A systematic review of EPDS cultural suitability with Indigenous mothers: a global perspective
Bibliographic record
Abstract
The Edinburgh Postnatal Depression Scale (EPDS) is used extensively as the "gold standard" perinatal depression and anxiety screening tool. This study contributes to an emerging discussion about the tool's shortcomings, specifically around cultural suitability for use with Indigenous women. A systematic search was conducted in ProQuest, PsycINFO, MEDLINE (Web of Science), PubMed, Scopus, Informit, and CINAHL research databases, and grey literature. The quality of the body of evidence was assessed using the NHMRC Level of Evidence framework. Three studies supported the cultural validation of the EPDS with Indigenous groups in Canada (n = 2) and the USA (n = 1). The remaining eleven Australian studies demonstrated that cultural concerns were suggested by either Indigenous mothers, healthcare professionals (Indigenous and non-Indigenous), or both, though cultural concerns were more weighted from the perspectives of healthcare professionals. The quality of the evidence was not strong, and thus, there is a critical and urgent need for targeted research in this area. This review identified and recommended Indigenous-specific methodologies that can be adopted for more trustworthy, culturally safe, and effective research in this area. Given that the EPDS is currently considered gold standard in routine perinatal mental health screening practice in countries around the world, these findings raise significant concerns. Using culturally relevant research methodologies, such as the use of mixed-methods design, could lay stronger groundwork for further investigation of the broader utility and cultural relevance of the tool.
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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 | 0.034 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| 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".