The SARS-CoV-2 Vaccine Hesitancy Among the General Population: A Large Cross-Sectional Study From Kuwait
Bibliographic record
Abstract
Although the approved COVID-19 vaccines have proven to be safe and effective, multiple beliefs and misconceptions still exist influencing the vaccine uptake rates around the world. The multifaceted complex phenomenon of vaccine hesitancy could jeopardize the efforts to overcome this pandemic. The aim of this study is to identify the prevalence and examine the factors associated with vaccine hesitancy in Kuwait. This is a web-based cross-sectional study conducted in Kuwait from March 2021 until April 2021, during the second wave of the COVID-19 pandemic. Our questionnaire examined basic demographic information, attitudes towards the COVID-19 vaccines as well as reasons for and against accepting the vaccine. Out of the 2345 responders, the majority are fully convinced to take the vaccine (83%) and the rate of vaccine hesitancy is 17%. Vaccine hesitancy is higher among non-healthcare workers, those previously positive for the COVID-19 virus, and those against vaccines in general. Vaccine hesitancy could jeopardize the efforts to overcome this pandemic; therefore, intensifying nationwide education and dismissal of falsified information is an essential step towards addressing vaccine hesitancy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.000 |
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 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".