When does evidence from clinical trials influence health policy? A qualitative study of officials in nine African countries of the factors behind the HIV policy decision to adopt Option B+
Bibliographic record
Abstract
Introduction The appropriate role of evidence in health policy decision making is controversial and requires more data on how decisions are actually made. Option B+ is a strategy to prevent mother to child transmission (PMTCT) of HIV that involves starting pregnant, HIV-positive women on triple drug antiretroviral therapy (ART) and continuing for life. It was rapidly adopted by sub-Saharan African countries with limited scientific evidence for its efficacy and safety, without waiting for the results from an ongoing randomised controlled trial (RCT) comparing PMTCT strategies. Methods We interviewed 14 senior HIV policymakers in nine sub-Saharan African countries about factors influencing their adoption of Option B+. Results While scientific evidence was important to the decision to adopt Option B+, policymakers were persuaded by data that did not come from RCTs. Other factors also played an important role including: evidence for ancillary benefits, simplicity, alignment with other values and priorities, and ease of integration with existing programmes. Conclusions In adopting Option B+, gold-standard scientific evidence played a relatively minor role; other considerations were more important. Future research could help researchers determine whether these factors are influential in other contexts and to develop evidence that is more responsive to the needs of policymakers.
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How this classification was reachedexpand
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 | 0.014 | 0.213 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".