Effect of Benson Relaxation Technique on Intensity of Post Cesarean Section Pain among Primipara Women
Bibliographic record
Abstract
Background: Benson relaxation technique is an effective and safe method for reducing the intensity of post cesarean section pain. Aim: The present study aimed to evaluate effect of Benson relaxation technique on intensity of post cesarean section pain among primipara women. Design: A quasi experimental design was used to fulfill the aim of the present study. Setting: Post-partum unit of Obstetrics and Gynecology at Benha university hospital. Sample: A Purposive sample consisted of 120 primipara women after cesarean section which divided into two groups study and control group (60 for each). Tools: Data was collected through two main tools; I-A structured interviewing questionnaire, II-The short-form McGill pain questionnaire. Results: A statistically significant difference was observed in pain intensity between two groups after application of Benson relaxation technique at the four phases (p< 0.05) as pain intensity decreased in the study group more than the control group. Conclusion: Practicing of Benson's relaxation technique had a positive effect on reducing the intensity of post cesarean section pain among primipara women. Recommendation: Benson relaxation technique should be recommended as non pharmacological routine of care in maternity hospitals for reducing intensity of post cesarean pain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".