Unmasked Connections: Piloting Virtual Interactive Artist Performances in Healthcare — A Feasibility Study
Bibliographic record
Abstract
The arts offer many health benefits and can be especially impactful in hospital or continuing care facilities through group art interventions or personalized art activities. Arts can also be socially prescribed to fulfill social needs, improve emotional well-being, and have a positive impact of the social determinants of heath. This feasibility study explores the value of a pilot program that brought personalized virtual 1-on-1 art performances to residents in long-term care (LTC) during the Covid-19 pandemic which limited social activities and caused feelings of uncertainty and stress for many people. The purpose of this study was to document the process of developing and executing this pilot program, to evaluate its feasibility, and to provide a testimony to the benefits of art programs in LTC. This study qualifies as a feasibility study because it aimed to evaluate the quality, efficiency, and financial feasibility of the pilot project, making the primary objective of this research quality improvement. Online surveys were completed by the participating LTC residents, the Recreation Staff in the LTC facility, the hired artists, and the organizing team (Radical Connections). The results of the surveys strongly indicate that the pilot was successful and proved to be viable; the sessions were high quality, person-centered artistic care was made accessible to a vulnerable population at a sustainable cost, and most importantly, a demand for this type of program was revealed.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".