Exploring Children's Knowledge of Healthy Eating, Digital Media Use, and Caregivers’ Perspectives to Inform Design and Contextual Considerations for Game-Based Interventions in Schools for Low-Income Families in Lima, Peru: Survey Study
Notice bibliographique
Résumé
BACKGROUND: The prevalence of overweight and obesity in schoolchildren is increasing in Peru. Given the increased use of digital media, there is potential to develop effective digital health interventions to promote healthy eating practices at schools. This study investigates the needs of schoolchildren in relation to healthy eating and the potential role of digital media to inform the design of game-based nutritional interventions. OBJECTIVE: This study aims to explore schoolchildren's knowledge about healthy eating and use of and preferences for digital media to inform the future development of a serious game to promote healthy eating. METHODS: A survey was conducted in 17 schools in metropolitan Lima, Peru. The information was collected virtually with specific questions for the schoolchild and their caregiver during October 2021 and November 2021 and following the COVID-19 public health restrictions. Questions on nutritional knowledge and preferences for and use of digital media were included. In the descriptive analysis, the percentages of the variables of interest were calculated. RESULTS: We received 3937 validated responses from caregivers and schoolchildren. The schoolchildren were aged between 8 years and 15 years (2030/3937, 55.8% girls). Of the caregivers, 83% (3267/3937) were mothers, and 56.5% (2223/3937) had a secondary education. Only 5.2% (203/3937) of schoolchildren's homes did not have internet access; such access was through WiFi (2151/3937, 54.6%) and mobile internet (1314/3937, 33.4%). In addition, 95.3% (3753/3937) of schoolchildren's homes had a mobile phone; 31.3% (1233/3937) had computers. In relation to children's knowledge on healthy eating, 42.2% (1663/3937) of schoolchildren did not know the recommendation to consume at least 5 servings of fruits and vegetables daily, 46.7% (1837/3937) of schoolchildren did not identify front-of-package warning labels (FOPWLs), and 63.9% (2514/3937) did not relate the presence of an FOPWL with dietary risk. Most schoolchildren (3100/3937, 78.7%) preferred to use a mobile phone. Only 38.3% (1509/3937) indicated they preferred a computer. In addition, 47.9% (1885/3937) of caregivers considered that the internet helps in the education of schoolchildren, 82.7% (3254/3937) of caregivers gave permission for schoolchildren to play games with digital devices, and 38% (1495/3937) of caregivers considered that traditional digital games for children are inadequate. CONCLUSIONS: The results suggest that knowledge about nutrition in Peruvian schoolchildren has limitations. Most schoolchildren have access to the internet, with mobile phones being the device type with the greatest availability and preference for use. Caregivers' perspectives on games and schoolchildren, including a greater interest in using digital games, provide opportunities for the design and development of serious games to improve schoolchildren's nutritional knowledge in Peru. Future research is needed to explore the potential of serious games that are tailored to the needs and preferences of both schoolchildren and their caregivers in Peru in order to promote healthy eating.
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 | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 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 ».