Perinatal depression screening: a systematic review of recommendations from member countries of the Organisation for Economic Co-operation and Development (OECD)
Bibliographic record
Abstract
Perinatal depression (PND) screening recommendations are made by national, state-based and professional organisations; however, there is disagreement regarding screening timing, provider responsible, screening setting, screening tool as well as the follow-up and referral pathways required post-screening. This systematic review aimed to identify, describe and compare PND screening recommendations from member countries of the Organisation for Economic Co-operation and Development (OECD). Publications were identified through systematically searching PubMed, Google and the Guidelines International Network (GIN). Recommendations regarding PND screening endorsement, timing, frequency, responsible provider, tools/assessments and follow-up and referral were extracted. Twenty-one publications, including guidelines, from five countries were included. Most made recommendations in support of PND screening using the Edinburgh Postnatal Depression Scale. Details differed regarding terminology used, as well as frequency of screening, follow-up mechanisms and referral pathways. A broad range of health providers were considered to be responsible for screening. This is the first review to identify and compare PND screening recommendations from OECD member countries; however, only online publications published in English, from five countries were included. Heterogeneity of publication types and inconsistency in definitions rendered quality assessment inappropriate. While most publications generally endorsed PND screening, there are exceptions and the associated details pertaining to the actual conduct of screening vary between and within countries. Developing clear, standardised recommendations based on current evidence is necessary to ensure clarity amongst healthcare providers and a comprehensive approach for the early detection of PND.
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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 | 0.027 | 0.105 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".