THE EFFECT OF SOCIAL SUPPORT ON HOUSING STABILITY AMONG PSYCHIATRIC CONSUMER SURVIVORS
Bibliographic record
Abstract
Mental illnesses have a huge burden on individuals, families and society as a whole. Individuals with mental illness can experience an increase in housing instability (number of moves, number of undesirable moves and number of nights homeless). This problem creates a financial strain on the economy as well as on the individuals and families involved. This secondary analysis was carried out with 3 main goals: (1) to determine the relationship between overall support and housing instability, (2) to determine the relationship between social and family relations to housing instability, and (3) to compare the relationship between social and family relations of men and women. Data were collected through the Demographic Questionnaire, the Colorado Client Assessment Record (CCAR), the Lehman Quality of Life (QOL) (brief version) questionnaire, and the Housing History Survey (HHS) from 846 psychiatric consumer/survivors in a city in Southwestern Ontario. Correlational analyses supported an overall significant relationship between social and family relations and housing instability, however, family relations and numbers of nights homeless were not significantly related. Differences for both men and women were examined. Results indicate that having a strong level of family support greatly reduces the number of moves and number of undesirable moves for men. Women on the other hand, relied on their social networks of friends to reduce the number of nights they spent homeless. Implications for nursing practice and future directions for housing stability call for nurses to advocate at the systems level for increased income and affordable housing for individuals with a mental illness.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".