ReviewBMJ open2025
Antenatal care interventions in Afghanistan from 2000 to 2024: a rapid realist review.
Review in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Postnatal Care Service Utilization and Associated Factors Among Women in Rural Afghanistan: A Cross-Sectional Analysis of the 2022-2023 Multiple Indicator Cluster Survey.Health science reports · 2026Article
- Effectiveness of a Health Belief Model-Based Educational Intervention on Iron-Folic Acid Supplement Intake Among Pregnant Women in Southern Afghanistan: A Quasi-Experimental Study.International journal of women's health · 2026Article
- Barriers and Facilitators of Compliance with Iron-Folic Acid Supplementation Among Pregnant Women in Southern Afghanistan: A Qualitative Study.Patient preference and adherence · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionIn 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.
methodsA 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.
resultsFrom 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.
conclusionOur 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.