FC11-04 - Patterns of depression and trajectories of treatment over the perinatal period
Bibliographic record
Abstract
Introduction Perinatal depression is an important problem with potentially deleterious health outcomes; however, we know little about the trajectories of depression and treatment. Purpose We report the patterns of maternal depression and trajectories of treatment response in early and late pregnancy and during postpartum in 649 women recruited from the general population of pregnant women in Western Canada. Women who scored ≥ 12 on the Edinburgh Postnatal Depression Scale were classified as depressed. Findings Fifty-two percent of participants were primiparas, 90% were partnered, 83.3% Caucasian, 67% earn more than $40,000 per year, 90% completed high school, and 77% had planned pregnancy. The unadjusted prevalence of depression in early pregnancy (17 weeks) was 14%, late pregnancy (30 weeks) 11.5%, and postpartum (4.1 weeks) was 9.8%. All of the psychosocial factors measured - history of depression, mood instability, lack of social support, relationship problems, worry, and stressors heighten depression symptoms throughout parturition. Our practice of referring women who screened positive for depression changed prevalence rates of women who were depressed and in treatment. The number of women in treatment increased from 12.2% in early pregnancy to 24.8% at postpartum. Women were significantly more likely to get symptom relief counselling in pregnancy compared to psychotropic medication use in postpartum, with the exception of those women with history of depression and treatment engagement. Summary Increased understanding of the patterns and nature of maternal depression and treatment response is essential to early identification of women who are depressed and lead to treatment that is more effective.
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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 | 0.001 | 0.002 |
| 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) | 0.005 | 0.001 |
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".