Vaping and Mental Health Conditions in Children: An Umbrella Review
Bibliographic record
Abstract
The e-cigarette (EC) epidemic began in the United States (US) in 2007; since 2014 EC is the most commonly used form of tobacco. However, the mental health implications of vaping are grossly unknown. The aim of this umbrella review is to provide astate-of-the-art summary of existing research concerning vaping and mental health conditions in children. Following the PRISMA Statement 2020 guidelines, a systematic search was conducted across PubMed, Cochrane Library, and Google Scholar up to April 15th, 2022 to locate relevant studies. The Joana Briggs Institute (JBI) methodology for umbrella reviews and quality appraisal tool was utilized. Six studies, pooling a total of 846,510 adolescents aged 21 years or below, were included by collating 85 primary clinical studies. Of these, 58.8% of the primary clinical studies originated in the US, with 4.7% from Canada, South Korea, and the United Kingdom each; 3.5% each from England and Taiwan; 2.4% each from Australia, France, Hawaii, Mexico, and Russia; and 1.2% each from Denmark, Greece, Hong Kong, Iceland, New Zealand, Poland, and Switzerland. Overall, significant associations were found between mental health outcomes, including depression and suicidality, among current EC users and those who had ever used EC. Compared to adolescents who had never used EC, both depression and anxiety were reportedly higher among EC users. Impulsive behaviors, reported as impulsivity, were also found to be correlated with the adoption of EC use. However, there is a lack of evidence regarding the impact of EC use on mental health outcomes in children. This umbrella review highlights the urgent need to further explore the effects of current EC use from a psychiatric and public health perspective.
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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) | 0.001 | 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".