Music Therapy with Adults Diagnosed with Cancer and Their Families
Bibliographic record
Abstract
This chapter describes music therapy in cancer care in Western and Asian countries. Detailed descriptions of cancer prevalence, mortality rates, histological classifications, treatments, and biopsychosocial effects are provided. When affected by cancer, music therapy can offer support, enable symptom alleviation, promote endurance and spiritual well-being, and assist in functional restoration and quality of life improvement. An evolving music therapy assessment procedure in oncology is outlined as well as common music therapy methods used in inpatient and outpatient settings, and to promote community ward-based care. Music therapists can: Replay music from the patients’ and families’ lives; help them to explore new musical experiences, such as improvisation, song writing, chanting and toning; and offer music relaxation and supportive or guided imagery experiences. Research has demonstrated music therapy’s positive effects on patients, their families, and staff care givers, reinforcing its important and meaningful role in multidisciplinary oncology care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".