The attitudes of brain cancer patients and their caregivers towards death and dying: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Much money and energy has been spent on the study of the molecular biology of malignant brain tumours. However, little attention has been paid to the wishes of patients afflicted with these incurable tumours, and how this might influence treatment considerations. METHODS: We interviewed 29 individuals - 7 patients dying of a malignant brain tumor and 22 loved ones. One-on-one interviews were conducted according to a pre-designed interview guide. A combination of open-ended questions, as well as clinical scenarios was presented to participants in order to understand what is meaningful and valuable to them when determining treatment options and management approaches. The results were analyzed, coded, and interpreted using qualitative analytic techniques in order to arrive at several common overarching themes. RESULTS: Seven major themes were identified. In general, respondents were united in viewing brain cancer as unique amongst malignancies, due in large part to the premium placed on mental competence and cognitive functioning. Importantly, participants found their experiences, however difficult, led to the discovery of inner strength and resilience. Responses were usually framed within an interpersonal context, and participants were generally grateful for the opportunity to speak about their experiences. Attitudes towards religion, spirituality, and euthanasia were also probed. CONCLUSION: Several important themes underlie the experiences of brain cancer patients and their caregivers. It is important to consider these when managing these patients and to respect not only their autonomy but also the complex interpersonal toll that a malignant diagnosis can have.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".