Effect of Acupressure on Labor Pain for Women during First Stage of Normal Labor
Bibliographic record
Abstract
Background: Acupressure is thought to promote blood flow and the release of neurotransmitters, thereby maintaining the body's regular functions and offering a sense of well-being. Nevertheless, there is limited scientific evidence to substantiate the beneficial impacts of Acupressure in the realm of obstetric healthcare. Purpose of the study: To assess the impact of applying Acupressure at the LI4 acupoint on the pain experienced by women in the initial stage of labor. Research design: An experimental study with a pretest and posttest control group design. A total of 100 women were randomly assigned to two groups. Each group received LI4 Acupressure or light skin stroking. Setting :It was the obstetric unit of El-Shouhdaa hospital, Menoufia Governorate, in Egypt. Data: collected through an interviewing questionnaire, Visual Analogue Scale and, McGill questionnaire part I (VAS and MPQ Part 1). Methods: labor pain was assessed four times using labor pain scales (VAS and MPQ Part 1) before, immediately after, 30 and 60 minutes after the intervention. Findings: A considerable decrease in labor pain during the active phase of the first stage of labor among the two groups with the more pain reduction with Acupressure. Conclusions: The application of LI4 Acupressure demonstrated effectiveness in alleviating labor pain in the active phase of the initial stage of labor.
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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 | 0.001 |
| 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) | 0.004 | 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".