Neutral douche: a hydrotherapeutic tool to manage pain and systemic symptoms in primary dysmenorrhea - a randomised controlled study
Bibliographic record
Abstract
BACKGROUND & OBJECTIVES: The douche, one of the hydrotherapeutic treatment modality is commonly used by Naturopathy physicians as a treatment of choice in the management of several ailments. This study was done to assess the effect of full body neutral douche in the management of pain and systemic symptoms in adult females with primary dysmenorrhoea. METHODS: 68 subjects of age 18-22 years with primary dysmenorrhoea were recruited for the study and were randomly divided into two groups: the experimental group (n = 34) and the control group (n = 34). The experimental group received whole body neutral douche, whereas the control group followed the routine as usual. Assessments for the pain, systemic symptoms and menstrual cramps were done by using McGill Pain Questionnaire, Verbal multidimensional scoring system and analog scale for severity of pain and menstrual cramps respectively at baseline, day 30 and day 60 of intervention. Two- way repeated measures of ANOVA was performed to understand the between group changes, adjusted for the respective baseline values and age. RESULT: Data was analyzed with SPSS (Version 21.0) package. Neutral douche resulted in significant improvement in pain [F(2,66) = 114.564, p < 0.0005, partial ?2 = 0.771], severity of pain [F(2,66) = 70.418, p < 0.0005, partial ?2 = 0.681], cramps [F(2,66) = 75.986, p < 0.0005, partial ?2 = 0.697] and systemic symptoms [F(2,66) = 14.64, p < 0.0005, partial ?2 = 0.307] as compared to the control group. CONCLUSION: Findings suggest that neutral douche can be used as a non-pharmacological intervention in the management of pain and systemic symptoms in primary 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".