Complementary feeding intervention on stunted Guatemalan children: a randomised controlled trial
Bibliographic record
Abstract
OBJECTIVE/BACKGROUND: Guatemala's indigenous Maya population has one of the highest rates of childhood stunting in the world. The goal of this study was to examine the impact of an intensive, individualised approach to complementary feeding education for caregivers on feeding practices and growth over usual care. DESIGN: An individually randomised (1:1 allocation ratio), parallel-group superiority trial, with blinding of study staff collecting outcome data. SETTING: Rural Maya communities in Guatemala. PARTICIPANTS: 324 children aged 6-24 months with a height-for-age Z score of less than or equal to -2.5 SD were randomised, 161 to the intervention and 163 to usual care. INTERVENTIONS: Community health workers conducted home visits for 6 months, providing usual care or usual care plus individualised caregiver education. MAIN OUTCOMES MEASURES: The main outcome was change in length/height-for-age Z score. Secondary outcomes were changes in complementary feeding indicators. RESULTS: Data were analysed for 296 subjects (intervention 145, usual care 151). There was a non-significant trend to improved growth in the intervention arm (length/height-for-age Z score change difference 0.07(95% CI -0.04 to 0.18)). The intervention led to a 22% improvement in minimum dietary diversity (RR 1.22, 95% CI 1.11 to 1.35) and a 23% improvement in minimal acceptable diet (RR 1.23, 95% CI 1.08 to 1.40) over usual care. CONCLUSIONS: Complementary feeding outcomes improved in the intervention arm, and a non-significant trend towards improved linear growth was observed. Community health workers in a low-resource rural environment can implement individualised caregiver complementary feeding education with significant improvements in child dietary quality over standard approaches. CLINICAL TRIAL REGISTRATION NUMBER: NCT02509936. Stage: Results.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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".