Prevalence, risk factors, and interventions for chronic obstructive pulmonary disease in South Asia: a scoping review protocol
Bibliographic record
Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is increasingly contributing to the disease burden in South Asia. This review will summarize the prevalence and risk factors of COPD in South Asia and the interventions regarding COPD that have been introduced in South Asian countries. METHOD: This scoping review will primarily follow Arksey and O'Malley's six steps of scoping review methodology. Additionally, it will follow the recent upgradation of the scoping review methodology by Levac et al., and the Joanna Briggs Institute. Research questions were already identified at the beginning of the proposed scoping review. Electronic databases will be searched (PubMed, Web of Science, and ProQuest) using search terms. Studies will be screened independently by two reviewers through a two-stage screening process using pre-developed inclusion criteria for this scoping review. Eligible studies will be abstracted and charted in a standardised form. Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) will be used to report the result. Additionally, feedback from South Asia's experienced COPD researchers on the final literature list will be collected for gap identification in literature search. Two independent reviewers will assess the quality of each included study's design using the Joanna Briggs Institute's tool. DISCUSSION: The proposed scoping review will map the evidence on COPD in South Asia through literature review, and it will focus on prevalence, risk factors, and interventions. This review will contribute to the advancement of research on COPD and will be beneficial for policy-makers, public health specialists, and clinicians.
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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 | 0.132 | 0.085 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.083 | 0.022 |
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".