In-person 1-day cognitive behavioral therapy-based workshops for postpartum depression: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Postpartum depression (PPD) affects up to one in five mothers and birthing parents, yet as few as 10% access evidence-based treatment. One-day cognitive behavioral therapy (CBT)-based workshops for PPD have the potential to reach large numbers of sufferers and be integrated into stepped models of care. METHODS: This randomized controlled trial of 461 mothers and birthing parents in Ontario, Canada with Edinburgh Postnatal Depression Scale (EPDS) scores ⩾10, age ⩾18 years, and an infant <12 months of age compared the effects of a 1-day CBT-based workshop plus treatment as usual (TAU; i.e. care from any provider(s) they wished) to TAU alone at 12-weeks post-intervention on PPD, anxiety, the mother-infant relationship, offspring behavior, health-related quality of life, and cost-effectiveness. Data were collected via REDCap. RESULTS: < 0.01) and were associated with three times higher odds of a clinically significant decrease in PPD [odds ratio (OR) 3.00, 95% confidence interval (CI) 1.93-4.67]. Anxiety also decreased and participants had three times the odds of clinically significant improvement (OR 3.20, 95% CI 2.03-5.04). Participants reported improvements in mother-infant bonding, infant-focused rejection and anger, and effortful control in their toddlers. The workshop plus TAU achieved similar quality-adjusted life-years at lower costs than TAU alone. CONCLUSIONS: One-day CBT-based workshops for PPD can lead to improvements in depression, anxiety, and the mother-infant relationship and are cost-saving. This intervention could represent a perinatal-specific option that can treat larger numbers of individuals and be integrated into stepped care approaches at reasonable cost.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".