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Record W2114944756 · doi:10.1136/tc.2009.030189

Distinguishing risk factors for the onset of cravings, withdrawal symptoms and tolerance in novice adolescent smokers

2009· article· en· W2114944756 on OpenAlexaff
Paul Wileyto, Jennifer O’Loughlin, Magdalena Lagerlund, Garbis Meshefedjian, Erika N. Dugas, André Gervais

Bibliographic record

VenueTobacco Control · 2009
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsCentre Hospitalier de l’Université de MontréalWestern UniversityUniversité de Montréal
Fundersnot available
KeywordsPsychologyMedicinePsychiatryClinical psychology

Abstract

fetched live from OpenAlex

AIM: While many studies report determinants of adolescent cigarette smoking, few identify risk factors for nicotine dependence (ND). This study distinguished between risk factors for three hallmarks of ND including cravings, withdrawal symptoms and tolerance. METHODS: A total of 319 novice smokers were followed every 3 months from first puff on a cigarette until the end of secondary school. Outcomes included time to first report of cravings, withdrawal symptoms and tolerance. RESULTS: Female sex, inhalation, smoking a whole cigarette, weekly smoking, daily smoking and alcohol use each independently increased the incidence of the onset of cravings. Inhalation, weekly smoking, daily smoking and alcohol use predicted the onset of withdrawal symptoms. Withdrawal symptoms, smoking a whole cigarette, monthly smoking, daily smoking and friends and siblings smoking increased the incidence of the onset of tolerance. None of parental education, impulsivity, novelty seeking, self-esteem, depression, stress, parental smoking, physical activity, or participation in sports teams was associated with the outcomes. CONCLUSION: The hallmarks of early ND are related to intensity and frequency of cigarette use. Avoidance of daily smoking may be particularly important in preventing the onset of ND symptoms and sustained smoking.

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)0.000
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 score0.016
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.011
GPT teacher head0.269
Teacher spread0.257 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

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