Effectiveness of a web-enabled psychoeducational resource for postpartum depression and anxiety among women in British Columbia
Bibliographic record
Abstract
Abstract Purpose Postpartum depression (PPD) and anxiety (PPA) affect nearly one-quarter (23%) of women in Canada. eHealth is a promising solution for increasing access to postpartum mental healthcare. However, a user-centered approach is not routinely taken in the development of web-enabled resources, leaving postpartum women out of critical decision-making processes. This study aimed to evaluate the effectiveness, usability, and user satisfaction of PostpartumCare.ca, a web-enabled psychoeducational resource for PPD and PPA, created in partnership with postpartum women in British Columbia. Methods Participants were randomized to either an intervention group ( n = 52) receiving access to PostpartumCare.ca for four weeks, or to a waitlist control group ( n = 51). Measures evaluating PPD (Edinburgh Postnatal Depression Scale) and PPA symptoms (Perinatal Anxiety Screening Scale) were completed at baseline, after four weeks, and after a two-week follow-up. User ratings of website usability and satisfaction and website metrics were also collected. Results PPD and PPA symptoms were significantly reduced for the intervention group only after four weeks, with improvements maintained after a two-week follow-up, corresponding with small-to-medium effect sizes (PPD: partial η 2 = 0.03; PPA: partial η 2 = 0.04). Intervention participants were also more likely than waitlist controls to recover from clinical levels of PPD symptoms (χ 2 (1, n = 63) = 4.58, p = .032) and PostpartumCare.ca’s usability and satisfaction were rated favourably overall. Conclusion Findings suggest that a web-enabled psychoeducational resource, created in collaboration with patient partners, can effectively reduce PPD and PPA symptoms, supporting its potential use as a low-barrier option for postpartum women. Trial Registration Protocol for this trial was preregistered on NIH U.S. National Library of Medicine, ClinicalTrials.gov as of May 2022 (ID No. NCT05382884).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".