Translating research into policy and practice in developing countries: a case study of magnesium sulphate for pre-eclampsia
Bibliographic record
Abstract
BACKGROUND: The evidence base for improving reproductive health continues to grow. However, concerns remain that the translation of this evidence into appropriate policies is partial and slow. Little is known about the factors affecting the use of evidence by policy makers and clinicians, particularly in developing countries. The objective of this study was to examine the factors that might affect the translation of randomised controlled trial (RCT) findings into policies and practice in developing countries. METHODS: The recent publication of an important RCT on the use of magnesium sulphate to treat pre-eclampsia provided an opportunity to explore how research findings might be translated into policy. A range of research methods, including a survey, group interview and observations with RCT collaborators and a survey of WHO drug information officers, regulatory officials and obstetricians in 12 countries, were undertaken to identify barriers and facilitators to knowledge translation. RESULTS: It proved difficult to obtain reliable data regarding the availability and use of commonly used drugs in many countries. The perceived barriers to implementing RCT findings regarding the use of magnesium sulphate for pre-eclampsia include drug licensing and availability; inadequate and poorly implemented clinical guidelines; and lack of political support for policy change. However, there were significant regional and national differences in the importance of specific barriers. CONCLUSION: The policy changes needed to ensure widespread availability and use of magnesium sulphate are variable and complex. Difficulties in obtaining information on availability and use are combined with the wide range of barriers across settings, including a lack of support from policy makers. This makes it difficult to envisage any single intervention strategy that might be used to promote the uptake of research findings on magnesium sulphate into policy across the study settings. The publication of important trials may therefore not have the impacts on health care that researchers hope for.
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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 | 0.013 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".