One-Day Peer-Delivered Cognitive Behavioral Therapy-Based Workshops for Postpartum Depression: A Randomized Controlled Trial
Bibliographic record
Abstract
INTRODUCTION: Myriad treatment barriers prevent birthing parents with postpartum depression (PPD) from receiving timely treatment. We aimed to determine whether a peer-delivered online 1-day cognitive behavioral therapy (CBT)-based workshop added to treatment as usual (TAU) improves PPD and its comorbidities and is more cost-effective than TAU alone. METHODS: This parallel-group, randomized controlled trial took place in Ontario, Canada (June 7, 2021, to February 18, 2022). Participants were ≥18 years old, had an infant ≤12 months old, and an Edinburgh Postnatal Depression Scale (EPDS) score ≥10. Participants were allocated to receive the workshop plus TAU (n = 202) or TAU and waitlisted to complete the workshop 12 weeks later (n = 203). The primary outcome was change in PPD (EPDS score) from enrollment to 12 weeks later. The secondary outcome was cost-effectiveness and tertiary outcomes included anxiety, social support, partner relationship quality, the mother-infant relationship, parenting stress, and infant temperament. RESULTS: Participants had a mean age of 32.3 years (SD = 4.30) and 65% were White. The workshop led to a significant reduction in EPDS scores (15.95-11.37; d = 0.92, p < 0. 01) and was associated with higher odds of exhibiting a clinically significant decrease in EPDS scores (OR = 2.03; 95% CI: 1.26-3.29). The workshop plus TAU was more cost-effective than TAU alone. It also led to improvements in postpartum anxiety, infant-focused anxiety, parenting stress, and infant temperament. CONCLUSIONS: Peer-delivered 1-day CBT-based workshops can improve PPD and are a potentially scalable low-intensity treatment that could help increase treatment access.
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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 | 0.005 |
| 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 | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".