First Nations populations’ perceptions, knowledge, attitudes, beliefs, and myths about prevention and bereavement in stillbirth: a mixed methods systematic review protocol
Bibliographic record
Abstract
OBJECTIVE: The objective of this review is to investigate First Nations populations' perceptions, knowledge, attitudes, beliefs, and myths about stillbirth. INTRODUCTION: First Nations populations experience disproportionate rates of stillbirth compared with non-First Nations populations. There has been a surge of interventions aimed at reducing stillbirth and providing better bereavement care, but these are not necessarily appropriate for First Nations populations. As a first step toward developing appropriate interventions for these populations, this review will examine current perceptions, knowledge, attitudes, beliefs, and myths about stillbirth held by First Nations people from the United States, Canada, Aotearoa/New Zealand, and Australia. INCLUSION CRITERIA: The review will consider studies that include individuals of any age (bereaved or non-bereaved) who identify as belonging to First Nations populations. Eligible studies will include the perceptions, knowledge, attitudes, beliefs, and myths about stillbirth among First Nations populations. METHODS: This review will follow the JBI methodology for convergent mixed methods systematic reviews. The review is supported by an advisory panel of Aboriginal elders, lived-experience stillbirth researchers, Aboriginal researchers, and clinicians. PubMed, MEDLINE (Ovid), CINAHL (EBSCOhost), Embase (Ovid), Emcare (Ovid), PsycINFO (EBSCOhost), Indigenous Health InfoNet, Trove, Informit, and ProQuest Dissertations and Theses will be searched for relevant information. Titles and abstracts of potential studies will be screened and examined for eligibility. After critical appraisal, quantitative and qualitative data will be extracted from included studies, with the former "qualitized" and the data undergoing a convergent integrated approach. REVIEW REGISTRATION: PROSPERO CRD42023379627.
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 | 0.104 | 0.119 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.017 | 0.016 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.005 |
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".