Exposure to Negative News Stories About Vaping, and Harm Perceptions of Vaping, Among Youth in England, Canada, and the United States Before and After the Outbreak of E-cigarette or Vaping-Associated Lung Injury (‘EVALI’)
Bibliographic record
Abstract
INTRODUCTION: Little is known about the international impact of E-cigarette or Vaping-Associated Lung Injury ('EVALI') on youth perceptions of vaping harms. METHODS: Repeat cross-sectional online surveys of youth aged 16-19 years in England, Canada, and the United States before (2017, 2018), during (2019 August/September), and after (2020 February/March, 2020 August) the 'EVALI' outbreak (N = 63380). Logistic regressions assessed trends, country differences, and associations between exposure to negative news stories about vaping and vaping harm perceptions. RESULTS: Exposure to negative news stories increased between 2017 and February-March 2020 in England (12.6% to 34.2%), Canada (16.7% to 56.9%), and the United States (18.0% to 64.6%), accelerating during (2019) and immediately after (February-March 2020) the outbreak (p < .001) before returning to 2019 levels by August 2020. Similarly, the accurate perception that vaping is less harmful than smoking declined between 2017 and February-March 2020 in England (77.3% to 62.2%), Canada (66.3% to 43.3%), and the United States (61.3% to 34.0%), again accelerating during and immediately after the outbreak (p < .001). The perception that vaping takes less than a year to harm users' health and worry that vaping will damage health also doubled over this period (p ≤ .001). Time trends were most pronounced in the United States. Exposure to negative news stories predicted the perception that vaping takes less than a year to harm health (Adjusted Odds Ratio = 1.55, 1.48-1.61) and worry that vaping will damage health (Adjusted Odds Ratio = 1.32, 1.18-1.48). CONCLUSIONS: Between 2017 and February-March 2020, youth exposure to negative news stories, and perceptions of vaping harms, increased, and increases were exacerbated during and immediately after 'EVALI'. Effects were seen in all countries but were most pronounced in the United States. IMPLICATIONS: This is the first study examining changes in exposure to news stories about vaping, and perceptions of vaping harms, among youth in England, Canada, and the United States before, during, and after 'EVALI'. Between 2017 and February-March 2020, youth exposure to negative news stories, and perceptions of vaping harms, increased, and increases were exacerbated during and immediately after 'EVALI'. By August 2020, exposure to negative news stories returned to 2019 levels, while perceptions of harm were sustained. Exposure to negative news stories also predicted two of the three harm perception measures. Overall, findings suggest that 'EVALI' may have exacerbated youth's perceptions of vaping harms internationally.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".