Contextual factors related to vector-control interventions for malaria: a scoping review and evidence and gap map protocol
Bibliographic record
Abstract
Objective: This scoping review will identify existing literature regarding contextual factors relevant to vector-control interventions to prevent malaria. We will use the findings of the scoping review to produce an interactive evidence and gap map. The map will assist in the priority setting, development, and conduct of targeted systematic reviews. These systematic reviews seek to assist the Vector Control and Insecticide Resistance Unit of the World Health Organization's Global Malaria Programme by informing recommendation development by their Guidelines Development Group. Introduction: Malaria contributes substantially to the global burden of disease, with an estimated 247 million cases and 619,000 deaths in 2021. Vector-control is key in reducing malaria transmission. Vector-control interventions directly target the mosquito, reducing the potential for parasite infections. These interventions commonly include insecticides used in indoor residual spraying or insecticide-treated nets and larval source management. Several new vector-control interventions are under evaluation to complement these. In addition to estimating the effects of interventions on health outcomes, it is critical to understand how populations at risk of malaria consider them in terms of their feasibility, acceptability, and values. Inclusion Criteria: Eligible studies will have assessed the contextual factors of feasibility or acceptability of the interventions of interest, or the valuation of the outcomes of interests. These assessments will be from the perspective of people who receive (residents) or deliver (workers or technicians) the vector-control intervention for the purpose of preventing malaria. Methods: We will conduct this scoping review in accordance with the JBI methodology for scoping reviews and report in line with the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR). We will construct the evidence and gap map following guidance from the Campbell Collaboration.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
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 | 0.144 | 0.159 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.009 | 0.016 |
| Bibliometrics | 0.037 | 0.024 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.008 | 0.016 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.082 | 0.016 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".