An Investigation of Social and Pharmacological Exposure to Secondhand Tobacco Smoke as Possible Predictors of Perceived Nicotine Dependence, Smoking Susceptibility, and Smoking Expectancies Among Never-Smoking Youth
Bibliographic record
Abstract
INTRODUCTION: Recent studies evidenced that adolescent never-smokers exposed to secondhand tobacco smoke (SHS) endorsed nicotine dependence symptoms. Other studies showed that SHS exposure measured with biomarkers among never-smokers independently predicted withdrawal sensations and prospective smoking initiation. The aim of the present study was to replicate and extend these findings by investigating whether social and pharmacological measures of SHS exposure predicted precursors to smoking among never-smoking adolescents. METHODS: Participants included 327 never-smokers aged 11-15 years attending sixth or seventh grade in French language schools in Montréal, Canada. They completed self-report questionnaires measuring their smoking status, social smoke exposure (number of smokers in their environment and number of situations where SHS exposure occurs), and precursors to smoking initiation (smoking expectancies, perceived nicotine dependence, and smoking susceptibility). Each participant provided a saliva sample from which cotinine biomarkers were derived to measure pharmacological exposure to SHS. RESULTS: When predictors were modeled individually, number of smokers predicted perceived nicotine dependence (p ≤ .05), smoking susceptibility (p ≤ .001), and expected benefits (p ≤ .05), whereas number of situations predicted smoking susceptibility (p ≤ .01). When predictors were modeled simultaneously, number of smokers predicted perceived nicotine dependence (p ≤ .01), smoking susceptibility (p ≤ .01), and expected benefits (p ≤ .05). CONCLUSIONS: Social smoke exposure was a predictor for smoking precursors. Pharmacological exposure to SHS did not predict smoking precursors, which may be partly attributable to the low cotinine values observed in our sample. Suggestions for improved pharmacological measurement of SHS and implications for public health are discussed.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".