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Record W3034555923 · doi:10.1186/s13031-020-00285-x

Impact of conflict on maternal and child health service delivery: a country case study of Afghanistan

2020· article· en· W3034555923 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueConflict and Health · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsHospital for Sick Children
FundersDirektoratet for UtviklingssamarbeidInternational Development Research CentreFamily Larsson‐Rosenquist FoundationUNICEFBill and Melinda Gates Foundation
KeywordsPublic healthHealth services researchMedicineEpidemiologyEnvironmental healthHealth servicesBiostatisticsHealth economicsService delivery frameworkChild healthHealth administrationHealth policyService (business)Family medicineNursingBusinessPopulationPathology

Abstract

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INTRODUCTION: Since decades, the health system of Afghanistan has been in disarray due to ongoing conflict. We aimed to explore the direct effects of conflict on provision of reproductive, maternal, newborn, child and adolescent health and nutrition (RMNCAH&N) services and describe the contextual factors influencing these services. METHOD: We conducted a quantitative analysis of secondary data on RMNCAH&N indicators and undertook a supportive qualitative study to help understand processes and contextual factors. For quantitative analysis, we stratified the various provinces of Afghanistan into minimal-, moderate- and severe conflict categories based on battle-related deaths from Uppsala Conflict Data Program (UCDP) and through accessibility of health services using a Delphi methodology. The coverage of RMNCAH&N indicators across the continuum of care were extracted from the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Survey (MICS). The qualitative data was captured by conducting key informant interviews of multi-sectoral stakeholders working in government, NGOs and UN agencies. RESULTS: Comparison of various provinces based on the severity of conflict through Delphi process showed that the mean coverage of various RMNCAH&N indicators including antenatal care (OR: 0.42, 95%CI: 0.32-0.55), facility delivery (OR: 0.42, 95%CI: 0.32-0.56), skilled birth attendance (OR: 0.43, 95%CI: 0.33-0.57), DPT3 (OR: 0.26, 95% CI: 0.20-0.33) and oral rehydration therapy (OR: 0.37, 95% CI: 0.25-0.55) was significantly lower for severe conflict provinces when compared to minimal conflict provinces. The qualitative analysis identified various factors affecting decision making and service delivery including insecurity, cultural norms, unavailability of workforce, poor monitoring, lack of funds and inconsistent supplies. Other factors include weak stewardship, capacity gap at the central level and poor coordination at national, regional and district level. CONCLUSION: RMNCAH&N service delivery has been significantly hampered by conflict in Afghanistan over the last several years. This has been further compromised by poor infrastructure, weak stewardship and poor capacity and collaboration at all levels. With the potential of peace and conflict resolution in Afghanistan, we would underscore the importance of continued oversight and integrated implementation of sustainable, grass root RMNCAH&N services with a focus on reaching the most marginalized.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.053
GPT teacher head0.362
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it