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Record W2750744978 · doi:10.1093/jmt/thx010

Singing and Vocal Interventions in Palliative and Cancer Care: Music Therapists’ Perceptions of Usage

2017· article· en· W2750744978 on OpenAlexafffundabout
Amy Clements-Cortés

Bibliographic record

VenueJournal of Music Therapy · 2017
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of Toronto
FundersOntario Medical Association
KeywordsSingingPsychological interventionMusic therapyPalliative carePsychologyMoodIntervention (counseling)PsychotherapistMedicineNursingClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Music therapists in palliative and cancer care settings often use singing and vocal interventions. Although benefits for these interventions are emerging, more information is needed on what type of singing interventions are being used by credentialed music therapists, and what goal areas are being addressed. OBJECTIVE: To assess music therapists' perceptions on how they use singing and vocal interventions in palliative and cancer care environments. METHOD: Eighty credentialed music therapists from Canada and the United States participated in this two-part convergent mixed-methods study that began with an online survey, followed by individual interviews with 50% (n = 40) of the survey participants. RESULTS: In both palliative and cancer care, singing client-preferred music and singing for relaxation were the most frequently used interventions. In palliative care, the most commonly addressed goals were to increase self-expression, improve mood, and create a feeling of togetherness between individuals receiving palliative care and their family. In cancer care, the most commonly addressed goals were to support breathing, improve mood, and support reminiscence. Seven themes emerged from therapist interviews: containing the space, connection, soothing, identity, freeing the voice within, letting go, and honoring. CONCLUSIONS: Music therapists use singing to address the physical, emotional, social, and spiritual goals of patients, and described singing interventions as accessible and effective. Further research is recommended to examine intervention efficacy and identify factors responsible that contribute to clinical benefit.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.128
GPT teacher head0.431
Teacher spread0.303 · 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 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

Citations24
Published2017
Admission routes3
Has abstractyes

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