Attitudes towards smoking and COVID-19, and changes insmoking behaviors before and after the outbreak of COVID-19:A nationwide cross-sectional survey study in China
Bibliographic record
Abstract
INTRODUCTION: China has more than 300 million current smokers. There is a controversy over smokers' risk of COVID-19 infection. Smoking is a risk factor for COVID-19 disease progression, and the outbreak of COVID-19 may change people's smoking behaviors. This study assessed people's attitudes towards 'smoking and COVID-19' and changes of smoking behaviors before and after the outbreak of COVID-19. METHODS: A cross-sectional web survey of 11009 adults in China was conducted between 7 May and 3 August 2020. Attitudes towards 'smoking and COVID-19' were compared among non-smokers (n=8837), ex-smokers (n=399) and current smokers (n=1773), and changes in smoking behaviors before and after the outbreak of COVID-19 were assessed among current smokers. RESULTS: Fewer current smokers (26.2%) agreed with the statement that 'Current smokers are more likely than ex-smokers or non-smokers to contract COVID-19' compared with non-smokers (53%) or ex-smokers (41.4%); fewer current smokers (55.9%) agreed with the statement 'If contracted, current smokers are more likely than ex-smokers or non-smokers to risk disease progression' compared with non-smokers (75.5%) or ex-smokers (68.7%). There were no changes in cigarettes smoked per day (mean ± SD: 13.3 ± 9.55 vs 13.4 ± 9.69, p=0.414), percentage of daily smokers (70.8% vs 71.1%, p=0.882) and percentage of smokers with motivation to quit (intend to quit within the next 6 months, 9.4% vs 10.9%, p=0.148) before and after the outbreak of COVID-19. CONCLUSIONS: The survey found that fewer current smokers agreed that smoking is a risk-factor for COVID-19 compared with non-smokers or ex-smokers. Among current smokers, there were no changes in their cigarette consumption and motivation to quit before and after the outbreak of COVID-19. More efforts are needed to educate smokers about the health risks of smoking, as well as efforts to promote their motivation to quit.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".