Healthcare Workers’ Knowledge and Perception of the SARS-CoV-2 Omicron Variant: A Multinational Cross-Sectional Study
Bibliographic record
Abstract
In late November 2021, a new SARS-CoV-2 Variant of Concern (VOC) named Omicron (initially named B.1.1.529) was first detected in South Africa. The rapid spread of the SARS-CoV-2 Omicron variant became globally dominant, and the currently available COVID-19 vaccines showed less protection against this variant. This study aimed to investigate healthcare workers’ (HCWs) knowledge and perceptions about the novel SARS-CoV-2 Omicron variant. A cross-sectional anonymous electronic survey concerning the SARS-CoV-2 Omicron variant was conducted among HCWs during the second week of January 2022. The survey instrument was distributed through social media among HCWs to explore awareness (2 items), knowledge (10 items), source of information (1 item), and perceptions (10 items). Respondents who answered ≥80% of the items correctly were considered as having good knowledge and perception. A total of 940 of the 1054 HCW participants completed the survey (response rate: 89.1%); they had a mean age of 31.2 ± 11.2 years, most were doctors (45.7%), and most were from Asia (64.3%). All the participants were aware of the SARS-CoV-2 Omicron variant (100%). Only 36.3% attended lectures/discussions about Omicron and used news media to obtain information. Only a quarter of the HCWs demonstrated good knowledge (24.3%, n = 228) and perception (20.6%) about Omicron. However, while significant differences were observed in the knowledge and perception among HCWs, only a small proportion of doctors exhibited good knowledge (13%) and perception (10%) about the Omicron variant. HCWs who had participated in training/discussion related to the Omicron variant were more likely to have higher knowledge and perception scores (odds ratio: 1.80; 95% confidence interval: 1.04–3.11). As the SARS-CoV-2 Omicron variant spreads rapidly across the globe, ongoing educational interventions are warranted to improve knowledge and perceptions of HCWs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".