Home-Based Pediatric Cancer Care: Perspectives and Improvement Suggestions From Children, Family Caregivers, and Clinicians
Bibliographic record
Abstract
PURPOSE: Although the hospital remains the dominant site for delivering most pediatric cancer care, home-based care is increasingly provided. To effectively deliver comprehensive, relevant, and acceptable care in children's homes, the voices of these key informants must be considered. We examined the views of children with cancer, their family caregivers, and clinicians on home-based cancer care to identify necessary strategies to improve the delivery of care. METHODS: Children with cancer, their family caregivers, and multiprofessional clinicians who provide care at a tertiary pediatric care center or in the community participated in audio-recorded, semistructured interviews in French and English. Interviews were conducted until data saturation in each participant group was achieved. Interviews were transcribed, coded, and analyzed using thematic analysis. RESULTS: Thirteen children, 20 family caregivers, and 22 clinicians participated. Home-based care was endorsed as a means to improve child health-, family social- and financial-, and system-level outcomes. The success of a home-based model is built on care that addresses child and family informational, treatment and care, material, and psychosocial needs. Mechanisms to improve care include enhanced homecare agency-hospital-family communication, training for homecare nurses in pediatric cancer care, virtual solutions, and an expanded breadth of services provided in-home. Child-, family-, and system-related factors affect the delivery of optimal home-based care. CONCLUSION: Children, families, and clinicians value a model of pediatric cancer care that incorporates home-based services. The insights of these key informants should be reflected in the principles that become the basis of home-based cancer care best practices.
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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 | 0.028 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".