EXAMINING CHANGES IN MATERNAL MENTAL HEALTH AND INFANT BEHAVIOUR AFTER PEER-DELIVERED TREATMENT FOR POSTPARTUM DEPRESSION
Bibliographic record
Abstract
Background: Postpartum depression (PPD) affects up to 20% of mothers and birthing parents, yet only 1 in 10 receive evidence-based treatment. Left untreated, PPD increases the risk of future depressive episodes, familial disharmony, and offspring problems. This study sought to determine if an online 9-week group cognitive-behavioural therapy (CBT) intervention delivered by mothers who have recovered from postpartum depression (i.e., peers) can effectively improve PPD, anxiety, social support, the mother-infant relationship, and infant temperament in those with PPD. Methodology: During the COVID-19 pandemic, 183 participants were randomized into experimental (received intervention at baseline plus treatment as usual (TAU)) and waitlist control (TAU plus the intervention after a 9-week wait) groups. 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. Depression, anxiety, social support, mother-infant bonding, and infant behaviour were reported by all mothers at enrollment and 9-weeks later, and three months after that in the experimental group. Results: Participants in the experimental group experienced clinically and statistically significant improvements in PPD and anxiety post-treatment and three months later. Perceptions of social support, infant-focused anxiety, and negative emotionality in infants also improved immediately post-intervention and remained stable three months later in the experimental group. Conclusion: Online peer-delivered group CBT for PPD can effectively treat PPD and anxiety, as well as improve social support, the mother-infant relationship, and infant temperament. Online Peer-Delivered Group CBT for PPD is a novel approach to service delivery that can increase treatment uptake, providing mothers experiencing PPD with access to a credible and engaging source of help, and has the potential to revolutionize the treatment of PPD in Canada and around the world.
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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 | 0.001 | 0.003 |
| 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) | 0.002 | 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".