Postpartum depression: we know the risks, can it be prevented?
Bibliographic record
Abstract
In the past 20 years, there has been increasing recognition that for some women, pregnancy may be burdened with mood problems, in particular depression, that may impact both mother and child. With identification of risk factors for postpartum depression and a growing knowledge about a biologic vulnerability for mood change following delivery, research has accumulated on attempts to prevent postpartum depression using various psychosocial, psychopharmacologic, and hormonal strategies. The majority of psychosocial and hormonal strategies have shown little effect on postpartum depression. Notwithstanding, results from preliminary trials of interpersonal therapy, cognitive-behavioural therapy, and antidepressants indicate that these strategies may be of benefit. Information on prevention of postpartum depression using dietary supplements is sparse and the available evidence is inconclusive. Although a few studies show promising results, more rigorous trials are required. The abounding negative evidence in the literature indicates that postpartum depression cannot be easily prevented, yet.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".