Social Media-based Parenting Program for Women With Postpartum Depressive Symptoms: An RCT
Bibliographic record
Abstract
OBJECTIVES: To test effects of a social media-based parenting program for mothers with postpartum depressive symptoms. METHODS: We conducted a randomized controlled trial from December 2019 to August 2021 of a parenting program using Facebook. Women with mild-to-moderate depressive symptoms (Edinburgh Postnatal Depression Scale [EPDS] 10-19) were randomized to the program, plus online depression treatment or depression treatment alone for 3 months. Women completed the EPDS monthly and the Parent-Child Early Relational Assessment, Parenting Stress Index-Short Form, and Parenting Sense of Competence pre- and postintervention. Differences among groups were assessed using intention-to-treat analysis. RESULTS: Seventy-five women enrolled and 66 (88%) completed the study. Participants were predominantly Black (69%), single (57%), with incomes <$55 000 (68%). The parenting group reported a more rapid decline in depressive symptoms than the comparison group (adjusted EPDS difference, -2.9; 95% confidence interval, -4.8 to -1.0 at 1 month). There were no significant group X time interactions for the Parent-Child Early Relational Assessment, Parenting Stress Index-Short Form, or Parenting Sense of Competence scores. Forty-one percent of women sought mental health treatment for worsening symptoms or suicidality. Women in the parenting group who exhibited greater engagement or reported mental health treatment had greater parenting responsiveness. CONCLUSIONS: A social media-based parenting program led to more rapid declines in depressive symptoms but no differences in responsive parenting, parenting stress, or parenting competence relative to a comparison group. Social media can provide parenting support for women with postpartum depressive symptoms, but greater attention to engagement and treatment access are needed to improve parenting outcomes.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".