Midwives’ adaptation of their practice, role, and scope to ensure access to sexual and reproductive services during humanitarian crises: A scoping review
Bibliographic record
Abstract
PROBLEM: Limited research has examined and synthesized the adaptation of midwives and midwife-led interventions during crises. BACKGROUND: Evidence suggests that midwives are essential to respond to sexual and reproductive health care needs during disruptive times, and that they adapt to continue to provide their services during those circumstances. AIM: To map the adaptations of midwives when providing care during crises globally. Secondary objectives include identifying which midwives adapted, what services were adapted and how, and the demographic receiving care. STUDY METHODS: Scoping review using Levac's modifications of Arksey and O'Malley's methods. Publications and grey literature, in English and Spanish, with no limitations based on study design or date were included. Data was extracted and mapped using Wheaton and Maciver's Adaptation framework. FINDINGS: We identified 3329 records, of which forty-two were included. Midwives' prior training impacted adaptation. Midwives adapted to the COVID-19 pandemic, epidemics, natural disasters, and World War II. They adapted in hospital and community settings around the provision of antenatal, labor and birth, postpartum, and contraceptive care. However, no specific data identified population demographics. Midwifery adaptations related to their practice, role, and scope of practice. CONCLUSION: The limited available evidence identified the challenges, creativity, and mutual aid activities midwives have undertaken to ensure the provision of their services. Evidence is highly concentrated around maternal health services. Further high-quality research is needed to provide a deeper understanding of how midwifery-led care can adapt to guide sustainable responses to ensure access to sexual and reproductive health services during crises.
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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 | 0.030 | 0.126 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".