The ENRICH study to evaluate the effectiveness of a combination intervention package to improve isoniazid preventive therapy initiation, adherence and completion among people living with HIV in Ethiopia: Rationale and design of a mixed methods cluster randomized trial
Bibliographic record
Abstract
BACKGROUND: Isoniazid preventive therapy (IPT) prevents tuberculosis among HIV-positive individuals, however implementation is suboptimal. Implementation science studies are needed to identify interventions to address this evidence-to-program gap. OBJECTIVE: The ENRICH Study is a mixed methods cluster randomized trial aimed at evaluating the effectiveness and acceptability of a combination intervention package (CIP) to improve IPT implementation in Ethiopia. DESIGN: Ten health centers were randomized to receive the CIP or standard of care. The CIP includes: nurse training and mentorship using a clinical algorithm, tool to identify IPT-eligible family members, and data review at multidisciplinary team meetings; patient transport reimbursement; and adherence support using peer educators and interactive voice response messages. Routine data were abstracted for all newly-enrolled IPT-eligible HIV-positive patients; anticipated sample size was 1400 individuals. A measurement cohort of patients initiating IPT was recruited; target enrollment was 500 individuals, to be followed for the duration of IPT (6-9 months). Inclusion criteria were: HIV-positive; initiated IPT; age ≥18; Amharic-, Oromiffa-, Harari-, or Somali-speaking; and capable of informed consent. Three groups were recruited from CIP health centers for in-depth interviews: IPT initiators; IPT non-initiators; and health care providers. Primary outcomes are: IPT initiation; and IPT completion. Secondary outcomes include: retention; adherence; change in CD4+ count; adverse events; and acceptability. Follow-up is complete. DISCUSSION: The ENRICH Study evaluates a CIP targeting barriers to IPT implementation. If the CIP is found effective and acceptable, this study has the potential to inform TB prevention strategies for HIV patients in resource-limited countries in sub-Saharan Africa.
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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 | 0.026 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".