Providing Housing First services for an underserved population during the early wave of the COVID-19 pandemic: A qualitative study
Bibliographic record
Abstract
OBJECTIVE: We assessed the critical role of Housing First (HF) programs and frontline workers in responding to challenges faced during the first wave of the COVID-19 pandemic. METHOD: Semi-structured interviews were conducted with nine HF frontline workers from three HF programs between May 2020 and July 2020, in Toronto, Canada. Information was collected on challenges and adjustments needed to provide services to HF clients (people experiencing homelessness and mental disorders). We applied the Analytical Framework method and thematic analysis to our data. RESULTS: Inability to provide in-person support and socializing activities, barriers to appropriate mental health assessments, and limited virtual communication due to clients' lack of access to digital devices were among the most salient challenges that HF frontline workers reported during the COVID-19 pandemic. Implementing virtual support services, provision of urgent in-office or in-field support, distributing food aid, connecting clients with online healthcare services, increasing harm reduction education and referral, and meeting urgent housing needs were some of the strategies implemented by HF frontline workers to support the complex needs of their clients during the pandemic. HF frontline workers experienced workload burden, job insecurity and mental health problems (e.g. distress, worry, anxiety) as a consequence of their services during the first wave of the COVID-19 pandemic. CONCLUSION: Despite the several work-, programming- and structural-related challenges experienced by HF frontline workers when responding to the needs of their clients during the first wave of the COVID-19 pandemic, they played a critical role in meeting the communication, food, housing and health needs of their clients during the pandemic, even when it negatively affected their well-being. A more coordinated, integrated, innovative, sustainable, effective and well-funded support response is required to meet the intersecting and complex social, housing, health and financial needs of underserved and socio-economically excluded groups during and beyond health emergencies.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".