The clinical utility of maternal self‐reported personal and familial psychiatric history in identifying women at risk for postpartum depression
Bibliographic record
Abstract
BACKGROUND: To determine whether maternal self-reported data on personal and family psychiatric history would significantly predict postpartum depressive symptomatology at 8 weeks postpartum and to examine which of these variables were the most predictive for inclusion in an obstetrical clinical assessment aimed at early identification of postpartum depression. METHODS: As part of a longitudinal study, a population-based sample of 622 women completed mailed questionnaires at 1 and 8 weeks postpartum. RESULTS: At 8 weeks postpartum, mothers who indicated that they had any personal psychiatric history were almost four times more likely to exhibit depressive symptomatology (Edinburgh Postnatal Depression Scale score > 9) than those with no previous mental health difficulties (odds ratio [OR] 3.65, 95% CI 2.30-5.82). Any family psychiatric history was not a significant risk factor. Variables most predictive of depressive symptomatology at 8 weeks, explaining 42% of the variance, included: maternal antenatal depression (OR 3.77, p=0.03), maternal history of postpartum depression (OR 2.21, p=0.02), and Edinburgh Postnatal Depression Scale score >9 at 1 week postpartum (OR 18.23, p<0.001). CONCLUSIONS: The results suggest that maternal variables, particularly those related to the index and past pregnancies, not family psychiatric history, are the best predictors of postpartum depressive symptoms. These findings highlight the importance of assessing symptoms of depression and anxiety during pregnancy and the early postpartum period, in order to facilitate timely identification of women at risk for developing postpartum depression.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".