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Record W2170598296 · doi:10.1542/peds.2009-2335

Water-Pipe Smoking Among North American Youths

2010· article· en· W2170598296 on OpenAlexaffabout
Erika N. Dugas, Michèle Tremblay, Nancy Low, Daniel Cournoyer, Jennifer O’Loughlin

Bibliographic record

VenuePEDIATRICS · 2010
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsMcGill UniversityInstitut National de Santé Publique du QuébecUniversité de Montréal
Fundersnot available
KeywordsMedicineBinge drinkingContext (archaeology)Water pipeEnvironmental healthLogistic regressionPublic healthOddsPsychological interventionNicotineMultivariate analysisOdds ratioDemographyPoison controlSuicide preventionPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVES: The objectives of this analysis were to identify the sociodemographic characteristics of water-pipe users in a North American context and to describe concurrent psychoactive substance use. METHODS: Data on sociodemographic characteristics, water-pipe smoking, and use of other psychoactive substances were collected in 2007 through mailed self-report questionnaires completed by 871 young adults, 18 to 24 years of age, who were participating in the Nicotine Dependence in Teens Study, a longitudinal investigation of the natural history of nicotine dependence among adolescents in Montreal, Canada. Independent sociodemographic correlates of water-pipe use were identified in multivariate logistic regression analyses. RESULTS: Previous-year water-pipe use was reported by 23% of participants. Younger age, male gender, speaking English, not living with parents, and higher household income independently increased the odds of water-pipe use. Water-pipe use was markedly higher among participants who had smoked cigarettes, had used other tobacco products, had drunk alcohol, had engaged in binge drinking, had smoked marijuana, or had used other illicit drugs in the previous year. CONCLUSIONS: Water-pipe users may represent an advantaged group of young people with the leisure time, resources, and opportunity to use water-pipes. Evidence-based public health and policy interventions are required to equip the public to make informed decisions about water-pipe use.

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 score0.004
Threshold uncertainty score0.431

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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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

Citations75
Published2010
Admission routes2
Has abstractyes

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