Fifty years of evidence on perinatal experience among refugee and asylum-seeking women in Organization for Economic Co-operation and Development (OECD) countries: A scoping review
Bibliographic record
Abstract
BACKGROUND: Members of the Organization for Economic Co-operation and Development (OECD) play a significant role in hosting and supporting refugees. Refugees and asylum seekers in OECD countries may face unique challenges in accessing perinatal healthcare. These challenges can impact their use of and experience with perinatal health services leading to poor maternal and infant outcomes. This scoping review describes the general trends in perinatal health research among refugees/asylum seekers in OECD countries over the past fifty years (1970 to 2021) as well as summarizes their perinatal experience. METHODS: Databases including Embase and Medline were searched using relevant key words for "refugee/ asylum seeker", "perinatal ", and " OECD countries.". Articles were excluded if they only involved economic migrants or internally displaced persons, conducted in non-OECD countries, only assessed health behaviors and practices during pregnancy (e.g., smoking), or were published in a language other than English. The final list of articles included 82 unique studies. RESULTS: In the 40 years between 1970 and 2009, very few studies (n = 9) examined perinatal health among refugees/ asylum seekers in OECD countries. However, an increasing trend was observed over the past decade. Early studies (1980 to 2009) focused more on traditional perinatal outcomes; however, from 2010 onwards, studies related to perinatal experience were more likely to emerge in the global health literature. Access to timely prenatal care remains a challenge with failure to address the root causes of the problem in several OECD countries including those with a long history of hosting refugees. The limited availability of interpretation services and the lack of a patient-centered approach to care have also interfered with the perceived quality of care. In addition, perceived isolation and the limited social support experienced by this vulnerable population have negatively impacted their perinatal experiences in several OECD countries. CONCLUSION: Refugee/asylum seekers in OECD countries face a number of challenges during the perinatal period. Policy changes and further research are needed to address access barriers and identify specific interventions that can improve their well-being during this critical period.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".