Arts engagement facilitated by artists with individuals with life-limiting illness: A systematic integrative review of the literature
Bibliographic record
Abstract
BACKGROUND: Living with life-limiting illness significantly impacts quality of life. A growing body of evidence suggests that arts engagement facilitated by artists promotes well-being. However, no synthesis of the literature exists to describe arts engagement delivered by artists with individuals receiving palliative care. AIM: To systematically review and synthesize evidence to identify outcomes and key knowledge gaps to inform future research and practice. DESIGN: A systematic integrative literature review was conducted using a pre-defined search strategy and reported using PRISMA guidelines. Analysis was conducted iteratively and synthesis achieved using constant comparison to generate themes. DATA SOURCES: PubMed/MEDLINE, CINAHL, PsycINFO, Scopus, Web of Science, and Embase were searched for studies published between database inception and August 2020. Search terms included variations on arts/artists; patients/service users; and palliative or end-of-life care. Eligibility criteria was applied and study quality assessed. RESULTS: Seven reviewed studies explored literary, performing, and visual arts engagement in hospitals, hospice and community settings in England, the United States, France, and Canada. Study designs, interventions and findings were discussed. Themes identified across studies associated arts engagement with (1) a sense of well-being, (2) a newly discovered, or re-framed, sense of self, (3) connection with others, and (4) challenges associated with practice. CONCLUSION: Recommendations for future research were offered in order to maximize benefits, minimize risks and address complexity of artists' engagement in palliative care including: (1) consistency in methods and reporting; (2) inclusion of wider perspectives; and (3) key considerations for adapting the arts by health condition and art form.
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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 | 0.013 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".