23 Findings from a pilot and feasibility trial of a music therapy intervention in specialist palliative care
Bibliographic record
Abstract
Introduction Music therapy aligns to the holistic approach to palliative and end-of-life care (PEOLC) with increased prevalence in PEOLC settings (Graham-Wiseneret al.2018). Despite this there is a dearth of high-quality evidence examining the impact of music therapy towards end of life on quality of life (McConnellet al.2016). Aims The aim of this pilot and feasibility study was to: test procedures; outcomes and validated tools; estimate recruitment and attrition rates; and calculate the sample size required for a phase III randomised controlled trial. Methods A single-centre pilot and feasibility trial with patients admitted to a specialist palliative care inpatient unit within the United Kingdom. Participants were randomised (1:1) to either a music therapy intervention of two 30–45 min sessions of music therapy per week for three consecutive weeks or usual care. The primary outcome measure was to evaualte the feasibility of administering the McGill Quality of Life Questionnaire (MQoL) baseline with follow-up measures at one, three and five weeks. Results 51 participants were recruited to the trial over a 12 month period. Feasibility of administering music therapy intervention and attrition rates identified one-week follow-up as an appropriate primary outcome. Results suggest a likely effect on MQoL total score between intervention and control arms in particular the existential subscale. Conclusion The current study resolved a number of issues towards informing robust procedures for a phase III RCT. This data is urgently needed to ensure an evidence-based decision on inclusion of music therapy in palliative care services. References . Graham-Wisener L, Watts G, Kirkwood J, Harrison C, McEwan J, Porter S, Reid J, McConnell TH. Music therapy in UK palliative and end-of-life care: A service evaluation. BMJ supportive & palliative care2018. . McConnell T, Scott D, Porter S. Music therapy for end-of-life care: An updated systematic review. Palliative Medicine2016;30(9):877–883.
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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 | 0.038 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".