Peer-Delivered Cognitive-Behavioral Therapy for Postpartum Depression
Bibliographic record
Abstract
Objective: To determine if a 9-week group cognitive-behavioral therapy (CBT) intervention delivered by women who have recovered from postpartum depression (peers) can effectively reduce symptoms of postpartum depression (PPD) and anxiety and improve social support and the mother-infant relationship. Methods: A sample of 73 mothers living in Ontario, Canada, were randomized into experimental and waitlist control groups between March 2018 and February 2020. Participants were ≥ 18 years of age, had an infant < 12 months old, were fluent in English, and scored ≥ 10 on the Edinburgh Postnatal Depression Scale. The experimental group completed the 9-week group CBT intervention immediately after study enrollment, while the control group did so after a 9-week waiting period. All outcomes were assessed at enrollment (n = 54) and 9 weeks later (n = 38). Outcomes were assessed in the experimental group at 6 months to assess treatment stability. Results: Peer-delivered group CBT for PPD led to clinically and statistically significant improvements in symptoms of depression (F1,47 = 22.52, P < .01) and anxiety (F1,45 = 20.56, P < .05) in the experimental group, and these improvements were stable at the 6-month follow-up. Perceptions of impaired mother-infant bonding (t15 = 3.72, P < .01) and rejection and pathological anger (t15 = 3.01, P < .01) also decreased at the 6-month follow-up in the experimental group. Conclusions: Peer-delivered group CBT for PPD effectively treats symptoms of PPD and anxiety and may lead to improvements in the mother-infant relationship. This intervention is an effective and potentially scalable means by which access to a treatment that meets the needs and wants of mothers with PPD can be increased. Trial Registration: ClinicalTrials.gov Identifier: NCT03285139
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".