Perceptions of physicians caring for pediatric patients with cancer in Europe: insights into the use of palliative care, its timing, and barriers to early integration
Bibliographic record
Abstract
Background: Integrating pediatric palliative care (PPC) into pediatric oncology standard care is essential. Therefore, it is important to assess physicians' knowledge and perceptions of PPC to optimize its practice. Objective: To evaluate the knowledge, comfort levels, and perspectives of physicians regarding the timing and perceived barriers to integrating PPC into pediatric cancer care across Europe. Design: The Assessing Doctors' Attitudes on Palliative Treatment (ADAPT) survey, originally developed for other global regions, was culturally and contextually adapted for Europe. Setting/Subjects: The survey was distributed via the European Society of Paediatric Oncology (SIOPE) membership listserv. Any physicians caring for children with cancer across Eastern, Southern, Central, and Northern Europe were invited to complete the survey. Results: A total of 198 physicians from 29 European countries completed the ADAPT survey. Physicians demonstrated relative agreement with the World Health Organization's guidance; median alignment was 83.4% (range 59.9%-94.1%). Although most respondents felt comfortable addressing physical (84.4%) and emotional (63.4%) needs, they felt less comfortable addressing spiritual needs (41.9%) and providing grief and bereavement support (48.5%). There were significant regional differences, such as physicians in Eastern and Southern Europe reporting a lack of PPC specialists, opioids, and home-based care, while those in Northern and Central Europe did not. Conclusion: Physicians caring for children with cancer throughout Europe have a good understanding of PPC. However, misconceptions about PPC persist, requiring educational and capacity-building efforts. Additionally, the regional differences in perceived barriers must be addressed to ensure equitable access to PPC for all European children with cancer.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".