Effects of music on complications during hemodialysis for chronic renal failure patients
Bibliographic record
Abstract
The study was planned as a case-control study to examine the effects of music on some of the complications experienced by chronic renal failure (CRF) patients during hemodialysis. A total of 60 patients (30 intervention and 30 control) diagnosed with end-stage renal failure undergoing hemodialysis treatment participated in this study. The study was conducted in Manisa Merkez Efendi State Hospital Hemodialysis Unit and Manisa Özel Anemon Hemodialysis between April 2012 and July 2012. The intervention group listened 30 minutes in each session (12 total sessions) Turkish art music at the beginning of the third hour of their hemodialysis sessions. Patient Information Form and visual analog scale to assess pain, nausea, vomiting, and cramps during hemodialysis session were used. For the analysis of data, the number, percentage, chi-square test, and significance test of independent group differences between two averages were conducted. According to the findings of the study, the average of the intervention and control group ages, respectively, was 50.86 ± 11.3 and 55.13 ± 9.68. The primary duration of hemodialysis treatment for both intervention and control groups was "1 year and above" (70.0%). The intervention group's pain and nausea scores were lower than the control group for all 12 sessions. The difference between the intervention and the control group's pain scores was significant (P < 0.05). However, in pain scores from the first session to 12th session, continuous decreasing trend was not observed. According to the results, music can be used as an independent nursing practice for reduction of complications for CRF patients receiving hemodialysis treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".