“Some things are even worse than telling a child he is going to die”: Pediatric oncology healthcare professionals perspectives on communicating with children about cancer and end of life
Bibliographic record
Abstract
INTRODUCTION: This study explored pediatric oncology healthcare professionals' (HCPs) perspectives on direct communication with children with advanced disease about their disease, palliative care, and end-of-life (EOL) communication. METHODS: Forty-six pediatric oncologists, nurses, psychosocial team members, and other HCPs from six hospital centers in Israel participated in semi-structured interviews. The Grounded Theory method was used. Data were analyzed line-by-line with codes and categories developed inductively from participants' narratives. RESULTS: HCPs viewed communication about disease progression and EOL as vital because children were often aware of their prognosis, because lack of communication could lead to emotional distress, and because communication is a prerequisite for shared decision-making. HCPs identified several barriers for communication including HCP barriers (such as emotional strains, lack of training), parental barriers, guardianship law, and language and culture. HCPs also described strategies to promote EOL communication. Direct strategies include tailoring communication, allowing for silence, echoing children's questions, giving information gradually, and answering direct questions honestly. Indirect strategies included encouraging parents to talk to their children and teamwork with colleagues. CONCLUSIONS: Open communication with children who have cancer is essential. Nevertheless, multiple barriers persist. The rising accessibility of online information calls for urgent training of HCPs in communication so that children will not turn to unmediated and potentially misleading information online in the absence of HCP communication. Evidence-based effective communication training modules and emotional support should be offered to HCPs. Knowledge about children's development, age-appropriate communication, and cultural sensitivity should be included in this training.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".