Bangladesh policy on prevention and control of non-communicable diseases: a policy analysis
Bibliographic record
Abstract
BACKGROUND: This paper is aimed at critically assessing the extent to which Non-Communicable Disease NCD-related policies introduced in Bangladesh align with the World Health Organization's (WHO) 2013-2020 Action Plan for the Global Strategy for the Prevention and Control of NCDs. METHODS: The authors reviewed all relevant policy documents introduced by the Government of Bangladesh since its independence in 1971. The literature review targeted scientific and grey literature documents involving internet-based search, and expert consultation and snowballing to identify relevant policy documents. Information was extracted from the documents using a specific matrix, mapping each document against the six objectives of the WHO 2013-2020 Action Plan for the Global Strategy for the Prevention and Control of NCDs. RESULTS: A total of 51 documents were identified. Seven (14%) were research and/or surveys, nine were on established policies (17%), while seventeen (33%) were on action programmes. Five (10%) were related to guidelines and thirteen (25%) were strategic planning documents from government and non-government agencies/institutes. The study covered documents produced by the Government of Bangladesh as well as those by quasi-government and non-government organizations irrespective of the extent to which the intended policies were implemented. CONCLUSIONS: The policy analysis findings suggest that although the government has initiated many NCD-related policies or programs, they lacked proper planning, implementation and monitoring. Consequently, Bangladesh over the years had little success in effectively addressing the growing burden of non-communicable diseases. It is imperative that future research critically assess the effectiveness of national NCD policies by monitoring their implementation and level of population coverage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.017 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".