Voices unheard: End-of-life experiences of Québec's English-speaking informal caregivers
Bibliographic record
Abstract
Informal caregivers (e.g., a spouse, adult child, or friend) are pivotal in assisting individuals who face health challenges including end-of-life (EOL) decisions and care. Effective communication among all involved is essential for optimal EOL-related care processes and outcomes. In Québec, English-speaking patients, and caregivers, being a linguistic minority, can encounter unique challenges due to possible language barriers . Caregiver EOL experiences in this context require further exploration.This qualitative study begins to explore EOL experiences among informal caregivers (N = 16) of a language minority group (English) in Québec, Canada where the majority is French speaking. Informal caregivers were conveniently recruited from the Community Health and Social Services Network (CHSSN), Senior wellness centers in various regions around Québec, and Hope & Cope – a volunteer community organization. Inclusion criteria were being at least 18 years old, having access to a phone or computer with Zoom capabilities, self-identifying as English-speaker and being a primary caregiver for someone who died by either MAiD, PSUD, or natural death within the past 5 years. Individual semi- structured (virtual) interviews were conducted with participants and lasted between 60 and 90 minutes. These were transcribed verbatim, and narratives were examined using interpretive description. Findings were structured using the Comprehensive Cancer Experience Measurement Framework, covering four domains. (1) Individual (internal) caregiver experiences: Overall, participants reported needing detailed information about EOL care and facing internal challenges such role conflict, feelings of guilt, and diverse opinions towards EOL decisions. (2) Caregiver-patient shared experiences: Participants emphasized how important shared decision-making was regarding care and death location and the patient’s dependence on the caregiver. (3) Caregiver-family shared experiences: Participants highlighted degrees of family involvement in EOL decisions and support needed from family members other than the primary caregiver, especially while providing care at home. (4) Caregiver-health care system interactions: The fourth domain was the most salient, namely how goal-concordant care (i.e., aligning professional care with patients/caregivers’ goals, beliefs, and values) was construed as key in optimizing the EOL experience and its outcomes. Language barriers further challenged coming to terms with goal-concordant care. Taken together, these findings provide a deeper understanding of participants’ experiences caring for someone through the EOL process and beyond
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".