A qualitative exploration of music therapy practice development in intellectual disability services in Ireland: “The future is the community”
Bibliographic record
Abstract
Introduction The task of music therapy service development is one that is faced by many music therapists worldwide as they expand their professional practice. While general strategies for effective service development have been highlighted, little is known about successful development of music therapy programmes within the context of intellectual disability (ID) services as a leading employment sector in Ireland.Method This study explored perspectives on music therapy service development within ID organisations in Ireland. Six music therapists and three music therapy managers who had experience of working in ID participated in individual semi-structured interviews. Interviews were analysed using reflexive thematic analysis.Results Analysis of nine interviews revealed four main themes including (1) Music therapist’s unexpected realities of service development, (2) Ingredients of successful music therapy service development including a) Getting the pitch right, b) Looking through the manager lens and c) Careful and sustainable scheduling, (3) The educational role of the music therapist in ID settings and (4) The value of a flexible and community-oriented approach to music therapy service development.Discussion Findings suggest that when developing new music therapy programmes in ID music therapists may benefit from remaining curious, flexible and clearly focussed on how their service can best address service user needs. While this pursuit makes navigation of unchartered territory highly likely, we recommend being mindful of the transferability of the music therapy clinical skillset, engaging with other health professionals and exploring manager optics, while employing a theoretical approach that aligns with the organisational culture of the ID setting.
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 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 | 0.016 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".