Bibliographic record
Abstract
148 Background: Palliative Medicine consultation is greater for cancer than non-cancer patients. Decreased symptom burden, improved survival time and quality of life, and cost savings are associated with palliative care. Most patients do not receive information about palliative care until end of life, resulting in negative outcomes. We examined perceptions and access to Palliative Medicine for persons living with advanced illnesses. The purpose was to inform the design of palliative care pathways for cancer and non-cancer diagnoses. Methods: Using Interpretive Phenomenological Analysis, patients/caregivers with metastatic cancer, chronic kidney disease, chronic obstructive pulmonary disease and advanced heart failure were interviewed. This qualitative research method explores an individual’s lived illness experience. Interviews addressed care processes, teams, understanding of palliative care and goals of care. Six reviewers read, coded, categorized interview transcripts and extracted themes. Results: Fifty interviews were completed, 36/50 with metastatic cancer or COPD. Despite different diagnoses, themes were similar. Caregiver’s responses reflected the patient’s burden and overall experience. Themes were: focused individual care; multiple dimensions of time; 24/7 home care; physical and psychological impacts; and spirituality. Perceptions about Palliative Medicine remain aligned with end of life. Conclusions: Palliative Medicine remains associated with end of life, regardless of the diagnosis. Majority had limited access to palliative care, despite pursuing information on supportive services. They also expressed high expectations of receiving such information from physicians and other providers. Results are similar to national strategies on palliative care. The project’s findings have informed the design of clinical pathways for early integration of Palliative Medicine for patients with cancer and non-cancer diagnoses.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".