Challenges and strategies in accessing perinatal care for refugee pregnant women: scoping review
Bibliographic record
Abstract
The perinatal period, spanning from the 22nd week of gestation to seven days after birth, requires comprehensive, continuous, and high-quality care, which is essential for preventing complications and fostering strong bonds between healthcare providers and patients. However, refugee women—a population that, as of 2024, includes over 122 million forcibly displaced individuals—face heightened risks during pregnancy due to structural, cultural, and linguistic barriers, as well as discrimination and unfamiliarity with the healthcare systems of host countries. This study aimed to analyze, through a scoping review, the barriers and facilitators in accessing perinatal care for refugee pregnant women, identifying key challenges, strategies for care provision, and gaps in the scientific literature. The methodology followed the Joanna Briggs Institute (JBI) guidelines, using the PCC mnemonic (Population: refugee women in the perinatal period; Concept: structure and approach of perinatal care; Context: access to care in host countries). Searches were conducted in PubMed, ScienceDirect, BVS, ERIC, and LILACS using standardized descriptors, with no time or geographic restrictions, and included literature in Portuguese, English, and Spanish. Out of 1,107 identified records, after removing duplicates and applying eligibility criteria, 43 studies were included in the review. The results revealed that since 2007, scientific production on the topic has increased, initially highlighting structural and sociocultural challenges in caring for refugee pregnant women, such as dependence on family authorization to access services, language barriers, and lack of care continuity. From 2015 onward, evidence grew regarding late initiation of prenatal care, dissatisfaction with care quality, and higher rates of adverse outcomes, including preterm births, low birth weight, and obstetric complications. Although multidisciplinary and culturally sensitive care models have shown positive impacts on patient satisfaction and adherence, many refugee women still experience insecurity, lack of privacy, prejudice, and insufficient psychosocial support. Most studies employed quantitative methods, particularly cohort designs comparing perinatal outcomes between refugees and local populations, revealing significant disparities. Research was predominantly conducted in high-income countries—such as Australia, Turkey, the Netherlands, Germany, and Canada—reflecting contexts with higher migration flows, while low- and middle-income countries, despite hosting highly vulnerable populations, were underrepresented. The discussion highlighted that challenges in accessing perinatal care include delayed prenatal care initiation, fewer consultations, lack of providers trained in culturally sensitive practices, discrimination, language barriers, and limited awareness of available rights and resources. Additional factors such as frequent relocations, migratory instability, lack of social support, and psychological distress related to past traumas further exacerbate these women's vulnerability, negatively impacting maternal and child outcomes. As improvement strategies, the literature emphasizes the importance of integrated, culturally responsive care models, including qualified interpreters, psychosocial support, health education, community leadership engagement, and specialized multidisciplinary teams. Implementing public policies that recognize the complexity of refugee women’s trajectories and ensure care continuity is critical for equitable, humane, and safe perinatal care. In conclusion, while significant progress has been made in developing policies and guidelines for perinatal care for refugee women, substantial gaps remain in implementing effective and welcoming practices. The literature underscores the need for stronger, sustainable public policies to expand access and ensure equity in perinatal healthcare for refugee populations, particularly in high-vulnerability settings.
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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 | 0.013 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 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".