Social Media Exposure and Other Correlates of Increased e-Cigarette Use Among Adolescents During Remote Schooling: Cross-Sectional Study
Bibliographic record
Abstract
Background: Little is known about the role of exposure to e-cigarette-related digital content, behavioral and mental health factors, and social environment on the change in adolescent e-cigarette use during COVID-19 shelter-in-place orders and remote schooling. Objective: The aim of the study was to examine changes in adolescent e-cigarette use during shelter-in-place and remote schooling in association with exposure to e-cigarette-related digital content and other correlates: stronger e-cigarette dependence, feeling lonely, inability to socialize, e-cigarette use to cope with shelter-in-place, and the number of family members aware of participants' e-cigarette use. Methods: A cross-sectional survey conducted between August 2020 and March 2021 included 85 California adolescents (mean age 16.7, SD 1.2 years; 39/85, 46% identified as female and 37/85, 44% as Hispanic) who reported e-cigarette use in the past 30 days. Multivariable penalized logistic regressions determined associations adjusted for age, race and ethnicity, and mother's education. The outcome of increased e-cigarette use was defined as more frequent use of e-cigarettes of the same or stronger nicotine or tetrahydrocannabinol concentration. Results: Almost all respondents (83/85, 98%) reported using social media more since shelter-in-place, and 74% (63/85) reported seeing e-cigarette digital content. More than half (46/85, 54%) reported increased e-cigarette use during shelter-in-place. Most individuals who increased use were exposed to e-cigarette digital content (38/46, 83%) compared to those who did not increase e-cigarette use (25/39, 64%), but the association was nonsignificant after adjusting for demographics (adjusted odds ratio [AOR] 2.34, 95% CI 0.71-8.46). Respondents who felt lonely (AOR 3.33, 95% CI 1.27-9.42), used e-cigarettes to cope with shelter-in-place (AOR 4.06, 95% CI 1.39-13.41), or had ≥2 family members aware of participants' e-cigarette use (AOR 6.42, 95% CI 1.29-39.49) were more likely to report increased e-cigarette use. Conclusions: Almost all participants reported using social media more during shelter-in-place, with many respondents reporting increased e-cigarette use, and significant associations with loneliness and use to cope with shelter-in-place. Future interventions should consider leveraging digital platforms for e-cigarette use prevention and cessation and address the mental health consequences of the COVID-19 pandemic.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".