Overcoming Barriers to Early Integration of Specialized Palliative Care Services in Children and Adolescents with Cancer: A Pilot Qualitative Study of Canadian Healthcare Providers
Bibliographic record
Abstract
Background The integration of specialized palliative care (SPC) in pediatric oncology aims to minimize the significant suffering experienced by children and families. While early integration of SPC is recommended, barriers to integration of SPC exist and the ways to overcome those barriers are not entirely clear. Procedure We conducted semi-structured interviews of Candian healthcare providers (HCPs) in the fields of pediatric oncology and pediatric palliative care. We performed thematic analysis on the transcripts of those interviews to identify barriers to early SPC integration and solutions to overcome those barriers. Results Eight HCPs were interviewed (4 pediatric oncology and 4 palliative care providers). While the views of HCPs varied about the integration framework (universal, criteria-based, or unguided provider-initiated referrals), the importance of early SPC integration in patients with a high risk of mortality or high symptom burden was consistently described. We identified categories of barriers to early SPC integration including family perception, healthcare team-related, and process/systemic barriers. Common reported barriers include the association of palliative care with death or giving up and the perception that the family is “not ready” to meet SPC. Categories of solutions include improving communication with families, enhancing the collaboration between SPC and oncology teams, and optimizing the referral processes. Participants described strategies that often addressed several categories of barriers. Such strategies include skillful introduction of SPC to families and regular discussions amongst the pediatric oncology and SPC teams. Conclusion Barriers to early integration of SPC can be overcome through thoughtful discussions amongst HCPs. Those strategies should be considered when optimizing SPC integration with the goal of reducing the suffering of children and adolescents with cancer and their families.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".