Needs of cancer patients in palliative care during medical visits: Qualitative study.
Bibliographic record
Abstract
OBJECTIVE: To explore the needs of cancer patients in palliative care and to determine how care providers, including family physicians, could meet these needs more fully. DESIGN: Qualitative study performed using semistructured interviews. SETTING: Palliative care departments (ambulatory and intrahospital). PARTICIPANTS: Twelve patients with a diagnosis of cancer deemed to be in the palliative phase, who had already received either chemotherapy or radiation treatment. METHODS: The interviews were recorded and transcribed. They were then coded and categorized to identify and define themes describing the participants' experience. Data were collected until new interviews no longer yielded new categories of results. MAIN FINDINGS: Study participants primarily needed the expertise of their physicians, but they also needed reassurance by means of clear information about their disease, its treatment, and the prognosis delivered over the course of patient-physician visits, and by means of various measures that could act as safety nets. Participants needed to be heard without being judged. In terms of follow-up care, the oncology nurse navigator was just as important as the physician and could stand in for him or her to meet most relational needs and share and explain information on the disease. CONCLUSION: Non-family physician specialists cannot meet all of the patients' complex needs; throughout the palliative phase, non-family physician specialists need the support of a family physician and an oncology nurse navigator. Each care provider must be made aware of the patient's needs and ensure that they are met, to the best of his or her ability. Failing to do so might exacerbate the loneliness and anxiety experienced by terminally ill patients.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| 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".