Recognition and management of perinatal depression and anxiety by general practitioners: a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Perinatal anxiety and depression are widespread, with up to 20% of women affected during pregnancy and after birth. In the UK, management of perinatal mental health falls under the remit of general practitioners (GPs). We reviewed the literature on GPs' routine recognition, diagnosis and management of anxiety and depression in the perinatal period. METHOD: A systematic search of Embase, Medline, PsycInfo, Pubmed, Scopus and Web of Science was conducted. Studies were eligible if they reported quantitative measures of GPs' or Family Physicians' assessment, recognition and management of anxiety or depression in pregnancy or post-partum. RESULTS: Thirteen papers, reporting 10 studies, were identified from the United States, Australia, UK, Netherlands and Canada. All reported on depression; two included anxiety disorders. Reported awareness and ability to diagnose perinatal depression among GPs was high. GPs knew about and used screening tools in the UK but less so in US settings. Antidepressants were the first line of treatment, with various SSRIs considered safest. Counseling by GPs and referrals to specialists were common in the post-natal period, less so in pregnancy. Treatment choices were determined by resources, attitudes, knowledge and training. CONCLUSIONS: Data on GPs' awareness and management of perinatal depression were sparse and unlikely to be generalizable. Future directions for research are proposed; such as exploring the management of anxiety disorders which are largely missing from the literature, and understanding more about barriers to disclosure and recognition in primary care. More standardized training could help to improve recognition and management practices.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it