P-17 From heartbreak to hope: redefining hospice care through music in hospices
Bibliographic record
Abstract
Background The UK hospice sector faced a collective estimated deficit of £77 million in the financial year 2023-24 (Hospice UK. Hospice sector facing collective deficit of £77 m. [news item] 2024 April 15). Research shows that every £1 invested in social prescribing can yield £4–£11 in savings per person (Fancourt. The relationship between arts and cultural services and health outcomes: a review. 2024). A UK YouGov survey (commissioned by King’s College London) found that ‘nearly a quarter of people (24%) across the UK say they don’t know much about or have not heard of palliative care’ (King’s College London. 65% of adults are worried about access to palliative care. [news item] 2024 April 29). The Lancet Commission on the Value of Death calls for greater civic participation in end-of-life care (Sallnow, Smith, Ahmedzai, et al. Lancet. 2022;399(10327):837-884). Community-led hospice models, such as Kerala’s Neighbourhood Network in Palliative Care, demonstrate the transformative power of civic engagement (D’Eer. The development and evaluation of civic engagement in palliative care: a study of community involvement in end-of-life care. 2024; Kumar. Indian J Palliat Care. 2007;13(1):1–5). Aims To co-design a personalised live music intervention embedded within hospice care practice. Evaluate its impact on patients’ quality of life, family experiences, staff perceptions, and broader community attitudes toward hospice spaces. Methods A six-month pilot at Greenwich & Bexley Community Hospice (now known as the Community Hospice). Monthly personalised live music sessions were delivered by professional musicians, informed by pre-session consultations capturing musical preferences, personal histories, and emotional needs. Sessions were delivered across inpatient wards, gardens, and communal areas, adapted flexibly to clinical realities. The pilot culminated in a large-scale celebration concert in partnership with the Lang Lang International Music Foundation. Results 70+ patients and 100+ family members engaged. Three medically notable transient improvements and restoration of function allowing for meaningful engagement. Zero PRN medications required by whole inpatient cohort during three-hour outdoor concert – the first time in the hospice’s 30-year history. Social media reach over 150,000 views, reaching 91% non-followers, amplifying hospice visibility nationally. Media coverage: BBC Radio 4 (Today Programme), BBC Breakfast, BBC Saturday Live. Qualitative themes 85% of participants reported emotional uplift or memory recall; 70% cited reduced agitation or distress; over 20 cases of strengthened family bonds, participation, and legacy building. Conclusions Embedding personalised music interventions can radically shift hospice culture from clinical isolation to connected, creative community spaces. Arts-based interventions offer a scalable, sustainable public health strategy for normalising hospice care and enriching end-of-life experiences.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.176 | 0.034 |
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".