Perceptions, knowledge and attitudes of the adult populations towards COVID-19 : A scoping review protocol v1
Bibliographic record
Abstract
Perceptions, knowledge and attitudes of the adult populations towards COVID-19 are key factors in the community transmission of SARS-CoV-2. During outbreaks, populations play a key role in limiting the spread of infectious diseases by adopting preventive measures. In the context of COVID-19 pandemic, identifying the perceptions, knowledge and attitudes of the populations is important to implement appropriate and effective preventive measures that will help to control and stop the spread of COVID-19. This scoping review aims to understand the perceptions, knowledge and attitudes of the adult populations towards COVID-19. We will conduct a comprehensive search of the following electronic databases: MEDLINE-Ovid, EMBASE-Ovid, PsycINFO-Ovid, Web of Science, and CINAHL (EBSCO). The searches will be conducted in English. All study designs will be included in the searches, both qualitative and quantitative. A comprehensive search of the grey literature, including preprints, will also be undertaken through Google Scholar, Semantic Scholar, CADTH Covid-19, Faculty Opinions, Publons and Medrxiv. We will also search the World Health Organization, Centers for Disease Control and Prevention, Center for Infectious Disease Research and Policy websites and any other relevant COVID-19 related websites.
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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 | 0.050 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.073 | 0.010 |
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".