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Record W4416831746 · doi:10.2196/80358

Effectiveness of an Educational and Counseling Program (the Green Mother Project Phase 2) to Enhance Breastfeeding and Improve Mothers’ Diets From an Environmental Perspective: Protocol for a Cluster Randomized Controlled Trial

2025· article· en· W4416831746 on OpenAlexvenueno aff
Rosa Cabedo-Ferreiro, Liudmila Liutsko, Judit Cos‐Busquets, Rosa García‐Sierra, Margalida Colldeforns‐Vidal, Azahara Reyes‐Lacalle, Pere Torán‐Monserrat, Míriam Gómez Masvidal, Concepción Violán, Laura Montero‐Pons, Gemma Falguera‐Puig, Gemma Cazorla‐Ortiz

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsBreastfeedingRandomized controlled trialProtocol (science)Cluster (spacecraft)Cluster randomised controlled trialProgram evaluationBreast feeding

Abstract

fetched live from OpenAlex

BACKGROUND: Exclusive breastfeeding is recommended as healthier and more sustainable than formula feeding. It produces less waste, requires fewer resources, and has a smaller environmental impact. Breastfeeding has some environmental impact related to increased maternal dietary needs and the use of feeding accessories. In light of the global climate emergency and suboptimal breastfeeding rates, targeted interventions are urgently needed to promote sustainable infant feeding practices. There are few studies that evaluate sustainability interventions in the postpartum period. OBJECTIVE: The objective of this study is to evaluate the effectiveness of an educational and counseling intervention on breastfeeding and healthy maternal nutrition from an environmental perspective. METHODS: A multicenter prospective intervention study is being conducted in 2 cohorts in primary care centers and hospitals in the north metropolitan area of Barcelona. The control group received standard obstetric care. The experimental group additionally received an educational intervention and health care support on breastfeeding and healthy and sustainable maternal nutrition. Pregnant women were monitored from 24 weeks of gestation to 6 months post partum. The rates of different types of breastfeeding, the women's diet, and the associated environmental impacts (climate change and water footprint) will be analyzed to assess the effectiveness of the intervention. RESULTS: The development of the educational and counseling intervention has been completed, including the creation of the Guide to Good Practices in Breastfeeding, Nutrition, and Sustainability. Health care professionals received targeted training. Recruitment of pregnant women was conducted from December 2023 to December 2024. Prenatal education sessions and specialized care pathways were designed and implemented. Breastfeeding-friendly spaces were adapted to support the participating centers. Data collection for monitoring breastfeeding practices, maternal diet, and environmental impact indicators (carbon footprint and water footprint), with the follow-up period of 6 months post partum, was extended until September 2025, with a complementary missing data collection in October 2025. Data cleaning for final analysis is expected to conclude by January 2026. This study hypothesizes that mothers who receive higher levels of education and counseling support will (1) breastfeed for a longer duration, (2) adopt healthier and more sustainable dietary practices, and (3) reduce environmental impacts associated with both infant feeding accessories and dietary choices. CONCLUSIONS: We expect an increase in the incidence and prevalence rates of breastfeeding and a shift toward a healthy and sustainable diet with low environmental impact. TRIAL REGISTRATION: ClinicalTrials.gov NCT05729581; https://clinicaltrials.gov/study/NCT05729581. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/80358.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.052
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.022
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0150.006
Bibliometrics0.0040.004
Science and technology studies0.0030.004
Scholarly communication0.0040.003
Open science0.0040.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0520.008

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.

Opus teacher head0.057
GPT teacher head0.554
Teacher spread0.497 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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