Maternal and Child Health (MCH) Handbook and Its Effect on Maternal and Child Health Care: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
To search the literature for evidence for examining the effect of MCH Handbooks to promote and improve health outcomes of the Maternal and Child Health care in developing countries.Pub Med, EMBASE, Cochrane, Web of Science, and Google Scholar were searched.Study quality and the risk of bias were evaluated using the Cochrane Handbook.A random effects meta-analysis was performed.The qualitative findings were also presented in a tabular form.The search resulted in 359 studies and 30 articles were included for full text screening and only seven were included in the meta-analysis.The estimated Risk Ratio (RR) for knowledge, practice and attitude of mothers on Maternal and Child Health Care were better among MCH Handbook users than non-MCH Handbook users.When comparing non-MCH handbook users to MCH handbook users for women's knowledge of antenatal care visits, RR was 0.81 (95% Confidence Interval [CI] 0.78-0.84)and for knowledge of danger signs RR was 0.51, 95% CI 0.45-0.59.Practice-related variables such as birth weight measured within 48hrs found RR 0.81, 95% CI 0.79-0.82.For delivery at health facility the RR when comparing non-MCH handbook users to MCH handbook users was 0.82, 95% CI 0.62-1.08Finally, attitude-related variables such as positive changes in attitude on pregnancy care calculated RR 0.33, 95% CI 0.14-0.81when comparing non-MCH handbook users to MCH handbook users.The positive impacts of the MCH Handbook on knowledge, practice, and attitude-related variables suggest that the MCH Handbook is an effective tool to promote the maternal and child health care.In addition, MCH Handbook may offer an alternative tool for educating mothers for better maternal and child health care.There is a need for additional research to explore gaps identified in the current literature.
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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 | 0.011 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.021 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".