Adolescents’ and Young Adults’ Perceptions of a Pop-Up Aimed at Combating the Spread of E-Cigarette Misinformation on Social Media: Cross-Sectional Survey Study
Bibliographic record
Abstract
Background: Social media is an important source of e-cigarette-related information for adolescents and young adults. However, misinformation is being shared across platforms, which may encourage e-cigarette use. Objective: This study aims to examine adolescent and young adult perceptions of a novel pop-up on social media that provides links to vaping-related health information from credible sources (eg, CDC). Methods: Between December 2023 and March 2024, participants aged 13-24 years (N=5326) completed a web-based cross-sectional survey. Participants were asked to select from 4 positive (eg, useful to share, helpful to check health-related information) and 4 negative or neutral sentiments (eg, usually ignore such notifications, would not trust it) to reflect their perceptions about a mock pop-up that provided a link to e-cigarette-related information on social media. Results: More participants endorsed positive sentiments than negative or neutral sentiments in relation to the pop-up. Specifically, 1078 (20.8%) endorsed two or more positive sentiments, and 690 (13.3%) endorsed two or more negative or neutral sentiments when searching for "vaping" on social media; similarly 913 (17.6%) participants endorsed two or more positive sentiments and 690 (13.3%) endorsed two or more negative or neutral sentiments when viewing e-cigarette-related posts in their feed (all P<.001). Among those who were searching for e-cigarette-related information, participants aged 13-18 years were more likely to endorse at least two positive sentiments compared to those aged 19-24 years (ie, 646, 22.0% vs 423, 19.2%, respectively), those who had never used e-cigarettes compared with those who had ever used them (ie, 674, 23.6% vs 404, 17.3%, respectively), and those who last used e-cigarettes more than 30 days ago compared with those who had used them in the past 30 days (ie, 187, 19.8% vs 217, 15.6%, respectively). Similarly, among participants who viewed e-cigarette-related posts in their feed, those who had never used e-cigarettes were more likely to endorse two or more positive perceptions compared to those who had ever used e-cigarettes (ie, 563, 19.7% vs 350, 15.0%), and those who had last used e-cigarettes more than 30 days ago (ie, 159, 16.9% vs 191, 13.7%) were more likely to endorse two or more positive perceptions compared to those who had used them in the past 30 days (all Ps<.001). Participants who had never used e-cigarettes were also less likely to trust pop-ups, compared to those who had ever used them, whether while searching for e-cigarette-related information on social media or while seeing e-cigarette-related posts in their feed (approximately, 19%vs 24%). There were no significant differences in the endorsement of negative or neutral sentiments. However, participants aged 13-18 years were more likely to ignore such notifications while viewing e-cigarette-related posts in their social media feed compared to those aged 19-24 years (ie, 850, 28.9% vs 563 25%); further, participants who had never used e-cigarettes were less trusting of e-cigarette-related information while searching for vaping or in their feed. Conclusions: Positive perception of a social media pop-up indicates its potential to prevent e-cigarette-related misinformation. Further development of a pop-up requires strategies to better engage and inform adolescents and young adults, specifically younger individuals, as they may be more likely to disregard pop-ups, and older individuals and those who used e-cigarettes in the past 30 days, as they are potentially more dismissive of such information.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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 | 0.000 |
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".