Implementing a national health research for development platform in a low-income country – a review of Malawi’s Health Research Capacity Strengthening Initiative
Bibliographic record
Abstract
BACKGROUND: National health research for development (R4D) platforms in lower income countries (LICs) are few. The Health Research Capacity Strengthening Initiative (HRCSI, 2008-2013) was a national systems-strengthening programme in Malawi involved in national priority setting, decision-making on funding, and health research actor mobilization. METHODS: We adopted a retrospective mixed-methods evaluation approach, starting with information gleaned from reports (HRCSI and Malawian) and databases (HRCSI). A framework of a health research system (actors and components) guided report review and interview guide development. From a list of 173 individuals involved in HRCSI, 30 interviewees were selected within categories of stakeholders. Interviews were conducted face-to-face or via telephone/Skype over 1 month, documented with extensive notes. Analysis of emerging themes was iterative among co-evaluators, with synthesis according to the implementation stage. RESULTS: Major HRCSI outputs included (1) National research priority-setting: through the production of themed background papers by Malawian health researchers and broad consultation, HRCSI led the development of a National Health Research Agenda (2012-2016), widely regarded as one of HRCSI's foremost achievements. (2) Institutional research capacity: there was an overwhelming view that HRCSI had produced a step-change in the number of high calibre scientists in Malawi and in fostering research interest among young Malawians, providing support for around 56 MSc and PhD students, and over 400 undergraduate health-related projects. (3) Knowledge sharing: HRCSI supported research dissemination through national and institutional meetings by sponsoring attendance at conferences and through close relationships with individuals in the print media for disseminating information. (4) Sustainability: From 2011-2013, HRCSI significantly improved research systems, processes and leadership in Malawi, but further strengthening was needed for HRCSI to be effectively integrated into government structures and sustained long-term. Overall, HRCSI carried out many components relevant to a national health research system coordinating platform, and became competent at managing over half of 12 areas of performance for research councils. Debate about its location and challenges to sustainability remain open questions. CONCLUSIONS: More experimentation in the setting-up of national health R4D platforms to promote country 'ownership' is needed, accompanied by evaluation processes that facilitate learning and knowledge exchange of better practices among key actors in health R4D systems.
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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 | 0.274 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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; both teacher heads agree on what is shown here.
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".