Adherence to Isoniazid Prophylaxis in the Homeless
Bibliographic record
Abstract
OBJECTIVES: To test 2 interventions to improve adherence to isoniazid preventive therapy for tuberculosis in homeless adults. We compared (1) biweekly directly observed preventive therapy using a $5 monetary incentive and (2) biweekly directly observed preventive therapy using a peer health adviser, with (3) usual care at the tuberculosis clinic. METHODS: Randomized controlled trial in tuberculosis-infected homeless adults. Outcomes were completion of 6 months of isoniazid treatment and number of months of isoniazid dispensed. RESULTS: A total of 118 subjects were randomized to the 3 arms of the study. Completion in the monetary incentive arm was significantly better than in the peer health adviser arm (P = .01) and the usual care arm (P = .04), by log-rank test. Overall, 19 subjects (44%) in the monetary incentive arm completed preventive therapy compared with 7 (19%) in the peer health adviser arm (P = .02) and 10 (26%) in the usual care arm (P = .11). The median number of months of isoniazid dispensed was 5 in the monetary incentive arm vs 2 months in the peer health adviser arm (P = .005) and 2 months in the usual care arm (P = .04). In multivariate analysis, independent predictors of completion were being in the monetary incentive arm (odds ratio, 2.57; 95% CI, 1.11-5.94) and residence in a hotel or other stable housing at entry into the study vs residence on the street or in a shelter at entry (odds ratio, 2.33; 95% CI, 1.00-5.47). CONCLUSIONS: A $5 biweekly cash incentive improved adherence to tuberculosis preventive therapy compared with a peer intervention or usual care. Living in a hotel or apartment at the start of treatment also predicted the completion of therapy.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".