End-of-Life Childhood Cancer Research: A Systematic Review
Bibliographic record
Abstract
CONTEXT: Children with incurable cancer may participate in research studies at the end of life (EOL). These studies create knowledge that can improve the care of future patients. OBJECTIVE: To describe stakeholder perspectives regarding research studies involving children with cancer at the EOL by conduct of a systematic review. DATA SOURCES: We used the following data sources: Ovid Medline, Embase, the Cumulative Index to Nursing and Allied Health Literature, PsycINFO, Web of Science, and ProQuest (inception until August 2020). STUDY SELECTION: We selected 24 articles published in English that examined perceptions or experiences of research participation for children with cancer at the EOL from the perspectives of children, parents, and health professionals (HPs). DATA EXTRACTION: Two authors independently extracted data, assessed study quality, and performed thematic analysis and synthesis. RESULTS: Eight themes were identified: (1) seeking control; (2) faith, hope, and uncertainty; (3) being a good parent; (4) helping others; (5) barriers and facilitators; (6) information and understanding; (7) the role of HPs in consent and beyond; and (8) involvement of the child in decision-making. LIMITATIONS: Study designs were heterogeneous. Only one study discussed palliative care research. CONCLUSIONS: Some families participate in EOL research seeking to gain control and sustain hope, despite uncertainty. Other families choose against research, prioritizing quality of life. Parents may perceive research participation as the role of a "good parent" and hope to help others. HPs have positive views of EOL research but fear that parents lack understanding of the purpose of studies and the likelihood of benefit. We identified barriers to research participation and informed consent.
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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 | 0.025 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".