Improving Collaboration Between Staff, Family Members, and Artists in Long-Term Dementia Care: A Participatory Action Research Project Into Health Care Clowning
Bibliographic record
Abstract
A growing amount of evidence shows the positive impact of arts-based interventions in dementia care. Existing studies focus on the impact of such interventions on individuals with dementia, yet there is little known about contextual factors influencing the impact of such practices. Contextual factors include personal and relational processes, such as the collaboration between staff, family members, and artists. It also includes making specific organizational choices about the way in which arts and care organizations structure and organize their collaboration. The study aimed to investigate contextual factors influencing the potential impact of health care clowning for persons with dementia. Through multi-country participatory action research (PAR) into health care clowning in dementia care, this study engaged artists (health care clowns), staff, family members, and representatives from four long-term dementia care facilities and three health care clowning organizations. The presented findings show that for arts-based interventions to have sustainable impact within the context of long-term dementia care, focusing on the intervention itself is not enough. Additional time and space are needed for implementation of the intervention and good collaboration on the work floor. The results of this study demonstrate that elements in the PAR process such as open dialogue and arts-based research methods can create communicative spaces which can serve as a catalyst for effective implementation of arts-based practices in long-term dementia care. Elements of the PAR process can therefore be regarded as a form of successful boundary work and in the future could be applied when implementing arts-based interventions in care settings.
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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 | 0.049 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".