Antenatal care interventions in Afghanistan from 2000 to 2024: a rapid realist review
Bibliographic record
Abstract
INTRODUCTION: In response to the high maternal mortality in Afghanistan, the government emphasised enhancing antenatal care (ANC) coverage to improve skilled birth attendance and reduce maternal mortality. This study aimed to explain how and why ANC interventions worked, for whom, and under what circumstances in Afghanistan between 2000 and 2024. METHODS: A rapid realist review was conducted to identify underlying programme theories and examine contextual factors and key mechanisms influencing ANC outcomes, with input from a panel of national experts. Data were extracted using context-mechanism-outcome (CMO) configurations to develop and refine theories for policy recommendations. RESULTS: From 3502 papers, 1860 duplicates were removed, 63 were screened for full text and 25 were included in the final review. In total, 29 CMOs were inferred across nine interventions, classified at individual, interpersonal, community and institutional levels. We found that ANC interventions could work best by empowering women and healthcare workers (HCWs), involving husbands, hiring female community health workers (CHWs), ensuring regular contact with the same HCWs, endorsing health messages by the government, incentivising CHWs and designing and implementing interventions using participatory approaches. Interventions are less successful when there is a lack of community trust in service quality or HCW qualifications, low decision-making ability among women, discomfort during travel to health facilities, adherence to traditional practices and beliefs, hiring CHWs from outside the community, chronic stress and lack of support among HCWs and unrecognised incentives. CONCLUSION: Our evidence synthesis can inform donors, policymakers and implementers on how to design more effective ANC interventions to achieve better health outcomes in Afghanistan. By emphasising intervention evaluation and ANC quality improvement, it highlights the importance of key social elements, such as cultural norms, power dynamics, relationships, beliefs and trust, which are likely to maximise impact. Community involvement is essential for designing and implementing effective and sustainable ANC interventions.
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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 | 0.023 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".