The Impact of Financial Incentives on Service Engagement Among Adults Experiencing Homelessness and Mental Illness: A Pragmatic Trial Protocol
Bibliographic record
Abstract
Background: People experiencing homelessness and mental illness have poorer service engagement and health-related outcomes compared to the general population. Financial incentives have been associated with increased service engagement, but evidence of effectiveness is limited. This protocol evaluates the acceptability and impact of financial incentives on service engagement among adults experiencing homelessness and mental illness in Toronto, Canada. Methods: This study protocol uses a pragmatic field trial design and mixed methods ( ClinicalTrials.gov Identifier: NCT03770221). Study participants were recruited from a brief multidisciplinary case management program for adults experiencing homelessness and mental illness following hospital discharge, and were randomly assigned to usual care or a financial incentives arm offering $20 for each week they attended meetings with a program provider. The primary outcome of effectiveness is service engagement, measured by the count of participant-provider health-care contacts over the 6-month period post-randomization. Secondary health, health service use, quality of life, and housing outcomes were measured at baseline and at 6-month follow-up. Quantitative data will be analyzed using descriptive statistics and inferential modeling including Poisson regression and generalized estimating equations. A subset of study participants and other key informants participated in interviews, and program staff in focus groups, to explore experiences with and perspectives regarding financial incentives. Qualitative data will be rigorously coded and thematically analyzed. Conclusions: Findings from this study will contribute high quality evidence to an underdeveloped literature base on the effectiveness and acceptability of financial incentives to improve service engagement and health-related outcomes among adults experiencing homelessness and 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 | 0.070 | 0.071 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.066 | 0.008 |
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".