Preventing Postpartum Depression Part I: A Review of Biological Interventions
Bibliographic record
Abstract
OBJECTIVE: This paper critically reviews the literature to determine the current state of scientific knowledge concerning the prevention of postpartum depression (PPD) from a biological perspective. METHODS: The criteria used to evaluate the interventions were derived from the standardized methodology developed by the Canadian Task Force on Preventive Health Care. Databases searched for this review include Medline, PubMed, Cinahl, PsycINFO, Embase, ProQuest, the Cochrane Library, and the World Health Organization Reproductive Health Library. Studies selected were peer-reviewed English-language articles published between January 1, 1966, and December 31, 2003. RESULTS: Seven studies that met criteria were examined. These studies focused on evaluating the preventive effect of antidepressant medication, estrogen and progesterone therapy, thyroid therapy, docosahexanoic acid, and calcium supplementation. Although some of these interventions have been examined rigorously for depression unrelated to childbirth, methodological study limitations render intervention efficacy equivocal for PPD; thus, there is limited strong evidence to guide practice or policy recommendations. CONCLUSIONS: Despite the recent upsurge of interest in this area, many questions remain unanswered, which has several implications for research.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".