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Record W2998464439 · doi:10.7454/uiphm.v4i1.260

Classical Music Therapy as The Intervention to Relieve Headache in A Meningitis Patient

2020· article· en· W2998464439 on OpenAlexaboutno aff
Gayatri Mauly Purwandari, Sri Yona

Bibliographic record

VenueUI Proceedings on Health and Medicine · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMethodologies in Health Research and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMusic therapyIntervention (counseling)MeningitisPhysical therapyPediatricsPsychiatry

Abstract

fetched live from OpenAlex

Objective: Headache is a manifestation of inflammatory response from meningeal infection. Headache may affect client physically and psychologically thus it requires treatment. This paper aimed to analyze implementation of classical music therapy as non-pharmacological intervention in relieving headache in patient with meningitis. Methods: This was a case study to evaluate the effectiveness of classical music therapy to relieve patient’s headache. The intervention was implemented for 3 days long by playing Beethoven Symphony 6. The headache was evaluated by using McGill Pain Questionnaire. Results: The result indicated a decrease in pain intensity from score of 8 to 6 in the third day of implementation. Conclusion: Classical music therapy relieved headache in patient with meningitis. Nurses are suggested to implement classical music therapy on client with headache in order to relieve and alleviate pain. Key words: Classical music, meningitis, pain

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.478
GPT teacher head0.573
Teacher spread0.096 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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

Citations2
Published2020
Admission routes1
Has abstractyes

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