Indigenous maternal and infant outcomes and women's experiences of midwifery care: A mixed‐methods systematic review
Bibliographic record
Abstract
BACKGROUND: The impact of midwifery, and especially Indigenous midwifery, care for Indigenous women and communities has not been comprehensively reviewed. To address this knowledge gap, we conducted a mixed-methods systematic review to understand Indigenous maternal and infant outcomes and women's' experiences with midwifery care. METHODS: We searched nine databases to identify primary studies reporting on midwifery and Indigenous maternal and infant birth outcomes and experiences, published in English since 2000. We synthesized quantitative and qualitative outcome data using a convergent segregated mixed-methods approach and used a mixed-methods appraisal tool (MMAT) to assess the methodological quality of included studies. The Aboriginal and Torres Strait Islander Quality Appraisal Tool (ATSI QAT) was used to appraise the inclusion of Indigenous perspectives in the evidence. RESULTS: Out of 3044 records, we included 35 individual studies with 55% (19 studies) reporting on maternal and infant health outcomes. Comparative studies (n = 13) showed no significant differences in mortality rates but identified reduced preterm births, earlier prenatal care, and an increased number of prenatal visits for Indigenous women receiving midwifery care. Quality of care studies indicated a preference for midwifery care among Indigenous women. Sixteen qualitative studies highlighted three key findings - culturally safe care, holistic care, and improved access to care. The majority of studies were of high methodological quality (91% met ≥80% criteria), while only 14% of studies were considered to have appropriately included Indigenous perspectives. CONCLUSION: This review demonstrates the value of midwifery care for Indigenous women, providing evidence to support policy recommendations promoting midwifery care as a physically and culturally safe model for Indigenous women and families.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.034 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".