Patterns of Depression and Treatment in Pregnant and Postpartum Women
Bibliographic record
Abstract
OBJECTIVE: To determine the course of depression and the effects of treatment during pregnancy and into the postpartum period. METHOD: This is a longitudinal study of a community sample of 649 pregnant women who were assessed in early pregnancy (17.4 ± 4.9 weeks), late pregnancy (30.6 ± 2.7 weeks), and postpartum (4.2 ± 2.1 weeks) with the Edinburgh Postnatal Depression Scale (EPDS). Women who scored 12 or more on the EPDS were encouraged to seek assessment and treatment. We used generalized estimating equation modelling to determine the predicted mean depression scores, taking age, ethnicity, history of depression, and previous and present treatment status into account. RESULTS: The unadjusted prevalence of depression (EPDS ≥ 12) was 14.1% (n = 91) in early pregnancy, 10.4% (n = 62) in late pregnancy, and 8.1% (n = 48) postpartum. Twelve per cent of women were engaged in treatment. The predicted mean EPDS score decreased over the course of the pregnancy into the postpartum period, most significantly when women were engaged in counselling or taking psychotropic medication. Counselling was the more common method of treatment during pregnancy and medication in the postpartum period. Women who were depressed and untreated were more likely to be younger, more stressed, have less support, have a history of depression, and use alcohol. CONCLUSIONS: We confirm that depressive symptoms improve over the course of the pregnancy into the postpartum period, particularly for women who receive treatment. Our study is unique as it takes the history of depression, present and past treatment status, and the longitudinal nature of the data into account.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".