studies should use composite risk measures that take into account both risk behaviors and risk factors to explain adolescents' mental well-being.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,001 |
| 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 ».