Art therapy and social function in palliative care patients: a mixed-method pilot study
Bibliographic record
Abstract
OBJECTIVES: To evaluate the influence of art therapy in reducing palliative symptoms, on social availability and on perceptions of aesthetics in hospitalised palliative care patients. The secondary objective was to evaluate its influence on bereaved families. METHODS: A mixed-method quasi-experimental before and after study comprising a follow-up postal survey of bereaved families. All patients who were keen to have art therapy sessions were eligible. We used patient-reported outcome scales 5 min before and after the session. The Edmonton Symptom Assessment Scale has been used for pain, anxiety, well-being, fatigue and depression. Ten-point visual analogue scales were used for social availability, lack of desire and wishes, and perceptions of aesthetics based on the Beautiful-Well-Good model. A postal survey was sent to bereaved families. Correlations and data mining analyses were performed. RESULTS: In all, 24 patients were recruited for a total of 53 art therapy sessions analysed. Seven families completed the survey. Art therapy significantly reduced the assessed symptoms and overall symptom distress by 54.4% (p <0.001, d = 1.08). It also decreased the feeling of social unavailability (-59%, d = 0.67) and the lack of desire and wishes (-60%, d=0.86). The analysis of the family questionnaires indicates the positive effects regarding support, artwork and feelings during illness and grief. CONCLUSION: Our results suggest an overall improvement in the symptoms experienced and social functioning of palliative patients. Based on our findings, we propose a model for the potential mechanism of action of art therapy.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".