A critical interpretive synthesis of the roles of midwives in health systems
Bibliographic record
Abstract
BACKGROUND: Midwives' roles in sexual and reproductive health and rights continues to evolve. Understanding the profession's role and how midwives can be integrated into health systems is essential in creating evidence-informed policies. Our objective was to develop a theoretical framework of how political system factors and health systems arrangements influence the roles of midwives within the health system. METHODS: A critical interpretive synthesis was used to develop the theoretical framework. A range of electronic bibliographic databases (CINAHL, EMBASE, Global Health database, HealthSTAR, Health Systems Evidence, MEDLINE and Web of Science) was searched through to 14 May 2020 as were policy and health systems-related and midwifery organisation websites. A coding structure was created to guide the data extraction. RESULTS: A total of 4533 unique documents were retrieved through electronic searches, of which 4132 were excluded using explicit criteria, leaving 401 potentially relevant records, in addition to the 29 records that were purposively sampled through grey literature. A total of 100 documents were included in the critical interpretive synthesis. The resulting theoretical framework identified the range of political and health system components that can work together to facilitate the integration of midwifery into health systems or act as barriers that restrict the roles of the profession. CONCLUSIONS: Any changes to the roles of midwives in health systems need to take into account the political system where decisions about their integration will be made as well as the nature of the health system in which they are being integrated. The theoretical framework, which can be thought of as a heuristic, identifies the core contextual factors that governments can use to best leverage their position when working to improve sexual and reproductive health and rights.
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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 | 0.157 | 0.256 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.034 | 0.026 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".