Experiences of nurses caring for maternal immigrant and refugee women: a qualitative systematic review protocol
Bibliographic record
Abstract
OBJECTIVE: This review will focus on studies inquiring into nurses working across diverse health care settings and their experiences of caring for immigrant and refugee women who are pregnant or mothering. Within this review, diverse terminologies used to conceptualize "nurse," immigrant," and "refugee" will also be captured. INTRODUCTION: Immigrant and refugee women who are pregnant or mothering experience poorer health than non-displaced women. Nurses are pivotal in providing care to this population. Understanding nursing experiences can reveal structural barriers and facilitators to equitable care provision. INCLUSION CRITERIA: Peer-reviewed, qualitative studies that include nurses working across diverse health care settings and providing care to involuntary immigrant and refugee maternal women will be considered. Studies where nurses are described as being educated within a basic and generalized nursing program and have been authorized by a regulatory organization to practice nursing in their country will be included. METHODS: Key information sources searched include CINAHL, PsycINFO, MEDLINE, Google Scholar, Web of Science, and PubMed. Search terms will be adapted for each information source. Study selection includes screening titles and abstracts by two independent reviewers against the inclusion criteria. These reviewers will then critically appraise for methodological quality and begin data extraction to understand experiences of nurses and diverse understandings of "nurse," "immigrant," and "refugee." Synthesis includes assembling and categorizing findings on the basis of meaning similarity. A set of statements will be generated representing this synthesis. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42019137922.
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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 | 0.121 | 0.081 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.040 | 0.006 |
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".