Exposure to and engagement with digital psychoeducational content and community related to maternal mental health by perinatal persons and mothers: design of an online survey with optional follow-up and participant characteristics
Bibliographic record
Abstract
Abstract Background Leveraging digital platforms may be an effective strategy for connecting perinatal persons and mothers with evidence-based information and support related to maternal mental health and peers. Momwell is a mom-centered model of care that provides psychoeducational content through several digital platforms including social media, podcasts, and blog posts. Objective To describe the design of a study of perinatal persons and mothers who are exposed to or engage with psychoeducation content and community related to maternal mental health on social media or other digital platforms (Momwell), and to describe characteristics of the sample. Methods Adults who engaged with Momwell on any of their digital platforms were recruited to participate in an online survey study in summer/fall 2023. Participants completed either a longer or shorter survey. Two to 3 months after completing this survey, participants who provided permission to be re-contacted were invited to complete a second survey. The surveys included validated psychological measures, study-specific quantitative questions, and open-ended questions that assessed participant demographics, exposure to and engagement with Momwell psychoeducation content and community, maternal mental health, parenting relationships, parenting self-efficacy, and additional psychosocial and health measures. Results Participants (N=584; n=298 longer survey, n=286 shorter survey) were >99% mothers, 46% perinatal (10% pregnant, 36% post-partum), and on average 32.4 (SD: 3.9) years old. Fifty-nine percent were from the United States, 36% from Canada, and 5% from other countries. The vast majority (95%) followed Momwell on Instagram, 44% listened to the Momwell podcast and 41% received their newsletter. Most participants had been exposed to Momwell’s psychoeducation content for at least 6 months across the different platforms (range: 40% TikTok to 87% Instagram). Two to 3 months later, 246 participants completed a second survey (n=149 longer survey, n=97 shorter survey). Conclusions Data from this study will provide insights into how perinatal persons and mothers leverage digital psychoeducational content and peer communities to support their mental health across the perinatal period and into the early years of motherhood. Leveraging digital platforms to disseminate evidence-based digital psychoeducational content related to maternal mental health and connect peers has the potential to change how we care for perinatal persons and mothers.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".