The role of peer victimization in the physical activity and screen time of adolescents: a cross-sectional study
Notice bibliographique
Résumé
BACKGROUND: Negative peer experiences may lead adolescents with overweight and obesity to be less active and engage in more sitting-related behaviors. Our study is among the first to empirically test these associations and hypothesized that 1) peer victimization would mediate the negative association between body weight status and moderate-to-vigorous physical activity (MVPA), and 2) peer victimization would mediate the positive association between body weight status and screen time. Differences by gender were also explored. METHODS: Participants were a part of the Year 1 data (2012-2013) from the COMPASS study, a prospective cohort study of high school students in Ontario and Alberta, Canada. The final sample consisted of 18,147 students in grades 9 to 12 from 43 Ontario secondary schools. The predictor variable was weight status (non-overweight vs. overweight/obese), the mediator was peer victimization, and the outcome variables were screen time and MVPA. Multilevel path analysis was conducted, controlling for clustering within schools and covariates. A few differences were observed between males and females; therefore, the results are stratified by gender. RESULTS: For both males and females peer victimization partially mediated the association between weight status and screen time. Specifically, females with overweight/obesity reported 34 more minutes/day of screen time than did females who were not overweight and 2 of these minutes could be attributed to experiencing peer victimization. Similarly, males who were overweight/obese reported 13 more minutes/day of screen time than the males who were not overweight and 1 of these minutes could be attributed to experiencing more victimization. Males and females who were overweight/obese also reported less MVPA compared to those who were not overweight; however, peer victimization did not mediate these associations in the hypothesized direction. CONCLUSIONS: We found that higher rates of peer victimization experienced by adolescents with overweight and obesity partially explained why they engaged in more screen time than adolescents who were not overweight. However, the effects were small and may be of limited practical significance. Because this is one of the first studies to investigate these associations, more research is needed before bully prevention or conflict resolution training are explored as intervention strategies.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 | 0,000 |
| 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 ».