Music in the endoscopy suite: a meta-analysis of randomized controlled studies
Bibliographic record
Abstract
BACKGROUND AND STUDY AIM: Prior studies have suggested that music therapy can provide stress relief and analgesia. In this meta-analysis we focused on the effects of music therapy on patients undergoing gastrointestinal endoscopic procedures. MATERIALS AND METHODS: A literature search using the PubMed and Cochrane Library databases and a manual search led to the inclusion of six randomized controlled trials that examined the effects of music therapy on patients undergoing gastrointestinal endoscopic procedures. After data extraction, four separate meta-analyses were performed: in the three studies that did not use pharmacotherapy (group A), anxiety levels were used as a measure of efficacy; in the three studies in which pharmacotherapy was used (group B), sedation and analgesia requirements and procedure duration times were analyzed. RESULTS: A total of 641 patients were included in the analysis. In group A, patients receiving music therapy exhibited lower anxiety levels (8.6% reduction, P = 0.004), compared with controls. In group B, patients receiving music therapy exhibited statistically significant reductions in analgesia requirements (29.7% reduction, P = 0.001) and procedure times (21% reduction, P = 0.002), and a reduction in sedation requirements that approached significance (15% reduction, P = 0.055), in comparison with controls. CONCLUSIONS: Music therapy is an effective tool for stress relief and analgesia in patients undergoing gastrointestinal endoscopic procedures.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.028 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".