Factors Associated With Protective Mask-Wearing Behavior to Avoid COVID-19 Infection in China: Internet-Based Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: The novel coronavirus disease COVID-19 is likely to spread from person to person in close-contact settings. The Chinese Center for Disease Control and Prevention released a handbook on COVID-19, which introduced health information to the public, specifically related to wearing masks correctly and adopting preventive measures to avoid COVID-19 infection. OBJECTIVE: The aim of this study was to assess the level of mask knowledge, behavior related to mask usage, and major information channels used for obtaining mask- and COVID-19-related information in China. METHODS: An internet-based survey was conducted primarily using DingXiang Doctor WeChat public accounts. The data about mask knowledge and behavior were collected and analyzed. In addition to descriptive statistics, logistic regression was used to analyze significant risk factors contributing to protective mask behavior. RESULTS: Data were collected from a total of 10,304 respondents to the survey. More than half of the respondents were under 30 years old and nearly three-quarters were women. Over 80% of participants had a bachelor's degree or higher, and the largest proportion of respondents (n=4204, 40.80%) were employed as business/service workers. Over half of the study participants were married (n=5302, 51.46%). The findings revealed that 67.49% (6954/10,304) of the participants practiced protective mask behavior; 97.93% (10,091/10,304) believed that wearing masks is an effective protective measure against COVID-19; 96.85% (9979/10,304) chose a mask that has two or more layers of washable, breathable fabric; and 70.57% (7272/10,304) wore the masks correctly. Gender, age, occupation, and education level had significant effects on behavior, whereas marital status and the infection status of family members were not significantly related to mask-wearing behavior. In addition, WeChat public accounts (9227/10,304, 89.55%) were the most prominent source of obtaining health information for Chinese netizens after the outbreak of COVID-19. CONCLUSIONS: This study elucidated that Chinese netizens' protective mask behavior is far lower than their mask-related knowledge. Improved information channels and adequate information on wearing masks are necessary to improve the public's protective mask behavior, particularly among men, the elderly, and people with less education.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".