Recovery education for people experiencing housing instability: An evaluation protocol
Bibliographic record
Abstract
Background:Recovery education centers (RECs) offer recovery supports through education rather than traditional health services. The Supporting Transitions and Recovery Learning Centre (STAR) in Toronto, Canada, is among the few that are internationally focused on individuals with histories of homelessness. Although research suggests that RECs positively impact participants, there is a paucity of rigorous studies and none address the engagement and impacts on homeless individuals.Aims:This protocol describes a realist-informed evaluation of STAR, specifically examining (1) if STAR participation is more effective in promoting 12-month recovery outcomes than participation in usual services for individuals experiencing housing instability and mental health challenges and (2) how STAR participation promotes recovery and other positive outcomes.Methods:This study uses a quasi-experimental mixed methods design. Personal empowerment (primary outcome) and recovery, housing stability, social functioning, health service use and quality of life (secondary outcomes) data were collected at baseline, and 6 and 12 months. Intervention group participants were recruited at the time of STAR registration while control group participants were recruited from community agencies serving this population after screening for age and histories of housing instability. Interviews and focus groups with service users and providers will identify the key intervention ingredients that support the process of recovery.Results:From January 2017 to July 2018, 92 individuals were recruited to each of the intervention and control groups. The groups were mostly similar at baseline; the intervention group’s total empowerment score was slightly higher than the control group’s (M (SD): 2.94 (0.23) vs 2.84 (0.28), p = .02), and so was the level of education. A subset of STAR participants (n = 20) and nine service providers participated in the qualitative interviews and focus groups.Conclusion:This study will offer important new insights into the effectiveness of RECs, and expose how key REC ingredients support the process of recovery for people experiencing housing instability.
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 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 | 0.083 | 0.041 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.039 | 0.006 |
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".