Music Interventions to Reduce Pain in Postoperative Patients Benigna Prostate Hyperplasia
Bibliographic record
Abstract
Benigna Prostate Hyperplasia (BPH) is a progressive enlargement of the prostate gland that can be surgically remedied. The result of surgery can cause pain. One of the pains is with the relaxation of music. Music relaxation is an action to free mentally and physically from tension and stress so as to increase tolerance to pain. The objective of the study is to know the music intervention to reduce pain in post-operative benigna prostate hyperplasia patients. This research is a literature study with a PRISMA approach and a systematic review using PICO. The search databases used are Google Scholar, PubMed, Alberta Health Services, and Wiley Online Library, with keywords. The results of the review obtained revealed that 15% to 60% of men over 40 years old have BPH, while TURP primarily occurs in patients aged 61-70 years, and all BPH patients experience pain and experience depression levels. 24.9% of patients suffered varying degrees of depression, including mild symptoms of 20.9% and moderate/severe symptoms of (3.9%). Patients were aged 61-70 years, 39.5%. Pasin returned to normal activity by 71%. TURP affects patient anxiety with a signification of 0.005. Musical interventions are effective for lowering pain in postoperative BPH patients. Advice to nurses is expected to provide musical interventions as an alternative to reduce pain in postoperative BPH patients.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".