Effect of the Mamás del Río programme on essential newborn care: a three-year before-and-after outcome evaluation of a community-based, maternal and neonatal health intervention in the Peruvian Amazon
Bibliographic record
Abstract
Background: Despite remarkable progress in maternal and neonatal health, regional inequalities persist in Peru. In rural areas of Amazonian Loreto, access to quality care is difficult, home births are frequent, and neonatal mortality is high. We conducted a prospective before-and-after study to assess the effect after implementation and over time of a community-based intervention on essential newborn care (ENC). Methods: Mamás del Río consists of tablet-enhanced educational home visits by Community health workers (CHW) to pregnant women and mothers of newborns, with supportive training on ENC of traditional birth attendants and facility staff. The study area comprised 79 rural communities of three districts in Loreto. Primary outcomes were ENC practices in home births, secondary outcomes were ENC in facility births as well as healthcare seeking, measured at baseline before and at year 2 and year 3 after intervention implementation. Community censuses included questionnaires to women aged 15-49 years with a live birth. We calculated prevalence of outcomes at each time point and estimated adjusted prevalence differences (PD) between time points using post-estimation based on logistic regression. Findings: Following implementation early 2019, 97% of communities had a trained CHW. At year 2 follow-up, 63% (322/530) of women received a CHW visit during pregnancy. Seven out of nine ENC indicators among home births improved, with largest adjusted prevalence differences in immediate skin-to-skin contact (50% [95% CI: 42-58], p < 0.0001), colostrum feeding (45% [35-54], p < 0.0001), and cord care (19% [10-28], p = 0.0001). Improvements were maintained at year 3, except for cord care. At year 2, among facility births only three ENC indicators improved, while more women gave birth in a facility. Sensitivity analyses showed ENC prevalence was similar before compared to after onset of Covid-19 lockdown. Interpretation: ENC practices in home births improved consistently and changes were sustained over time, despite the onset of the Covid-19 pandemic. A community-based approach for behaviour-change in home-based newborn care appears effective. Process evaluation of mechanisms will help to explain observed effects and understand transferability of findings. Funding: Grand Challenges Canada and Peruvian National Council of Science and Technology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".