A Controlled Before-and-After Perspective on the Improving Maternal, Neonatal, and Child Survival Program in Rural Bangladesh: An Impact Analysis
Bibliographic record
Abstract
OBJECTIVES: We evaluated the impact of the Improving Maternal, Neonatal, and Child Survival (IMNCS) project, which is being implemented by BRAC in rural communities in Bangladesh. METHODS: Four districts received program intervention i.e. trained community health workers to deliver essential maternal, neonatal, and child healthcare and nutrition services while two districts were treated as comparison group. A quasi-experimental study design (compared before-and-after) was undertaken. Baseline survey was conducted in 2008 among 7200 women followed by end line in 2012 among 4800 women with similar characteristics in the same villages. We evaluated maternal antenatal and post natal checkup, birth plans and delivery, complication and referred cases during antenatal checkup and post natal period, and child health indicators such as birth asphyxia, neonatal sepsis, and its management by the medically trained provider. FINDINGS: Increased number (four or more) antenatal visits, skill-birth attended delivery and postnatal visits (three or more) in the intervention group preceding four-year intervention period were observed compare to their counterpart. We noted negative difference-in-difference estimator (-5.0%, P = 0.159) regarding to the all major birth plans i.e. delivery place, birth attendant, and saved money in the comparison areas. Significant reduction of ante-partum and intra-partum complications occurred in the intervention group, contrary complications of such event increased in the comparison areas (-6.3%, P<0.05 and -20.5%, P<0.001 respectively). Referral case to the health centers due to these complications boosted significantly in intervention group than comparison group (2.3%, P<0.01 and 6.6%, P<0.001 respectively). Mother's knowledge of breastfeeding initiation and the practice of initiating breastfeeding within an hour of birth amplified significantly (14.6%, P<0.001 and 8.3%, P<0.001 respectively). We did not find any significant difference regards to the management of low birth weight by the medically trained health care provider and complete vaccination between the intervention and comparison arm. CONCLUSION: Medically trained health care provider assisted community based public health intervention could increase number of antenatal and postnatal visit, thereby could decrease pregnancy associated complications. These interventions may be considered for further up scaling when resources are limited.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".