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Record W4416738610 · doi:10.1371/journal.pone.0335895

The use of music in nursing care for psychological distress reduction in cancer patients: A scoping review protocol

2025· article· en· W4416738610 on OpenAlexaboutno aff
Karena Cristina da Silva Leal, Maria Améllia Lopes Cabral, Marllon Frank Teixeira Ferreira, Denilson Leal Rocha, Lara Dantas de Rubim Costa, Geovana Caroliny de Morais Silva, Louise Constância de Melo Alves Silva, Daniele Vieira Dantas, Rodrigo Assis Neves Dantas

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
Fundersnot available
KeywordsGrey literatureMEDLINEProtocol (science)Cochrane LibraryCINAHLNursing researchPsychological interventionHealth careMusic therapyInclusion (mineral)

Abstract

fetched live from OpenAlex

Psychological distress in cancer patients is a frequent and complex condition that significantly compromises quality of life, from diagnosis to palliative care. In this context, the use of music emerges as a promising, safe, and low-cost complementary practice capable of alleviating symptoms such as emotional distress. However, there are still gaps in the literature regarding the types, contexts, and specific effects of musical interventions in cancer patients. Thus, this protocol proposes a scoping review to map the available scientific evidence on the use of music as an intervention for the reduction of psychological distress in cancer patients. The methodology will adhere to the guidelines of the Joanna Briggs Institute and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist. The search will be conducted across twenty data sources, including PubMed Central, Latin American and Caribbean Literature in Health Sciences, Cumulative Index to Nursing and Allied Health Literature, Web of Science, Scientific Electronic Library Online, Cochrane Library, Elsevier's Scopus, ScienceDirect, Wiley Online Library, and the Virtual Health Library. For gray literature, Catalog of Theses and Dissertations of the Coordination for the Improvement of Higher Education Personnel, the Networked Digital Library of Theses and Dissertations,Google Scholar, European Thesis Portal; Electronic Thesis Online Service; Open Access Scientific Repository of Portugal; National Theses and Dissertations; Theses Canada; Treasury of the National Library of Australia; Online Academic Archive will be searched. Study screening and selection will be performed independently by two researchers according to the inclusion and exclusion criteria. Relevant data will be extracted into a structured spreadsheet, including study characteristics, type and setting of the musical intervention, outcomes related to psychological distress, and the role of nursing. The findings are expected to inform clinical practice, particularly in the field of oncology nursing, as well as to identify gaps for future research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.874
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.224
GPT teacher head0.482
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreProtocol

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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