Identifying women at risk for postpartum anxiety: a prospective population‐based study
Bibliographic record
Abstract
OBJECTIVE: To develop a multifactorial model to predict anxiety symptomatology at 8 weeks postpartum. METHOD: In a population-based study, 522 women in a health region near Vancouver, Canada, completed questionnaires at 1, 4, and 8 weeks postpartum. Questionnaires included risk factors measured at 1 week (sociodemographic, biological, pregnancy-related, life stressors, social support, obstetric, and maternal adjustment). Sequential logistic regression was completed to develop a predictive model of anxiety symptomatology at 8 weeks (State-Trait Anxiety Inventory score >40). RESULTS: The prevalence of anxiety symptomatology at 1, 4, and 8 weeks postpartum was 22.6%, 17.2%, and 14.8% respectively. In multivariable models, anxiety symptomatology at 1 week (aOR 2.78, 95% CI: 1.04-7.43), multiparous parity (aOR 3.29, 95% CI: 1.28-8.48), history of psychiatric problems (aOR 3.07, 95% CI: 1.19-7.97), perceived stress (1 SD increase: aOR 4.92, 95% CI: 2.62-9.26), and childcare stress (1 SD increase: aOR 1.63, 95% CI: 1.01-2.64) were independent predictors of anxiety symptomatology at 8 weeks. CONCLUSION: While a significant proportion of women experience anxiety symptomatology following childbirth, multiparous women with a psychiatric history who have high levels of diverse stress are at greatest risk. These key factors may be used to promote early identification and secondary preventive interventions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".