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Record W4392569953 · doi:10.59451/jami.87535

Facing Death Through Music: Palliative Patients' Experience of Guided Imagery and Music

2023· article· en· W4392569953 on OpenAlexafffund
Sheila Killoran

Bibliographic record

VenueJournal of the Association for Music and Imagery · 2023
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsGrey Nuns Community Hospital
FundersMcGill University Health CentreMcGill University
KeywordsGuided imageryMusic therapyPsychologyPsychotherapistPsychiatryAnxiety

Abstract

fetched live from OpenAlex

Music and imagery techniques can support the management of both the physical and psychosocial-spiritual needs of persons living with a life-limiting illness. The Bonny Method of Guided Imagery and Music (GIM) is a promising yet under-researched music psychotherapy method within the palliative care setting. In this study, six palliative inpatients received GIM sessions and participated in phenomenological interviews about their experience with the method. The resulting themes included (a) deep relaxation, (b) facing death, (c) messages of support, (d) diverse emotions, (e) relationship of self to past and present, (f) music as a guide, and (g) empowerment. Study participants benefited from using this method to help them cope with distressing symptoms and for emotional and spiritual processing at end of life. Applications for symptom management, clinical considerations, and future research directions are discussed.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.002
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 head0.091
GPT teacher head0.364
Teacher spread0.273 · 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 designQualitative
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
Published2023
Admission routes2
Has abstractyes

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