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Record W4406384078 · doi:10.24095/hpcdp.45.1.04

Use of nicotine vaping products during an attempt to quit smoking by Canadian adults who smoke or recently quit: findings from the 2022 Canada International Tobacco Control Four Country Smoking and Vaping Survey

2025· article· en· W4406384078 on OpenAlexaffvenueabout
Shannon Gravely, David Sweanor, Pete Driezen, David T. Levy, Geoffrey T. Fong, Anne C K Quah, Lorraine Craig, Janet Chung‐Hall, Susan Kaai, K. Michael Cummings

Bibliographic record

VenueHealth Promotion and Chronic Disease Prevention in Canada · 2025
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of OttawaOntario Institute for Cancer ResearchUniversity of Waterloo
Fundersnot available
KeywordsQuit smokingNicotineTobacco controlSmokeEnvironmental healthSmoking cessationMedicinePsychologyPsychiatryPublic healthEngineeringWaste managementNursing

Abstract

fetched live from OpenAlex

An analysis of 1771 Canadian adults who smoke or used to smoke cigarettes was conducted using data from the 2022 International Tobacco Control Four Country Smoking and Vaping Survey. Using weighted data, we estimated the prevalence of Canadian adults who tried to quit smoking between 2020 and 2022, and the use of a nicotine vaping product (NVP) and the flavours and devices used most often at their most recent quit attempt. Overall, 36.5% made a quit attempt; of those, 19.4% used an NVP. Those who were younger and quit smoking were more likely to have used an NVP. Prefilled cartridges or pods (36.3%) and fruit flavours (39.5%) were used most frequently.

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)0.001
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 score0.013
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.044
GPT teacher head0.316
Teacher spread0.272 · 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
Published2025
Admission routes3
Has abstractyes

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