Effectivenesss of Transcutaneous Electrical Nerve Stimulation and Diadynamic Current on Primary Dysmenorrhea : A Randomized Clinical Trial
Bibliographic record
Abstract
Background: Primary Dysmenorrhoea is a common problem among female adolescents which has become a leading cause of recurrent absenteeism from school or work.Studies have shown that TENS is one of the management options for Dysmenorrhea.Hence, this study was undertaken to compare effect of TENS and Diadynamic Current on Primary Dysmenorrhea.Purpose of the study: The aim of the study was to compare the effect of Transcutaneous Electrical Nerve Stimulation and Diadynamic current on Primary Dysmenorrhea.Method: 32 subjects diagnosed with Primary Dysmenorrhea were included in the study.The subjects were randomly allocated into two groups, where Group A (n=16) received Transcutaneous Electrical Nerve Stimulation (TENS) and Group B (n=16) received Diadynamic current for 5 days.The outcome measures used were Visual Analogue Scale, Moos Menstrual Distress Questionnaire, and McGill Pain Questionnaire.Results: The results showed that the intra group comparison was statistically significant with p= <0.001 for both the groups in terms of VAS, MPQ and MMDQ respectively.Inter group comparison was statistically insignificant with p= 0.53, 0.42, 0.19 for VAS, MPQ and MMDQ respectively.Showing that the Group B has reduced pain significantly more than Group A. Conclusion: This study indicates that both Diadynamic Current and TENS are effective in reducing dysmenorrheal pain.No adverse effects were being observed.The results clearly showed the immediate effect in pain relief after the use of both TENS and Diadynamic current, more in Diadynamic Current.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".