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Record W4312048467 · doi:10.26855/ijcemr.2022.10.016

Music Therapy and Advanced Dementia

2022· article· en· W4312048467 on OpenAlexaff
Jiajun Qiu

Bibliographic record

VenueInternational Journal of Clinical and Experimental Medicine Research · 2022
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsEarl Haig Secondary School
Fundersnot available
KeywordsMusic therapyDementiaPsychologyMedicinePsychotherapistInternal medicineDisease

Abstract

fetched live from OpenAlex

Advanced dementia is a progressive neurodegenerative disease that incurs substantial suffering and costs to the patient, family members, and care providers.In 2019, dementia affected an estimated 55.2 million people worldwide and was the 7th leading cause of death.Common symptoms of advanced dementia include impairment in behavioral, cognitive, and social function, which can severely compromise a patient's ability to perform activities of daily living (ADL).While there is no known cure, music therapy (MT) has risen in popularity as a non-pharmacological, palliative treatment.This paper examines existing literature on the effects of musical intervention on patients with advanced dementia.Most study results are positive, suggesting that MT may improve patients' quality of life.For example, some have shown that MT can improve pleasure, personal well-being, sundowning, swallowing, etc. Nonetheless, limitations in the studies are to be considered and future investigations on a greater scale are recommended to explore the clinical significance of these results.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.438
GPT teacher head0.630
Teacher spread0.192 · 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 designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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