Translating research into policy: lessons learned from eclampsia treatment and malaria control in three southern African countries
Bibliographic record
Abstract
BACKGROUND: Little is known about the process of knowledge translation in low- and middle-income countries. We studied policymaking processes in Mozambique, South Africa and Zimbabwe to understand the factors affecting the use of research evidence in national policy development, with a particular focus on the findings from randomized control trials (RCTs). We examined two cases: the use of magnesium sulphate (MgSO(4)) in the treatment of eclampsia in pregnancy (a clinical case); and the use of insecticide treated bed nets and indoor residual household spraying for malaria vector control (a public health case). METHODS: We used a qualitative case-study methodology to explore the policy making process. We carried out key informants interviews with a range of research and policy stakeholders in each country, reviewed documents and developed timelines of key events. Using an iterative approach, we undertook a thematic analysis of the data. FINDINGS: Prior experience of particular interventions, local champions, stakeholders and international networks, and the involvement of researchers in policy development were important in knowledge translation for both case studies. Key differences across the two case studies included the nature of the evidence, with clear evidence of efficacy for MgSO(4 )and ongoing debate regarding the efficacy of bed nets compared with spraying; local researcher involvement in international evidence production, which was stronger for MgSO(4 )than for malaria vector control; and a long-standing culture of evidence-based health care within obstetrics. Other differences were the importance of bureaucratic processes for clinical regulatory approval of MgSO(4), and regional networks and political interests for malaria control. In contrast to treatment policies for eclampsia, a diverse group of stakeholders with varied interests, differing in their use and interpretation of evidence, was involved in malaria policy decisions in the three countries. CONCLUSION: Translating research knowledge into policy is a complex and context sensitive process. Researchers aiming to enhance knowledge translation need to be aware of factors influencing the demand for different types of research; interact and work closely with key policy stakeholders, networks and local champions; and acknowledge the roles of important interest groups.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".