“We were learning together and it felt good that way.” A case study of a participatory group music program for cancer patients
Bibliographic record
Abstract
Though there are similarities to music therapy, the field of community music in healthcare, while in its infancy, is steadily growing. This case study explored how semi-formal, active music-making can play a role in illness and recovery and provide patients with a sense of voice, connection, and community, and the efficacy of community music programming in a hospital. Six participants began and three participants completed a 6-week music class learning the ukulele. Interpretative Phenomenological Analysis (IPA) was used as a method for data analysis from semi-structured pre-questionnaires, transcribed classes, transcribed post-interviews, and weekly questionnaires from both the participants and the facilitator. Emergent and recurrent themes central to the participants’ experiences were discovered: (1) Music as a connector, (2) Music within us external to cancer, (3) Musical experiences interrupted by cancer, (4) Music creates empowerment. Subthemes and individual experiences are also explored. Implications for future research and music’s role in improving the Patient Experience in hospital settings are discussed.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.014 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".