Frontline Healthcare Workers’ Knowledge, Perception and Risk Prevention Practices Regarding COVID-19 in Afghanistan: A Cross-Sectional Study
Bibliographic record
Abstract
(1) Background: As of 13 December 2020, Afghanistan reported around 48,952 confirmed COVID-19 cases and 1960 deaths. Lack of knowledge and perceptions among healthcare workers (HCWs) can pose challenges to disease control. Therefore, targeted, timely assessment of knowledge and perceptions are needed to address practices that might hinder efforts to stop the spreading of COVID-19 in Afghanistan. This study aimed to assess COVID-19-related knowledge, perceptions, and risk prevention practices (KPP) among frontline HCWs in Afghanistan; (2) Methods: A cross-sectional study was conducted with the support of field teams who were deployed in Afghanistan, surveyed from 14 to 22 April 2020 in eight provinces in Afghanistan with varying cumulative incidence of COVID-19 cases. A 28-item KPP survey instrument was adapted from other internationally validated questionnaires related to COVID-19. (3) Results: The survey was conducted among 213 frontline HCWs engaged in screening and treating COVID-19 patients. Survey results indicated that basic awareness of COVID-19 was 100% across all the participants. Knowledge and understanding of COVID-19 transmission, symptoms, incubation period and complications associated with COVID-19 are comprehensive and high (>90%), except available treatment for COVID-19 (84%). HCWs' perceptions towards the prevention and control of COVID-19 were positive. However, only 63% believed that the use of N-95 face masks and disposable and fluid-resistant gowns (76%) could prevent COVID-19 transmission. This survey showed high knowledge and positive perception (72%), and only 48% of frontline HCWs had shown risk prevention practices. Addressing their perceptions and placing additional focus on practices across all health facilities is recommended as a preparedness measure.
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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 | 0.013 | 0.112 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".