Community level youth-led interventions to improve maternal-neonatal outcomes in low- and middle-income countries: A systematic review of randomised trials
Bibliographic record
Abstract
Background: Evidence on the effectiveness of youth-led interventions for improving maternal-neonatal health and well-being of women and gender diverse childbearing people in low-income and middle-income countries (LMICs) is incomplete. We aimed to summarise the evidence on whether community level youth-led interventions can improve maternal and neonatal outcomes in LMICs. Methods: We included experimental studies of youth-led interventions versus no intervention, standard care, or another intervention. Participants were women and gender diverse childbearing people during antepartum, intrapartum, and postpartum periods. MEDLINE, Embase, CINAHL, Global Health, Web of Science, and Cochrane Library, and grey literature were searched to January 2023. All interventions addressing and targeting maternal-neonatal health and well-being that were youth-led and community level were included. Primary outcomes of interest were maternal death and neonatal death. We excluded based on population, intervention, comparison, and outcome (PICO) and design. Two reviewers independently extracted key information from each included study and assessed risk of bias. Random-effects meta-analysis was performed where there were sufficient data. The certainty of evidence was assessed using Grading of Recommendations, Assessment, Development and Evaluation (GRADE). A narrative synthesis was done for results that could not be pooled. Results: Of the 8054 records retrieved, four trials (21 813 enrolled participants) met the inclusion criteria. The Cooperative for Assistance and Relieve Everywhere, Inc. (CARE) Community Score Card intervention compared to standard reproductive health services control did not significantly improve Antenatal Care coverage (difference-in-differences estimate β = 0.04; 95% confidence interval (CI) = -0.11, 0.18, P = 0.610; one study, low certainty of evidence). The multi-component social mobilisation interventions compared to standard of care had no effect on adolescent/youth pregnancy (adjusted odds ratio estimate = 1.08; 95% CI = 0.87, 1.33; three studies; low certainty of evidence). Conclusions: Youth-led interventions in LMICs did not show a significant improvement in maternal outcomes. More studies are required to make more precise conclusions. Registration: PROSPERO: CRD42021288798.
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 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 | 0.018 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".