Is there a role for clowns in paediatric intensive care units?
Bibliographic record
Abstract
Hospital clowning is a programme in healthcare facilities involving visits from specially trained actors. In the paediatric intensive care unit (PICU), clowning may appear inappropriate and less intuitive. The patient could appear too ill and/or sedated, the environment too crowded or chaotic and the parents too stressed. Relying on our experience with professionally trained clowns both in France and Canada, the purpose of this article is to offer a model for hospital clowning and to suggest standards of practice for the implementation of clowning in PICUs. In this work, we provide a framework for the implementation of clown care in the PICU, to overcome the challenges related to the complex technical environment, the patient's critical illness and the high parental stress levels. Regardless of the specifics of the PICU, our experience suggests that professional clown activity is feasible, safe and can offer multiple benefits to the child, his/her parents and to hospital personnel. Due to the specific challenges in the PICU, clowns must be educated and prepared to work in this highly specialised environment. We stress that prior to clowning in a PICU, professional performers must be highly trained, experienced, abide by a code of ethics and be fully accepted by the treating healthcare team.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".