Mood and anxiety problems in perinatal Indigenous women in Australia, New Zealand, Canada, and the United States: A critical review of the literature
Bibliographic record
Abstract
We conducted a review of research literature related to anxiety, depression, and mood problems in Indigenous women in Canada, the United States (including Hawaii), Australia, and New Zealand. Quantitative and qualitative research studies published between 1980 and March 2010 were reviewed. The initial search revealed 396 potential documents, and after being checked for relevance by two researchers, data were extracted from 16 quantitative studies, one qualitative research article, and one dissertation. Depression is a common problem in Indigenous pregnant and postpartum women; however, the prevalence and correlates of anxiety and mood disorders are understudied. The review identified four key areas where further research is needed: (a) longitudinal, population-based studies; (b) further validation and modification of appropriate screening tools; (c) exploration of cultural diversity and meaning of the lived experiences of antenatal and postpartum depression, anxiety, and mood disorders; and (d) development of evidence-informed practices for researchers and practitioners through collaborations with Aboriginal communities to better understand and improve mental health of women of childbearing age.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".