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Record W4378070396 · doi:10.1016/j.pmedr.2023.102257

E-cigarette use by Ontario public elementary school and secondary school students: Has the use among sociodemographic groups changed from 2017 to 2019?

2023· article· en· W4378070396 on OpenAlexafffundabout
Linda L. Pederson, John J. Koval, Evelyn Vingilis

Bibliographic record

VenuePreventive Medicine Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsWestern UniversityCentre for Family Medicine
FundersCentre for Addiction and Mental Health
KeywordsDemographyMedicineDemographicsPublic healthGerontology

Abstract

fetched live from OpenAlex

This project examined e-cigarette use among Elementary School (ES) (grades 7 and 8) and Secondary School (SS) (grades 9-12) students in Ontario, Canada, for 2017 and 2019 and relationships with sociodemographic variables and traditional cigarette use. The data came from the Ontario Student Drug Use and Health Survey OSDUHS (2017, 2019). Socio-demographics included grade, school performance, sex, race, years in Canada, living arrangements and language spoken at home. E-cigarette use and cigarette smoking were any past year use. For 2017, there are a greater percentage of ES males than females who used e-cigarettes, older students, those living in more than one home and those smoking cigarettes. For SS students a greater percentage for those of older age, higher grades, living in Canada all their lives, using only English language at home, self-identified as white, with lower school performance, those with multiple household living arrangements and who reported smoking traditional cigarettes reported using e-cigarettes. Use was lower among females in 2017 (OR = 0.63, 95% CI = 0.46, 0.86, p = 0.002), but by 2019 use was higher among females, which resulted in a non-significant difference between males and females (OR = 0.91, 95% CI = 0.77, 1.09). Greater use of e-cigarettes was found among students who smoked traditional cigarettes compared to those who did not smoke in both years. Monitoring the trends, patterns and trajectories of use and variables related to use needs to be continued which may help inform the development of further legislative and educational measures.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.087
GPT teacher head0.313
Teacher spread0.226 · 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 teacher head, not a consensus.

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

Citations3
Published2023
Admission routes3
Has abstractyes

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