Pediatricians' Perceptions of and Preferred Timing for Pediatric Palliative Care
Bibliographic record
Abstract
OBJECTIVES: This study investigates how pediatricians define palliative care and their preferences regarding the timing of referrals for children with life-limiting diseases. METHODS: A random sample of 800 pediatricians in Florida and California received mail and online surveys. Analyses included descriptive and multivariate regression analyses. RESULTS: Of all respondents (N = 303), 49.1% were female, 34.0% had been practicing for > or =20 years, 44.2% were members of a racial/ethnic minority, and 76.2% were in private practice. Pediatricians were divided in their definitions of palliative care; 41.9% defined it as hospice care, 31.9% offered alternative definitions, and 26.2% did not know. Although pediatricians overwhelmingly cited the need for many types of palliative care services, only 49.3% had ever referred patients to palliative care and 29.4% did not know whether local services existed. For 13 diseases that vary in life limitation, there was no consensus regarding the timing of referrals. Diversity across diseases predicted the most variation in referrals, whereas pediatrician characteristics did not. CONCLUSIONS: Despite recommendations to refer children to palliative care early in the course of illness, most pediatricians define palliative care as similar to hospice care and refer patients once curative therapy is no longer an option. Creating a more-practical definition of care, one that emphasizes an array of services throughout the course of an illness, as opposed to hospice care, may increase earlier palliative care referrals for children with life-limiting illnesses.
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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 | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".