The effects of acupressure on severity of primary dysmenorrhea
Bibliographic record
Abstract
BACKGROUND: Dysmenorrhea constitutes one of the most frequent disorders in women of a fertile age. The objective of this research was to determine the effects of acupressure at Sanyinjiao (SP6) point and DiJi (SP8) point on pain severity of primary dysmenorrhea and the associated systemic symptoms. MATERIALS AND METHODS: In this crossover clinical trial, 50 females aged 18-30 years old who met the study criteria and were under the care of Sarpolezahab Health Center were selected. Subjects were randomly assigned to one of two groups and evaluated during three menstrual cycles. We evaluated pain severity using the McGill pain scale and associated systemic symptoms using a verbal multidimensional scoring system. Data acquired from 42 cases were analyzed using SPSS software, with a P value of <0.05 considered significant. RESULTS: The findings of our study indicate that the severity of dysmenorrhea pain diminishes significantly for up to 2 hours following treatment with acupressure at the SP6 and SP8 points (P < 0.001). Furthermore, the severity of associated systemic symptoms reduced significantly after acupressure at the SP6 and SP8 points, except for nausea and vomiting. Comparison of the severity of systemic symptoms with acupressure at the SP6 and SP8 points revealed no significant difference except for severity of fatigue, which was reduced significantly further with SP6 point compared to SP8 point (P = 0.004). CONCLUSION: Acupressure at the SP6 and SP8 points can reduce pain severity of dysmenorrhea for up to 2 hours after application, and these points may be used to alleviate the severity of systemic symptoms accompanying dysmenorrhea.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".