Exploring End-of-Life Perspectives in Structurally Vulnerable Populations: A Qualitative Focus Group Study
Bibliographic record
Abstract
BackgroundPalliative care is a key component of the healthcare system, yet structurally vulnerable populations face significant barriers to accessing it and its support in care planning. This study explored beliefs, needs, and concerns related to palliative care and advance care planning among these populations.MethodsTwo semi-structured focus groups were conducted in major cities in the province of Quebec, Canada, in May and August of 2022. Participants had to be at least 18 years old and be able to speak and understand French. They also had to attend or use the services of a partnered community organization serving the target population. Data was analyzed according to the thematic content analysis approach.ResultsFifteen (15) persons participated: all were Caucasian, and most were women, born before 1960, single, and retired. Misconceptions and a lack of awareness of the various palliative care options were generally observed among participants. Experience with caring for a dying person, access to a family physician, and access to a legal professional were identified as elements promoting awareness of palliative care. Participants raised an urgent need for more accessible information about palliative care and advance care planning, and for more access to care.ConclusionsA good understanding of palliative care options helps individuals and families make informed decisions and be better prepared for the end of life. Structurally vulnerable people urgently need accessible information to support this preparation. This study supports the development of equity-focused policies and tailored interventions to improve access and planning for this population.
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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 | 0.015 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".