Challenges faced by people experiencing homelessness and their providers during the COVID-19 pandemic: a qualitative study
Bibliographic record
Abstract
BACKGROUND: People experiencing homelessness are vulnerable to SARS-CoV-2 infection and its consequences. We aimed to understand the perspectives of people experiencing homelessness, and of the health care and shelter workers who cared for them, during the COVID-19 pandemic. METHODS: We conducted an interpretivist qualitative study in Toronto, Canada, from December 2020 to June 2021. Participants were people experiencing homelessness who received SARS-CoV-2 testing, health care workers and homeless shelter staff. We recruited participants via email, telephone or recruitment flyers. Using individual interviews conducted via telephone or video call, we explored the experiences of people who were homeless during the pandemic, their interaction with shelter and health care settings, and related system challenges. We analyzed the data using reflexive thematic analysis. RESULTS: Among 26 participants were 11 men experiencing homelessness (aged 28-68 yr), 9 health care workers (aged 33-59 yr), 4 health care leaders (aged 37-60 yr) and 2 shelter managers (aged 47-57 yr). We generated 3 main themes: navigating the unknown, wherein participants grappled with evolving public health guidelines that did not adequately account for homeless individuals; confronting placelessness, as people experiencing homelessness often had nowhere to go owing to public closures and lack of isolation options; and struggling with powerlessness, since people experiencing homelessness lacked agency in their placelessness, and health care and shelter workers lacked control in the care they could provide. INTERPRETATION: Reduced shelter capacity, public closures and lack of isolation options during the COVID-19 pandemic exacerbated the displacement of people experiencing homelessness and led to moral distress among providers. Planning for future pandemics must account for the unique needs of those experiencing homelessness.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| 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".