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Record W2102033082 · doi:10.1017/s1478951508000436

The conjoint use of music therapy and reflexology with hospitalized advanced stage cancer patients and their families

2008· article· en· W2102033082 on OpenAlexaff
Lucanne Magill, Susan Berenson

Bibliographic record

VenuePalliative & Supportive Care · 2008
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsReflexologyPsychosocialAnxietyPalliative careMusic therapyMedicineStage (stratigraphy)PsychotherapistMassagePhysical therapyPsychologyAlternative medicineNursingPsychiatry

Abstract

fetched live from OpenAlex

Advanced stage cancer patients experience debilitating physical symptoms as well as profound emotional and spiritual struggles. Advanced disease is accompanied by multiple changes and losses for the patient and the family. Palliative care focuses on the relief of overall suffering of patients and families, including symptom control, psychosocial support, and the meeting of spiritual needs. Music therapy and reflexology are complementary therapies that can soothe and provide comfort. When used conjointly, they provide a multifaceted experience that can aid in the reduction of anxiety, pain, and isolation; facilitate communication between patients, family members, and staff; and provide the potential for a more peaceful dying experience for all involved. This article addresses the benefits of the combined use of music therapy and reflexology. Two case studies are presented to illustrate the application and benefits of this dual approach for patients and their families regarding adjustment to the end of life in the presence of anxiety and cognitive impairment.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.081
GPT teacher head0.346
Teacher spread0.265 · 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 designObservational
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

Citations35
Published2008
Admission routes1
Has abstractyes

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