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Music as nursing intervention for pain in five Asian countries*

2006· review· en· W1997881572 on OpenAlexfundno aff
Perry Lim, Rozzano G.R.A.C. Locsin

Bibliographic record

VenueInternational Nursing Review · 2006
Typereview
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
FundersMcGill University
KeywordsIntervention (counseling)Music therapyInclusion (mineral)MedicineChinaPsychologyNursingPhysical therapyHistorySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: The use of music as intervention for relieving pain has increased in recent years, prompting its growing use among the people of the western world. However, among Asians, music has long been used for this purpose and continues to be so today. Despite this common knowledge, Asians have not generally written about the therapeutic effects of music. Consequently, most of the published research studies supporting this claim were conducted in western settings using western music. PURPOSE: To describe the use of music as intervention in painful conditions as experienced by people in five Asian countries: China, Thailand, Philippines, South Korea and Taiwan. METHOD: Descriptive survey of studies using music as intervention for painful conditions conducted in selected five Asian countries. FINDINGS: Twelve studies including theses and dissertations, published and unpublished, were found; however, only nine met the inclusion criteria. Data were categorized according to research design, sample size, gender, age, duration of music, frequency of music intervention, types of pain and instruments used to measure pain, conceptual or theoretical frameworks and statistical significance of the study. Five of the nine studies declared significant decrease in pain, while three reported mixed results. Fundamentally, the findings of the studies suggested that with music, relief of pain was possible. IMPLICATIONS: The mixed results imply the need for further investigation of the effects of music in painful conditions. Thus, the authors suggest continuing studies on the effects of music as intervention in painful conditions, and encourage increasing global dissemination of these studies, particularly in international journals.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.843
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.086
GPT teacher head0.492
Teacher spread0.406 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations24
Published2006
Admission routes1
Has abstractyes

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