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Record W1987528881 · doi:10.1155/2012/406283

Trends in Roll-Your-Own Smoking: Findings from the ITC Four-Country Survey (2002–2008)

2012· article· en· W1987528881 on OpenAlexafffundabout
David Young, Hua‐Hie Yong, Ron Borland, Lion Shahab, David Hammond, K. Michael Cummings, Nick Wilson

Bibliographic record

VenueJournal of Environmental and Public Health · 2012
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Waterloo
FundersNational Health and Medical Research CouncilMedical Research CouncilCanadian Institutes of Health ResearchUniversity of WaterlooCanadian Tobacco Control Research InitiativeNational Cancer InstituteCancer Research UKRobert Wood Johnson Foundation
KeywordsEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To establish the trends in prevalence, and correlates, of roll-your-own (RYO) use in Canada, USA, UK and Australia, 2002-2008. METHODS: Participants were 19,456 cigarette smokers interviewed during the longitudinal International Tobacco Control (ITC) Four-Country Survey in Canada, USA, UK, and Australia. RESULTS: "Predominant" RYO use (i.e., >50% of cigarettes smoked) increased significantly in the UK and USA as a proportion of all cigarette use (both P < .001) and in all countries as a proportion of any RYO use (all P < .010). Younger, financially stressed smokers are disproportionately contributing to "some" use (i.e., ≤50% of cigarettes smoked). Relative cost was the major reason given for using RYO, and predominant RYO use is consistently and significantly associated with low income. CONCLUSIONS: RYO market trends reflect the price advantages accruing to RYO (a product of favourable taxation regimes in some jurisdictions reinforced by the enhanced control over the amount of tobacco used), especially following the impact of the Global Financial Crisis; the availability of competing low-cost alternatives to RYO; accessibility of duty-free RYO tobacco; and tobacco industry niche marketing strategies. If policy makers want to ensure that the RYO option does not inhibit the fight to end the tobacco epidemic, especially amongst the disadvantaged, they need to reduce the price advantage, target additional health messages at (young) RYO users, and challenge niche marketing of RYO by the industry.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.079
GPT teacher head0.311
Teacher spread0.232 · 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.

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

Citations52
Published2012
Admission routes3
Has abstractyes

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