Effectiveness of the “Essential Coaching for Every Mother” postpartum text message program on maternal psychosocial outcomes: A randomized controlled trial
Bibliographic record
Abstract
Objective To determine the effectiveness of the Essential Coaching for Every Mother program on maternal self-efficacy, perceived social support, postpartum anxiety, and postpartum depression at six-weeks postpartum. Methods Participants from Nova Scotia were randomized, stratified by parity, to receive either the Essential Coaching for Every Mother postpartum text-message program or usual care, from birth to six-weeks postpartum. Participants completed surveys at enrollment (after birth) and at 6 weeks. Differences between groups were analyzed using analysis of covariance, considering parity and group allocation. Results Of the 171 participants recruited (53% primiparous), 150 completed the baseline survey (intervention n = 78, control n = 72). At baseline, newborns were on average 4.4 days old (SD: 3.9) and mothers 31.4 years old (SD: 4.5). Controlling for maternal age, primiparous women in the intervention group had a greater increase in maternal self-efficacy than primiparous women in the control group (mean difference [MD] = 4.84 (standard error [SE] = 0.75) vs. MD = 2.13 (SE = 0.81), p = 0.034). Women allocated to the intervention group had a greater reduction in postpartum anxiety symptoms than women in the control group for both multiparous and primiparous women (MD = −3.91 (SE = 1.82) vs. 2.81 (SE = 1.86), p = 0.011). There was no significant change in postpartum depression scores or perceived social support for either group. Discussion This study presents the results of the first Canadian postpartum text message program, which found improved psychosocial outcomes for postpartum women. Given the potential to reach numerous women at a low cost across geographical locations, the scalability of this intervention can improve maternal self-efficacy and reduce postpartum anxiety.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.002 |
| 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".