Barriers to End-of-Life Services for Persons Experiencing Homelessness as Perceived by Health and Social Service Providers
Bibliographic record
Abstract
BACKGROUND: People experiencing homelessness have significantly shorter life expectancies and higher rates of morbidity and mortality than the general population. Many barriers have been identified to providing palliative care to this population. This study examines health and social service providers' experiences providing end-of-life care to people experiencing homelessness, seeking recommendations to improve both patient and provider experience. METHODS: Qualitative study using phenomenological approach. Qualitative and quantitative surveys with 136 health and social service providers in Ontario's South East Local Health Integration Network, in-depth interview with 10 key informants. FINDINGS: Participants approached the end-of-life care of people experiencing homelessness from a framework of dignity and respect. Themes included barriers to end-of-life care internal to the health care system; care avoidance; the experience of stigma for this population when accessing end-of-life care; lack of provider information and awareness on how to provide care for marginalized groups, how to provide care in the context of substance use, and how to assist clients in accessing the formal palliative care system; and the need for harm reduction approaches to end-of-life care for persons experiencing homelessness. DISCUSSION: Focusing on harm reduction, and using the framework of Equity-Oriented Health Care to make systemic, cultural, and policy changes to develop a palliative-care system for persons experiencing homelessness may improve care experience for both patients and providers.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".