The Views of Patients with Brain Cancer about Palliative Care: A Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Palliative care, a specialty aimed at providing optimal care to patients with life-limiting and chronic conditions, has several benefits. Although palliative care is appropriate for neurosurgical conditions, including brain cancer, few studies have examined the views of brain cancer patients about palliative care. We aimed to explore the thoughts of brain cancer patients about palliative care, their opinions about early palliative care, and their preferred care setting. METHODS: Semi-structured interviews and the qualitative research methodologies of grounded theory were used to explore perceptions of palliative care on the part of 39 brain cancer outpatients. RESULTS: Seven overarching actions emerged: ■Patients would prefer to receive palliative care in the home.■Increased time with caregivers and family are the main appeals of home care.■Patients express dissatisfaction with brief and superficial interactions with health care providers.■Patients believe that palliative care can contribute to their emotional well-being.■Patients are open to palliative care if they believe that it will not diminish optimism.■There is a preconceived idea that palliative care is directly linked to active dying, and that supposed link generates fear in some patients.■Patients prefer to be educated about palliative care as an option early in their illness, even if they are fearful of it. CONCLUSIONS: Overall, when educated about the true meaning of palliative care, most patients express interest in accessing palliative care services. Although the level of fear concerning palliative care varies in patients, most recognize the associated benefits.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".