Identifying and characterising health policy and system-relevant documents in Uganda: a scoping review to develop a framework for the development of a one-stop shop
Bibliographic record
Abstract
BACKGROUND: Health policymakers in low- and middle-income countries continue to face difficulties in accessing and using research evidence for decision-making. This study aimed to identify and provide a refined categorisation of the policy documents necessary for building the content of a one-stop shop for documents relevant to health policy and systems in Uganda. The on-line resource is to facilitate timely access to well-packaged evidence for decision-making. METHODS: We conducted a scoping review of Uganda-specific, health policy, and systems-relevant documents produced between 2000 and 2014. Our methods borrowed heavily from the 2005 Arksey and O'Malley approach for scoping reviews and involved five steps, which that include identification of the research question; identification of relevant documents; screening and selection of the documents; charting of the data; and collating, summarising and reporting results. We searched for the documents from websites of relevant government institutions, non-governmental organisations, health professional councils and associations, religious medical bureaus and research networks. We presented the review findings as numerical analyses of the volume and nature of documents and trends over time in the form of tables and charts. RESULTS: We identified a total of 265 documents including policies, strategies, plans, guidelines, rapid response summaries, evidence briefs for policy, and dialogue reports. The top three clusters of national priority areas addressed in the documents were governance, coordination, monitoring and evaluation (28%); disease prevention, mitigation, and control (23%); and health education, promotion, environmental health and nutrition (15%). The least addressed were curative, palliative care, rehabilitative services and health infrastructure, each addressed in three documents (1%), and early childhood development in one document. The volume of documents increased over the past 15 years; however, the distribution of the different document types over time has not been uniform. CONCLUSION: The review findings are necessary for mobilising and packaging the local policy-relevant documents in Uganda in a one-stop shop; where policymakers could easily access them to address pressing questions about the health system and interventions. The different types of available documents and the national priority areas covered provide a good basis for building and organising the content in a meaningful way for the resource.
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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 | 0.221 | 0.445 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.109 | 0.084 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.024 | 0.027 |
| Open science | 0.008 | 0.018 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".