MétaCan
Menu
Back to cohort
Record W2059275812 · doi:10.1080/14622200801902201

Susceptibility to smoking and its association with physical activity, BMI, and weight concerns among youth

2008· article· en· W2059275812 on OpenAlexaffabout
Scott T. Leatherdale, Suzy L Wong, Steve Manske, Graham A. Colditz

Bibliographic record

VenueNicotine & Tobacco Research · 2008
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsCancer Care OntarioCanadian Cancer SocietyUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsMedicineGerontologyLibrary scienceFamily medicine

Abstract

fetched live from OpenAlex

Research has yet to examine how physical activity, body mass index (BMI) and concerns about weight among youth populations are associated with susceptibility to smoking among never smokers. The Physical Activity Module of the School Health Action, Planning and Evaluation System (SHAPES) was completed by 25,060 students in grades 9 to 12 within 76 secondary schools in Ontario (Canada) to examine how being overweight, weight concerns, and physical activity are associated with susceptibility to smoking in a large sample of youth. Among the 14,795 students who were never smokers, 3,809 (25.8%) were classified as susceptible to future smoking and 10,986 (74.2%) were classified as non-susceptible to future smoking. Smoking susceptibility was negatively associated with being highly active or at risk of overweight and positively associated with perceptions of being slightly overweight or slightly underweight. Students who report 1 or more hours of screen or phone time per day were also more likely to be susceptible. This is the first study to identify that susceptibility to future smoking among never smokers is associated with physical activity, overweight and concerns about weight. This is valuable new insight for tailoring and targeting future school-based tobacco control and/or physical activity programming to youth populations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.120
GPT teacher head0.388
Teacher spread0.269 · 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.

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

Citations38
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueNicotine & Tobacco ResearchSame topicSmoking Behavior and CessationFrench-language works237,207