Parents’ Experiences and Clinicians’ Perceptions of Managing Cancer Pain in Young Children at Home
Bibliographic record
Abstract
BACKGROUND: Pain is a prevalent and distressing symptom for children with cancer, negatively affecting quality of life and family functioning. While most research focuses on hospital-based care, many pain episodes occur at home, where parents act as primary caregivers with limited access to evidence-based symptom management. Young children are particularly vulnerable due to limited self-reporting capacity and reliance on parental assessment. We aimed to explore parent experiences and pediatric oncology clinician perceptions of young children's cancer pain at home, its impact on families, and recommended supports. METHODS: Using an interpretive descriptive qualitative design, we conducted semi-structured interviews with parents of children aged 2-11 years undergoing outpatient cancer treatment and clinicians at two hospitals in Canada and the United States. Data were analyzed using thematic analysis. RESULTS: In total, 21 parents and 21 clinicians participated. Three themes were developed: (1) the multifaceted experience of young children's cancer pain at home, (2) the ripple effects of a young child's cancer pain on the family unit, and (3) assessing and treating children's cancer pain at home. CONCLUSION: Managing cancer pain at home places substantial emotional and practical demands on the families of young children. Our findings highlight that structured supports providing parents and clinicians with education, effective communication pathways, and collaboration opportunities may optimize home-based pain care, reduce caregiving burden, and improve outcomes for children and their families.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".