Barriers to Rural Midwifery: An Integrative Review
Bibliographic record
Abstract
AIM: To explore the types of barriers that midwives face when practicing or attempting to practice in rural and remote locations. DESIGN: An integrative review using the Ecological Systems Theory. METHODS: The review was guided by Whitmore and Knafl. Included studies were appraised using the Mixed Methods Appraisal tool. DATA SOURCES: In January 2024, searches were undertaken in CINHAL, MEDLINE, Science Direct, and Google Scholar. RESULTS: A total of 470 articles were screened after searches. Fourteen articles published between 1990 and 2023 met all inclusion criteria. They were thematically analysed to explore barriers present at the micro-, macro-, and meso-levels. The mico-level barriers included isolation, financial insecurity due to low volume, and challenges in separating personal and professional life. Barriers at the meso level included discord in interprofessional relationships and challenges in attending continuing education. Lack of midwifery representation, overt medical dominance, and policy acted as barriers at the macro level. CONCLUSION: Rural midwives face complex challenges that demand multi-faceted and multi-level solutions. The findings highlight the need for an increase in midwifery representation in healthcare planning, improved policies related to midwifery, and the adoption of a rural model of healthcare planning that accounts for the unique social realities of living and practicing in rural communities. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: By illuminating the challenges faced by rural midwives, efforts can be directed toward sustainable solutions to support rural midwifery practices and decrease rural health disparities. IMPACT: Increasing midwifery access in rural communities can help reduce maternity care disparities for rural families. By identifying and addressing the barriers experienced by rural midwives, it can strengthen advocacy for targeted policies and support systems that empower midwives. REPORTING METHOD: This review is reported according to the PRISMA guidelines for scoping reviews. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.
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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 | 0.010 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".