Community midwifery initiatives in fragile and conflict-affected countries: a scoping review of approaches from recruitment to retention
Bibliographic record
Abstract
BACKGROUND: Birth assisted by skilled health workers is one of the most effective interventions for reducing maternal and neonatal mortality. Fragile and conflict-affected states and situations (FCAS), with one-third of global maternal deaths, face significant challenges in achieving skilled care at birth, particularly in health workforce development. The importance of community-level midwifery services to improve skilled care is internationally recognized, but the literature on FCAS is limited. This review aimed to examine community midwifery (CMW) approaches, from recruitment to retention, in FCAS. METHODS: This scoping review design adapted Arksey and O'Malley's six-stage framework. Data collection included systematic searching of seven databases, purposive hand-searching of reference lists and web sites, and stakeholder engagement for additional information. Potential sources were screened against inclusion and exclusion criteria. Included sources were appraised for methodological quality using the McGill University Mixed Methods Appraisal Tool. Data were analysed thematically, using deductive (i.e. cadre definition, recruitment, education, deployment and retention) and inductive coding (i.e. capacity, gender and insecurity). RESULTS: Twenty-three sources were included, of 2729 identified, discussing community midwifery programmes in six FCAS (i.e. eight for Sudan, six for Afghanistan, three each for Mali and Yemen, two for South Sudan and one for Somalia). Source quality was relatively poor, and cadre definitions were context dependent. Major enablers for effective CMW programmes were community linkages and acceptance, while barriers included inappropriate recruitment, non-standardized education, weak supportive environment, political insecurity and violence. CONCLUSIONS: While community engagement and acceptance were crucial, CMW programmes were weakened by inappropriate recruitment and training, lack of support and general insecurity. Further research and implementation evidence is needed to aid policy-makers, donors and implementing agencies in developing and implementing effective CMW programmes in FCAS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".