Ideas for improving preoperative preparation of children for anesthesia: Winners of a competition in France
Bibliographic record
Abstract
SPARADRAP, a nonprofit organization based in Paris, France, was founded in 1993 with the objectives of improving management of pain in children, better preparing children for health care interventions, and more fully involving family and friends when children are sick and hospitalized. Despite the improvement of technical methods and safety, anesthesia remains a cause of major concern for children and parents. These legitimate fears and pain can be significantly reduced when a project to better welcome and prepare children is established by departments of anesthesia. To encourage these initiatives and promote their development, SPARADRAP launched a national competition in 2011 for teams from the anesthesia departments of hospitals in France. SPARADRAP received 13 eligible applications from institutions ranging from academic tertiary care hospitals to primary care hospitals. The multidisciplinary jury comprised professionals from anesthesiology (nurse and physician), psychology, and sociology. The jury paid special attention to methods that promote the following: provision of information to child and families, well-being and comfort, separation from parents, assessment and relief of pain, and parental presence postoperatively. The team approach, the introduction of protocols, and a process of evaluation and sustainability were also part of the selection criteria. The winners of the contest were notified in September, 2012 (http://tinyurl.com/prix-duconcours), and they were awarded certificates depicting gold, silver and bronze anesthesia masks (Table 1). This competition revealed the inventiveness and effort of some units in taking care of children undergoing surgery and in ensuring that the operating room was no longer a closed and frightening place.
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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 | 0.019 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".