An exploratory study of the effect of labor pain management on postpartum depression among Chinese women
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to investigate the effects of pain relief during labor on the occurrence of potential postpartum depression in early postpartum among Chinese women. MATERIAL AND METHODS: A quasi-experimental study used, with a convenience sample of 565 women who delivered at the Women's Hospital, School of Medicine. Three types of pain relief were administered based on the women's preference (doula, n = 301; transcutaneous electrical nerve stimulation, n = 51; epidural analgesia, n = 213). Pain scores of participants were assessed using a 10-point visual analog scale during labor. The Edinburgh Postnatal Depression Scale was administered in person and by phone at three days and two to four weeks after delivery, respectively. All data were analyzed using SPSS 20.0. RESULTS: Visual analog scale pain scores in the epidural analgesia group decreased significantly during labor compared to those of the other two groups. The occurrence of potential postpartum depression at three days was 6.6% in the epidural analgesia group, 1.3% in the doula group, and 2% in the transcutaneous electrical nerve stimulation group (P = 0.04). Furthermore, potential postpartum depression occurred at two to four weeks after childbirth in 16% (34/213) of the participants in the epidural analgesia group, 7.3% (22/301) of those who received doula support, and in 7.8% (4/51) of those in the transcutaneous electrical nerve stimulation group (P = 0.006). CONCLUSIONS: The results indicated that epidural analgesia was an effective pain relief method during labor. However, it did not reduce the occurrence of potential postpartum depression and was associated with higher postnatal depression scores.
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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 | 0.001 | 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 | 0.001 | 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".