The Hotel Study: Multimorbidity in a Community Sample Living in Marginal Housing
Bibliographic record
Abstract
OBJECTIVE: The health of people living in marginal housing is not well characterized, particularly from the perspective of multimorbid illness. The authors investigated this population in a community sample. METHOD: A prospective community sample (N=293) of adults living in single-room occupancy hotels was followed for a median of 23.7 months. Assessment included psychiatric and neurological evaluation, multimodal MRI, and viral testing. RESULTS: Previous homelessness was described in 66.6% of participants. Fifteen deaths occurred during 552 person-years of follow-up. The standardized mortality ratio was 4.83 (95% CI=2.91-8.01). Substance dependence was ubiquitous (95.2%), with 61.7% injection drug use. Psychosis was the most common mental illness (47.4%). A neurological disorder was present in 45.8% of participants, with definite MRI findings in 28.0%. HIV serology was positive in 18.4% of participants, and hepatitis C virus serology in 70.3%. The median number of multimorbid illnesses (from a list of 12) was three. Burden of multimorbidity was significantly correlated with lower role functioning score. Comorbid addiction or physical illness significantly decreased the likelihood of treatment for psychosis but not the likelihood of treatment for opioid dependence or HIV disease. Participants who died during follow-up appeared to have profiles of multimorbidity similar to those of the overall sample. CONCLUSIONS: This marginally housed cohort had greater than expected mortality and high levels of multimorbidity with adverse associations with role function and likelihood of treatment for psychosis. These findings may guide the development of effective health care delivery in the setting of marginal housing.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".