First Nations Peoples’ perceptions, knowledge and beliefs regarding stillbirth prevention and bereavement practices: A mixed methods systematic review
Bibliographic record
Abstract
BACKGROUND: First Nations Peoples endure disproportionate rates of stillbirth compared with non-First Nations Peoples. Previous interventions have aimed at reducing stillbirth in First Nations Peoples and providing better bereavement care without necessarily understanding the perceptions, knowledge and beliefs that could influence the design of the intervention and implementation. AIM: The aim of this review was to understand the perceptions, knowledge and beliefs about stillbirth prevention and bereavement of First Nations Peoples from the US, Canada, Aotearoa/New Zealand, and Australia. METHODS: This review was conducted in accordance with the JBI methodology for a convergent integrated mixed method systematic review. This review was overseen by an advisory board of Aboriginal Elders, researchers, and clinicians. A search of eight databases (PubMed, MEDLINE, PsycInfo, CINAHL, Embase, Emcare, Dissertations and Theses and Indigenous Health InfoNet) and grey literature was conducted. All studies were screened, extracted, and appraised for quality by two reviewers and results were categorised, and narratively summarised. RESULTS: Ten studies were included within this review. Their findings were summarised into four categories: safeguarding baby, traditional practices of birthing and grieving, bereavement photography and post-mortem examination. The results indicate a diversity of perceptions, knowledge and beliefs primarily around smoking cessation and bereavement practices after stillbirth. However, there was a paucity of research available. CONCLUSIONS: Further research is needed to understand the perceptions, knowledge and beliefs about stillbirth among First Nations Peoples. Without research within this area, interventions to prevent stillbirth and support bereaved parents and their communities after stillbirth may face barriers to implementation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".