The impact of a conditional financial incentive on linkage to HIV care: Findings from the HITS cluster randomized clinical trial in rural South Africa
Bibliographic record
Abstract
Introduction: HIV elimination requires innovative approaches to ensure testing and immediate treatment provision. We investigated the effectiveness of conditional financial incentives on increasing linkage to HIV care in a 2×2 factorial cluster randomized controlled trial-Home-Based Intervention to Test and Start (HITS) - in rural South Africa. Methods: Of 45 communities in uMkhanyakude, KwaZulu-Natal, 16 communities were randomly assigned to the arms to receive financial incentives for home-based HIV counseling and testing (HBHCT) and linkage to care within 6 weeks (R50 [US$3] food voucher each) and 29 communities to the arms without financial incentives. We examined linkage to care (i.e., initiation or resumption of antiretroviral therapy after >3 months of care interruption) at local clinics within 6 weeks of a home visit, the eligibility period to receive the second financial incentive. Linkage to care was ascertained from individual clinical records. Intention-to-treat analysis (ITT) was performed using modified Poisson regression with adjustment for receiving another intervention (i.e., male-targeted HIV-specific decision support app) and clustering of standard errors at the community level. Results: Among 13,894 eligible men (i.e., ≥15 years and resident in the 45 communities), 20.7% received HBHCT, which resulted in 122 HIV-positive tests. Of these, 27 linked to care within 6 weeks of HBHCT. Additionally, of eligible men who did not receive HBHCT, 66 linked to care. In the ITT analysis, the proportion of linkage to care among men did not differ in the arms which received financial incentives and those without financial incentives (adjusted Risk Ratio [aRR]=0.78, 95% CI: 0.51-1.21). Among 19,884 eligible women, 29.1% received HBHCT, which resulted in 375 HIV-positive tests. Of these, 75 linked to care. Among eligible women who did not receive HBHCT, 121 linked to care within 6 weeks. Women in the financial incentive arms had a significantly higher probability of linkage to care, compared to those in the arms without financial incentives (aRR=1.50; 95% CI: 1.03-2.21). Conclusion: While a small once-off financial incentive did not increase linkage to care among men during the eligibility period of 6 weeks, it significantly improved linkage to care among women over the same period. Clinical Trial Number: ClinicalTrials.gov # NCT03757104.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".