Front-Line Insights Into the Social Determinants of Health in Housing Instability: A Multi-Province Study
Bibliographic record
Abstract
INTRODUCTION: Individuals experiencing housing instability face significant health inequities. Addressing housing instability requires an understanding of the factors that contribute to these inequities-a responsibility that has been assumed by community-based organizations. Interviewing individuals from 3 Canadian provinces, the present study aimed to examine the perspectives of individuals from front-line services of the social determinants of health (SDoH) needs of individuals experiencing housing instability. METHODS: As part of a larger knowledge translation study, we conducted 8 semi-structured interviews with individuals from front-line services (eg, shelter workers and shelter mental health nurses) in Canada (Nova Scotia, Saskatchewan, and Alberta) and used thematic analysis to identify predominant unmet SDoH needs. RESULTS: Individuals from front-line services discussed the roles of many SDoH that may perpetuate housing instability in their clients. These included: (1) limited social supports; (2) poor access to health services; (3) poor opportunities for income and employment; (4) lack of transportation; (5) gender-based discrimination; (6) race-based discrimination; and (7) limited access to education and limited literacy skills. CONCLUSION: This study reveals how front-line service providers observe SDoH factors contributing to housing instability and create barriers to accessing support services. They advocate for a multi-system approach to addressing intersecting SDoH factors to validate clients' experiences and help them achieve stable housing. Additionally, more research and consultation with front-line providers are necessary to understand and overcome systemic barriers to stable housing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".