Antenatal Depression: Prevalence and Determinants in a High-Risk Sample of Women in Saskatoon
Bibliographic record
Abstract
Pregnancy is often portrayed as a happy time for the woman and her family.In reality, many women struggle with negative emotions and moods that can have deleterious effects on the mother, the fetus, and the growing family.Depression is an increasing, worldwide problem, with women in their childbearing years and those of low socioeconomic status the most vulnerable.This study explores depression, as determined by the Edinburgh Postnatal Depression Scale (EPDS), in a high-risk sample of pregnant women enrolled in two prenatal programs in Saskatoon, Saskatchewan, Canada.A prevention and population health approach has been used to identify potential determinants and implications of antenatal depression.The data analyzed in this study were from the first cross-sectional portion of a longitudinal, epidemiological study of depression in pregnancy into the postpartum.Women were invited to participate in the study at their first prenatal visit.Data were collected by program staff.The prevalence of depression in this sample of 402 high-risk women was 29.5%, which is similar to other studies of inner-city, low income, and minority women elsewhere in the world.In the final model, antenatal depression was associated with a history of depression, moods going up and down, current smoking status, high levels of stressors, and social support.Factor analysis of the EPDS revealed three underlying factors: Anxiety, Depression, and Self-harm thoughts.The anxiety factor explained most of the variance in the overall EPDS scores in this sample of women.A history of problems with mood fluctuations was significantly associated with anxiety and depression subscales and selfharm.Significantly more women aged 21 and under experienced anxiety, and more Aboriginal women experienced depressive symptoms and self-harm thoughts.Twenty percent of women reported self-harm thoughts in the preceding seven days.Depressed, Aboriginal, and single women, and women who use alcohol were most at risk for selfharm thoughts.The level of depressive symptoms in this sample of women represents a significant public and mental health problem in women already challenged by inequities in their life circumstances.We need to develop public health policy that will support iii screening and identification of women with depression.Interventions at the primary, secondary, and tertiary levels of prevention can help to improve the health of women struggling with antenatal depression, promote the optimal intrauterine environment for their unborn children, and reduce the intergenerational transmission of depression.iv
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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 | 0.001 |
| 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".