How COVID-19 has impacted access to healthcare and social resources among individuals experiencing homelessness in Canada: a scoping review
Bibliographic record
Abstract
OBJECTIVES: In Canada, individuals experiencing homelessness (IEH) rely on public health and social services for healthcare, food and basic necessities. The COVID-19 pandemic has disproportionately affected marginalised populations, in part by impacting their access to such services. We performed a scoping review to identify from the published literature how access to services has changed for Canadian IEH during the pandemic. DATA SOURCES: OVID Medline, Web of Science, Sociological Abstracts, CINAHL and OVID EmCare databases, and websites for the Salvation Army, Homeless Hub, Canadian Alliance to End Homelessness, Canadian Network for the Health and Housing of People Experiencing Homelessness and BC Centre for Disease Control. STUDY DESIGN: We used the scoping review methodology developed by the Joanna Briggs Institute framework and defined access to healthcare and social services using the 10-component Levesque framework. Academic databases and grey literature searches were used, with the final searches for each taking place 24 May and 1 June 2021, respectively. Data were compiled into an Excel spreadsheet. Title and abstract screening and full-text review were completed by two independent reviewers (RG and MM). Data extraction was completed by MM and cross checked by RG. RESULTS: In total, 17 academic and grey literature articles were included. Positive and negative changes in service access were reported in the literature. During the COVID-19 pandemic, access to social and healthcare resources was generally reduced for Canadian IEH. A new component of access, digital connectivity, was identified. Unexpectedly, coordination and collaboration of services improved, as did the number of outreach services. CONCLUSIONS: Positive changes to service access such as improved coordination of services should be scaled up. Further work should be done to improve access to digital technologies for IEH.
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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 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.018 | 0.035 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.003 |
| 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".