Knowledge, attitudes and practice questionnaires in dengue, Zika, chikungunya and yellow fever settings: a scoping review protocol
Bibliographic record
Abstract
Introduction Arboviruses are a broad classification of viral pathogens that require vectors such as mosquitoes for infection transmission. The burden of arboviral diseases worldwide is substantial, affecting millions of people annually, with the Aedes aegypti mosquito responsible for spreading several common arboviruses, including dengue, chikungunya, Zika and yellow fever. One public health strategy to control and prevent these viruses is to influence community members’ behaviours related to reducing the breeding sites of Aedes mosquitoes, and knowledge, attitudes and practice (KAP) questionnaires are often used as part of these education campaigns. Objectives To explore the content of KAP questionnaires and methodologies used to evaluate arboviral infections, focusing on dengue, Zika, chikungunya and yellow fever. Methods and analysis To identify and describe KAP questionnaires for the selected arboviral infections, a scoping review will be performed and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Scoping Review Extension guidelines. Scientific databases such as MEDLINE, Cochrane, EMBASE, Web of Science, Scielo and LILACS will be searched systematically. Two independent reviewers will screen the title and abstract, followed by a full-text review of the selected articles using the COVIDENCE platform. The extracted information will include citation details, the type of arbovirus, the type of questions in each domain, the scoring system, the theoretical framework and the statistical analysis. The results will be presented comprehensively in tables and figures. Ethics and dissemination Ethics approval is not required. Knowledge transfer will be conducted through conference presentations and publications.
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 | 0.084 | 0.066 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.016 | 0.015 |
| Bibliometrics | 0.017 | 0.012 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.075 | 0.012 |
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".