The Effect of Perinatal Education on Iranian Mothers ’ Stress and Labor
Bibliographic record
Abstract
Lack of sufficient knowledge about the unknowns of pregnancy increases stress and requires more medical interventions. This study was conducted to assess the effects of prenatal education on mothers ’ stress and labor. This clinical trial was conducted to study 195 women (132 in the control group and 63 in the experimental group) who had attended healthcare centers in the city of Amol after their 16th gestational week. The experimental group participated in educational classes to learn how to experience a safe childbirth for 6-8 sessions of 1.5 hours almost every three weeks. The control group received only a routine care, pain assessment scales like Visual Analogue Scale (VAS) and McGill questionnaire, and Hospital Anxiety and Depression Scale (HADS) were employed to collect data. The data were analyzed using SPSS software through t-test and Chi Square test to compare the groups. The results of the t-test showed a meaningful difference in levels of stress felt by the experimental group compared to control group (p=0.002). The Visual Analogue Scale suggested that in the transitional stages (8-10 cm cervical dilation), the level of pain felt by the experimental group was meaningfully lower than that felt by the control group (p=0.03). However, this was not significantly different between the two groups at 3-4 cm cervical dilation and the second stage of childbirth. The McGill scale’s results for measuring
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".