Online peer‐delivered group cognitive‐behavioral therapy 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 just 10% receive evidence-based care. This randomized controlled trial aimed to determine if a synchronous online 9-week group cognitive-behavioral therapy (CBT) intervention delivered by mothers who have recovered from postpartum depression (i.e., peers) could effectively improve PPD and its comorbidities. METHODS: Participants (n = 183) in this study lived in Ontario, Canada, were ≥18 years-old, had an infant <12 months, were fluent in English, and scored ≥10 on the Edinburgh Postnatal Depression Scale (EPDS). They were randomized to experimental (received intervention plus treatment as usual (TAU)) or waitlist control (TAU plus the intervention after a 9-week wait) groups. Depression, anxiety, social support, mother-infant bonding, and infant temperament were assessed at baseline and 9 weeks later. Outcomes were assessed in the experimental group 3 months post-intervention to assess stability. RESULTS: Statistically significant reductions were observed in EPDS (B = 5.99; p < 0.001; d = 1.32) and Generalized Anxiety Disorder Questionnaire-7 scores (B = 5.94; p < 0.001; d = 1.22), improvements that remained stable 3 months post-intervention in the experimental group. Maternal social support (p = 0.02; d = 0.40), infant-focused anxiety (p = 0.02; d = 0.54), and infant negative emotionality (p < 0.01; d = 0.23) also improved post-intervention and remained stable 3 months later. CONCLUSION: Online peer-delivered group CBT for PPD can effectively treat PPD and anxiety, and improve social support, infant-focused anxiety, and negative emotionality in infants. This intervention could provide the means to increase access to treatment for those experiencing PPD and improve outcomes for mothers, birthing parents, and families.
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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) | 0.003 | 0.002 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".