Promoting Healthier Meal Selection and Intake Among Children in Restaurants: Protocol for a Cluster-Randomized Trial
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.037 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.097 | 0.016 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".