Enhanced Antenatal Care: Combining one-to-one and group Antenatal Care models to increase childbirth education and address childbirth fear
Bibliographic record
Abstract
BACKGROUND: We designed and implemented a new model of care, Enhanced Antenatal Care (EAC), which offers a combined approach to midwifery-led care with six one-to-one visits and four group sessions. AIM: To assess EAC in terms of women's satisfaction with care, autonomy in decision-making, and its effectiveness in lowering childbirth fear. METHODS: This was a quasi-experimental controlled trial comparing 32 nulliparous women who received EAC (n=32) and usual antenatal care (n=60). We compared women's satisfaction with care and autonomy in decision-making post-intervention using chi-square test. We administered a Fear of Birth Scale pre- and post-intervention and assessed change in fear of birth in each group using the Cohen's d for effect size. To isolate the effect of EAC, we then restricted this analysis to women who did not attend classes alongside maternal care (n=13 in EAC and n=13 in usual care). FINDINGS: Women's satisfaction with care in terms of monitoring their and their baby's health was similar in both groups. Women receiving EAC were more likely than those in usual care to report having received enough information about the postpartum period (75% vs 30%) and parenting (91% vs 55%). Overall, EAC was more effective than usual care in reducing fear of birth (Cohen's d=-0.21), especially among women not attending classes alongside antenatal care (Cohen's d=-0.83). CONCLUSION: This study is the first to report findings on EAC and suggests that this novel model may be beneficial in terms of providing education and support, as well as lowering childbirth fear.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".