Public Health Nurse–Delivered 1-Day Cognitive Behavioral Therapy–Based Workshops for Treating Postpartum Depression
Bibliographic record
Abstract
This pilot randomized controlled trial (RCT) examined the feasibility of study procedures and acceptability of 1-day cognitive behavioral therapy (CBT)-based workshops for postpartum depression (PPD) delivered by nonspecialist public health nurses (PHNs) and explored the potential effects of the intervention on PPD and anxiety to inform a future, full-scale RCT. Birthing parents ≥18 years old with an infant <12 months old, living in Ontario, Canada, with an Edinburgh Postnatal Depression Scale (EPDS) score ≥10 were recruited between March 18 and May 25, 2022, and randomly assigned to receive the 1-day CBT-based workshop plus treatment as usual (TAU; experimental group) or TAU alone (control group). Feasibility objectives (recruitment, retention, intervention attendance) were described using descriptive statistics, and treatment effects were assessed at enrollment and 3 and 9 months post-intervention. = .14) postworkshop than control participants. Recruiting and retaining participants in an RCT of PHN-delivered 1-day CBT-based workshops is feasible. Pilot results suggest that workshops may lead to improvements in PPD up to 9 months postworkshop. As this pilot study was not powered to detect differences in clinical outcomes, these findings warrant exploration in a full scale RCT. ClinicalTrials.gov identifier: NCT05314361.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.008 | 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".