Promoting Healthier Meal Selection and Intake Among Children in Restaurants: Protocol for a Cluster-Randomized Trial
Notice bibliographique
Résumé
BACKGROUND: US children's diets are high in calories and are of poor nutritional quality, and a likely contributing factor is the consumption of food from restaurants. While children readily accept the sweet and salty foods that characterize restaurant children's menus, research shows that their taste preferences are malleable, and regular exposure to healthier foods can promote their acceptance. OBJECTIVE: We describe a cluster-randomized controlled trial testing the effects of behavioral intervention strategies (choice architecture and repeated exposure) on ordering and dietary intake among children in restaurants and present baseline demographic data for the study cohort. METHODS: Six locations of a regional quick-service restaurant chain were randomized to the intervention or control group in pairs based on income in surrounding census tracts. Families with children aged 4 to 8 years were recruited and asked to complete 8 visits to the study restaurant, including a baseline assessment completed at the time of enrollment, followed by 6 visits during a designated 2-month exposure period and a final posttest assessment. Intervention content provided to intervention group families after baseline assessments includes placemats promoting 2 healthier kids' meals and the opportunity to redeem their kids' meal "cone token" for a toy instead of a dessert (choice architecture strategies). In addition, participating families receive frequent diner cards, which can be used to earn a free kids' meal after purchasing a promoted kids' meal 6 times (repeated exposure strategy). Families in control restaurants receive generic versions of these materials (eg, frequent diner cards that can be redeemed for a free kids' meal after purchasing any 6 kids' meals). The primary outcome is the meal ordered for the child at a posttest restaurant visit following the exposure period (ie, whether or not a promoted meal was ordered). Additional order data will include calories, saturated fat, sodium, and sugar content of children's orders at posttest. Other outcomes include children's in-restaurant and daily consumption of calories, saturated fat, sodium, and sugar. RESULTS: This study was funded in 2019, with preregistration completed in 2020, data collection occurring from June 2021 to November 2024, and data processing, analysis, and primary outcome manuscript preparation in 2025-2026. A total of 236 families provided baseline data on children's orders and comprise the study cohort; 234 of these families provided demographic data (n=184, 78.3% female parents; n=133, 56.8% female children; child mean age 6.5, SD 1.3 years). CONCLUSIONS: Given that restaurants are normative eating contexts for many children, this intervention has the potential to impact children's dietary intake and health. If found to be successful, future directions could include scaling the current intervention approach and conducting further effectiveness, implementation, and dissemination research to understand its applicability and impact across different types of restaurants and sociodemographic contexts. TRIAL REGISTRATION: ClinicalTrials.gov NCT04334525; https://clinicaltrials.gov/study/NCT04334525. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/73618.
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 | 0,041 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,008 | 0,004 |
| Méta-épidémiologie (sens large) | 0,013 | 0,005 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,008 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,097 | 0,016 |
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 ».