Prioritizing Patient Perspectives When Designing Intervention Studies for Homeless Older Adults
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
Purpose: Medical respite provides postacute care to people experiencing homelessness upon hospital discharge if they are too sick to recover on the streets or in a traditional shelter. The current study examined the feasibility of conducting a study to test the effectiveness of a medical respite intervention for older people experiencing homelessness. Methods: Fifteen patient and 11 provider participants were interviewed between July and November 2018. Results: Participants’ considerations for how to design a program of research included (1) desired qualities of researchers; (2) preferences for study design; (3) mechanisms for participant recruitment and retention; (4) what, where, and how to collect data; and (5) barriers and motivations to participation. Conclusions: Findings from this study build on an emerging research base on how to appropriately engage vulnerable patient groups, including older people experiencing homelessness, in trauma-informed research by including peer researchers on research teams to serve as advisors throughout the research process.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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