Characteristics of music intervention for anxiety relief in patients undergoing cardiac catheterization: Scoping Review Protocol
Bibliographic record
Abstract
Introduction: Although music is a non-pharmacological intervention that has been used to reduce anxiety and its manifestations in patients undergoing cardiac catheterization, its effectiveness is controversial. The lack of knowledge of the characteristics that constitute such an intervention may contribute to the lack of consistency. To map the characteristics music intervention to reduce anxiety in patients undergoing cardiac catheterization. Methods and analysis: A scoping review will be conducted according to the Joanna Briggs Institute (JBI) methodology. The searches will be performed using PubMed, CINAHL, PsycINFO, Cochrane, EMBASE, Scopus and LILACS databases. Unpublished studies will be searched using the CAPES Thesis Portal, DART-Europe E-theses Portal, Theses Canada Portal, Pro-Quest and Google Scholar databases. This review will include experimental and quasi-experimental studies that used intervention with music to reduce anxiety in adult patients before, during, or after cardiac catheterization in the hospital setting, published in Portuguese, English, and Spanish with no limit on the year of publication. Two independent reviewers will perform the selection of documents for full reading and data extraction. A third reviewer will resolve disagreements. The data extracted will include the characteristics of the manuscripts, of the research report, and of the intervention. There will be no critical appraisal of the studies. The results will be presented with a data map and in a descriptive approach, aligned with the objective of the scoping review. Ethics and dissemination: This protocol will be published in the registry on the OSF registration website.
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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 | 0.070 | 0.078 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.012 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.075 | 0.012 |
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".