Fostering Pre-Professionals and Learning Experiences in End-of-Life Care Contexts: Music Therapy Internship Supervision
Bibliographic record
Abstract
Certified music therapists use music within therapeutic relationships to address human needs, health, and well-being with a variety of populations. Palliative care and music therapy are holistic and diverse fields, adapting to unique issues within end-of-life contexts. Palliative care music therapy has been formally practiced since the late 1970s and affords a variety of benefits, including pain and anxiety reduction, enhancement of quality of life, emotional expression, and relationship completion. The training of music therapists varies around the globe, but clinical supervisors play a key role in skill acquisition. Clinical supervisors support pre-professionals as they realize the application of their training, foundational competencies, and authentic therapeutic approaches in end-of-life care, while navigating the challenges and rewards of this work. This article is a narrative review which offers background information on palliative care music therapy, and reports the authors' viewpoints and reflections on supervision strategies and models employed with music therapy interns in palliative care settings based on their experiences. Approaches are shared on supporting pre-professionals as they begin working in palliative care contexts, as well as implications for supervision practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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 teacher head, 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".