Pain management in intellectually disabled children: a survey of perceptions and current practices among Dutch anesthesiologists
Bibliographic record
Abstract
BACKGROUND: Intellectually disabled children are more likely to undergo surgical interventions and almost all have comorbidities that need to be managed. Compared with controls, intellectually disabled children tend to receive less intraoperative analgesia and fewer of them are assessed for postoperative pain. AIM: To evaluate perceptions and practices of anesthesiologists in the Netherlands concerning pain management in intellectually disabled children. METHODS/MATERIALS: We surveyed members of the Section on Pediatric Anesthesiology of the Netherlands Society of Anesthesiology in 2005 and 2009, using a self-designed questionnaire. RESULTS: The response rate was 47% in both years. In 2005, 32% of the anesthesiologists rated intellectually disabled children as 'more sensitive to pain' than nonintellectually disabled children--vs 25% in 2009. But no more than 7% in 2005 vs 6% in 2009 agreed with the statement 'children with intellectually disabled children need more analgesia'. Most anesthesiologists gave similar doses of intraoperative opioids for intellectually disabled and nonintellectually disabled children, 92% in 2005 vs 89% in 2009. In 2005, only 3% applied a pain assessment tool validated for intellectually disabled children, vs 4% in 2009. CONCLUSIONS: Anesthesiologists in the Netherlands take a different approach when caring for intellectually disabled children and they were not aware of pain observation scales for these children. However, the majority think that intellectually disabled children are not more sensitive to pain or require more analgesia. These opinions did not change over the 4-year period. One way to proceed is to implement validated pain assessment tools and to invest in education.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".