The Effects of an Educational Intervention About Front-of-Package Labeling on Food and Beverage Selection Among Children and Their Caregivers: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Overweight and obesity pose a global public health challenge and have a multifactorial origin. One of these factors includes obesogenic environments, which promote ultraprocessed foods characterized by being high in calories, saturated fats, added sugars, and sodium. In Mexico, it has been estimated that 30% of the total energy consumed comes from processed foods. The Modification to the Official Mexican Standards introduces nutritional information through black octagonal seals that alert consumers about products with excessive amounts of some components for a better food selection in the population. However, the effects of warning labels on processed food selection and purchases among children remain unknown. OBJECTIVE: We aimed to evaluate the impact of a digital educational intervention focusing on front-of-package warning labels on the food selection and purchasing behavior of elementary schoolchildren and their caregivers. METHODS: Children from 4 elementary schools in Mexico City, 2 public and 2 private schools, will participate in a randomized controlled trial. The schools will be chosen by simple random sampling. Schools will be randomized into 2 groups: intervention and control. In the control group, the dyads (caregiver-schoolchildren) will receive general nutritional education, and in the intervention group, they will receive guidance on reading labels and raising awareness about the impact of consuming ultraprocessed products on health. The educational intervention will be conducted via a website. Baseline measurements will be taken for both groups at 3 and 6 months. All participants will have access to an online store through the website, allowing them to engage in exercises for selecting and purchasing food and beverages. In addition, other measures will include a brief 5-question exam to evaluate theoretical understanding, a 24-hour reminder, a survey on food habits and consumption, application of a food preference scale, anthropometric measurements, and recording of school lunch choices. RESULTS: Registration and funding were authorized in 2022, and we will begin data collection in September 2024. Recruitment has not yet taken place, but the status of data analysis and expected results will be published in April 2025. CONCLUSIONS: The study is expected to contribute to evaluating whether reinforcing front-of-package warning labels with education enhances its effects and makes them more sustainable. Conducting this study will allow us to propose whether or not it is necessary to develop new intervention strategies related to front-of-package labeling for a better understanding of the population, improved food choices, and better health outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT06102473; https://clinicaltrials.gov/study/NCT06102473. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/54783.
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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 | 0.026 | 0.023 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.006 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.065 | 0.010 |
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".