“It’s More Difficult…”: Clinicians’ Experience Providing Palliative Care to Adolescents and Young Adults Diagnosed With Advanced Cancer
Bibliographic record
Abstract
PURPOSE: Adolescents and young adults (AYAs; age 15-39 years) with advanced cancer are a population in whom quality of life is uniquely affected because of their stage of life. However, training focused on palliative care for AYAs is not routinely provided for health care providers (HCPs) in oncology. This study aims to explore the experiences of HCPs involved in introducing and providing palliative care caring for AYAs with advanced cancer and their families to understand the unique challenges HCPs experience. METHODS: Using a qualitative descriptive design, semistructured interviews were conducted with medical and radiation oncologists, palliative care physicians, psychiatrists, and advanced practice nurses involved in caring for AYAs diagnosed with advanced cancer (N = 19). Interviews were transcribed verbatim and analyzed using thematic analysis in combination with constant comparative analysis and theoretical sampling. RESULTS: There were 19 participants, 9 men and 10 women, with a median age of 45 years (range, 24-67 years). Six were palliative care physicians, 5 medical oncologists, 4 nurse practitioners, and 2 each radiation oncologists and psychiatrists. Overall, participants perceived the provision of palliative care for AYAs to be more difficult compared with older adults. Four themes emerged: (1) challenges helping AYAs/families to engage in and accept palliative care, (2) uncertainty regarding how to involve the family, (3) HCP sense of tragedy, and (4) HCP sense of emotional proximity. CONCLUSION: Findings from this study support the development of dedicated training for HCPs involved in palliative care for AYA.
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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 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".