A scoping review examining the association of housing quality and psychosocial well-being following homelessness: an ecological systems perspective
Bibliographic record
Abstract
Housing quality (HQ) has been previously associated with health and quality of life. Although HQ is an important factor in preventing homelessness, little is known about the range and breadth of this body of literature. To identify existing studies, we conducted a scoping review guided by the question: “in what ways has housing quality been associated with psychosocial well-being following homelessness in existing peer-reviewed literature?” using the framework proposed by Arksey & O'Malley and PRISMA-ScR guidelines. Our search was deployed in eight databases. A total of 713 titles and abstracts were screened following the removal of duplicates, and 32 articles were included in narrative synthesis. Six themes emerged from our data analysis of included articles: 1) quality of housing affecting well-being; 2) feeling forced to live in unsafe and poor-quality housing due to no other options; 3) HQ mediated by housing first; 4) determinants of HQ; 5) standardized measures of HQ; and 6) HQ is de-emphasized in research and practice following homelessness. Our findings demonstrate that HQ is associated with psychosocial well-being at micro, meso, exo, and macro systems levels for persons experiencing homelessness. We argue addressing HQ following homelessness is a key homelessness prevention strategy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".