Music Therapists’ Global Perspectives on Telehealth Music Therapy: A Qualitative Interview Inquiry
Bibliographic record
Abstract
Abstract Telehealth music therapy (TMT) grew exponentially during the COVID-19 pandemic and has continued to be integrated in music therapy praxis. This interview study, which is a follow-up to a large international study of 572 music therapists, reports the perceptions and experiences of 20 music therapists from 10 countries across 5 global regions. Five themes arose from the qualitative analysis, including (1) accessibility of TMT, (2) suitability of TMT, (3) safety within TMT, (4) technology within TMT, and (5) advancing the practice of TMT. Several recommendations are provided for music therapy clinicians, educators and researchers to consider for the future of TMT including the inclusion of TMT theoretical and experiential training for preprofessionals, client perceptions, experiences and desires for TMT, and the role of caregivers in TMT provision.
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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 | 0.026 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".