Social network characteristics among adolescents at risk of obesity: a pilot study
Notice bibliographique
Résumé
ABSTRACTContext: Youth obesity has become a global epidemic. Identification of modifiable determinants is needed to develop effective prevention strategies. The Socio-Ecological Model suggests that physical and social environments can both support and inhibit behaviours related to healthy weight. Aspects of one’s personal social network (e.g. size, mode of interactions with contacts, and mean age of network members) might influence health outcomes, such as adiposity in adolescents. Social Network Analysis (SNA) is a conceptual framework, which allows us to investigate the potential relationship of social network characteristics on health-related outcomes. To this end, we developed a questionnaire designed to measure the personal social networks of adolescents and conducted a pilot study.Objective: The main objectives were to describe the structure and characteristics of adolescents’ social networks and to examine whether patterns emerged in relation to adiposity. Methods: We conducted a SNA pilot study nested within the QUALITY study, an ongoing longitudinal study, established in 2005 and designed to investigate the natural history of obesity in Quebec, Canada (n = 630 at baseline). Data were obtained from 46 adolescents during the 3rd phase of data collection when participants were aged 15-17 years old. The outcome was participant’s total body fat percentage measured by Dual-energy X-ray Absorptiometry (%BF). With respect to the SNA data collection, participants (egos) identified up to 10 friends (alters) with whom they discussed important matters. Participants also reported both their own and perceived alters’ lifestyle behaviours, and connections between alters. Characteristics of alters were combined to create the following indicators of support and encouragement: Positive role models (friends who often or sometimes participated in physical activities and eating healthy food), of cheerleaders (positive role models who often or sometimes encouraged the ego to be physically active) and negative role models (friends who rarely or never participated in physical activity and who rarely or never ate healthfully). For each indicator, proportions were computed for each ego network. Analysis: Descriptive statistics were generated for all variables, including network- and ego-level variables. Correlations were computed between all variables, and notably with the outcome, %BF. Sex-specific multilinear regression analyses were performed to further explore the relationship between potential network features and adiposity. Results: The final analytical sample included 28 boys and 16 girls with an average age for both of 16.3 years, and a total of 207 alters. The average %BF was 19.8% for boys and 34.2% for girls. The average proportion of cheerleaders in the network of boys was on average 0.23 and for girls an average of 0.14. Among boys, each increase in tertile of cheerleaders was associated with a decrease in the %BF by almost 8%. In contrast, a modest positive association was observed in girls.Conclusion: Perceived behaviours and encouragement of friends may be associated with adiposity in high-risk youth, but this relationship appears to differ between adolescent boys and girls. Although longitudinal investigations are needed, these preliminary findings suggest that leveraging social networks to enhance lifestyle interventions likely need to be sensitive to gender-based beliefs.Keywords: Obesity, adolescents, pilot study, questionnaire, weight-related lifestyle behaviours, friends, social network
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».