Mental health indicators among pregnant Aboriginal women in Canada: results from the Maternity Experiences Survey
Bibliographic record
Abstract
INTRODUCTION: There is little research done on mental health among pregnant Aboriginal women. Therefore, the purpose of the study was to examine the prevalence of postpartum depression (PPD) and its determinants, including pre-existing depression among non-Aboriginal and Aboriginal women in Canada. METHODS: The Maternity Experiences Survey (MES) is a national survey of Canadian women's experiences and practices before conception, up to the early months of parenthood. Predictors of PPD were calculated using the Mantel-Haenszel correction method relative to the risk estimates based on the odds ratio from adjusted regression analysis. The analysis was conducted among women who self-identified as Aboriginal (Inuit, Métis or First Nations living off-reserve) and those who identified as non-Aboriginal. RESULTS: The prevalence of pre-existing depression was higher among self-reported First Nations off-reserve and Métis women than non-Aboriginal women. Inuit women had the lowest prevalence of self-reported pre-existing depression, and Aboriginal women reported a higher prevalence of PPD than non-Aboriginal women. Pre-existing depression was not a predictor for PPD for Inuit or Métis women in this study but was a positive predictor among First Nations off-reserve and non-Aboriginal women. A disproportionally higher number of Aboriginal women reported experiencing abuse, as compared to non-Aboriginal women. CONCLUSION: Our study demonstrated that common predictors of PPD including anxiety, experiencing stressful life events during pregnancy, having low levels of social support, and a previous history of depression were consistent among non-Aboriginal women. However, with the exception of the number of stressful events among First Nations offreserve, these were not associated with PPD among Aboriginal women. This information can be used to further increase awareness of mental health indicators among Aboriginal women.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".