Recruitment and retention of homeless individuals with mental illness in a housing first intervention study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Homeless individuals with mental illness are challenging to recruit and retain in longitudinal research studies. The present study uses information from the Vancouver site of a Canadian multi-city longitudinal randomized controlled trial on housing first interventions for homeless individuals. We were able to recruit 500 participants and retain large number of homeless individuals with mental illness; 92% of the participants completed the 6-month follow up interview, 84% the 24-month follow up, while 80% completed all follow-up visits of the study. PURPOSE: In this article, we describe the strategies and practices that we considered as critical for successful recruitment and retention or participants in the study. METHODS: We discuss issues pertaining to research staff hiring and training, involvement of peers, relationship building with research participants, and the use of technology and social media, and managing challenging situations in the context of recruitment and retention of marginalized individuals. CONCLUSIONS: Recruitment and retention of homeless participant with mental illness in longitudinal studies is feasible. It requires flexible, unconventional and culturally competent strategies. Longitudinal research projects with vulnerable and hidden populations may benefit from extensive outreach work and collaborative approaches that are based on attitudes of mutual respect, contextual knowledge and trust.
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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 | 0.021 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it