Knowledge, attitudes, and practices toward COVID-19 among the general population: a cross-sectional study in Kankan, Guinea
Bibliographic record
Abstract
Background: Implementing decisive and effective infection prevention and control measures necessitates a thorough grasp of the general population's level of knowledge in order to identify existing gaps and react appropriately. Objective: The goal of this cross-sectional research was to assess public knowledge, attitudes, and practices (KAP) about COVID-19 in Kankan Guinea, in order to better understand the socio-demographic factors that are associated with poor KAP. Materials and Methods: The study population consists of 1230 people who reside in five health districts in the Kankan region. An anonymous paper-based questionnaire, given face-toface by trained field agents, was used to gather data. Results: The research included 1230 Guineans in total. The bulk of respondents (60%) were familiar with COVID-19. Only 44% of respondents under the age of 29 had a clear understanding of COVID-19. Male participants knew more about COVID-19 than female ones (P=0.003). The majority of participants (82%) had negative attitudes toward COVID-19, while 61% reported positive practices linked to COVID-19 measures. In this research, being female was a risk factor for poor knowledge of COVID-19 (P0,001), and being single was a risk factor for negative attitudes toward COVID-19 (P=0,009). Conclusion: Appropriate measures should be taken to increase public awareness and improve general practice of preventive measures aimed at reducing the spread of infectious diseases such as COVID-19.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".