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Record W7048065969

Internalizing Mental Health Symptoms and Nicotine Use Among Adolescents in Canada, England, and the US from 2020-2022

2024· article· en· W7048065969 on OpenAlexaboutno aff

Bibliographic record

VenueScholar Commons (University of South Carolina) · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsNicotineMultinomial logistic regressionMental healthDepression (economics)Association (psychology)Logistic regressionSocioeconomic statusSmoking cessation
DOInot available

Abstract

fetched live from OpenAlex

Background: There is a well-established bi-directional relationship between cigarette smoking and internalizing mental health (IMH) symptoms (e.g., symptoms of depression, symptoms of anxiety). However, it is unclear whether IMH symptoms are associated with using different types of nicotine products among adolescents, as adolescents are using a variety of nicotine products, including combustible products (cigarettes), non-combustible products (e-cigarettes), or combinations of both types of products. This dissertation examines associations between IMH symptoms and current use of various types of nicotine products across three countries from 2020-2022. Methods: Data come from the 2020-2022 waves of the International Tobacco Control (ITC) Adolescents Tobacco and Vaping Survey, an online repeat cross-sectional survey of adolescents aged 16-19 in Canada, England, and the US (n=67946). In the full sample, current nicotine use was examined in four categories: 1) no use, 2) exclusive non-combustible product, 3) exclusive combustible product use, and 4) use of both product types. Respondents reported current symptoms of depression or anxiety, and we generated a dichotomous IMH symptoms variable (yes vs. no). Respondents also reported their age race, sex, gender identity, and socioeconomic status. We examined the association between IMH symptoms and current nicotine use using multinomial logistic regression models that adjusted for covariates. Among the respondents that reported using cigarettes and/or e-cigarettes (n=15522), we also examined the association between IMH symptoms and nicotine dependence indicators and cessation variables (quit intention, quit attempt). Results: IMH symptoms were most strongly associated with use of both product types, followed by exclusive non-combustible use, and then exclusive combustible use. Nicotine use and IMH symptoms varied by gender identity. Among adolescents reporting current e-cigarette use, IMH symptoms were positively associated with nicotine dependence indicators. However, for those reporting cigarette use, this association varied by whether they were dual using e-cigarettes. For both products, IMH symptoms were positively associated with quit attempt and unassociated with quit intention. Conclusions: This dissertation provides an up-to-date examination of the relationship between mental health and nicotine use among adolescents. Results indicate that non-combustible product use may have a particularly strong relationship with poor mental health among adolescents. Longitudinal research is needed to better understand directionality. Results also provide an understanding of the relationship between gender identity and nicotine use.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.007
GPT teacher head0.190
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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