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Cessation assistance reported by smokers in 15 countries participating in the International Tobacco Control (ITC) policy evaluation surveys

2011· article· en· W2120468548 on OpenAlexafffundabout
Ron Borland, Lin Li, Pete Driezen, Nick Wilson, David Hammond, Mary E. Thompson, Geoffrey T. Fong, Ute Mons, Marc C. Willemsen, Ann McNeill, James F. Thrasher, K. Michael Cummings

Bibliographic record

VenueAddiction · 2011
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Waterloo
FundersNational Cancer InstituteCanadian Institutes of Health ResearchCancer Research UK
KeywordsTobacco controlSmoking cessationMedicineSmoking prevalenceEnvironmental healthHealth professionalsChinaPublic healthFamily medicineDemographyHealth careNursingGeographyEconomic growth

Abstract

fetched live from OpenAlex

AIMS: To describe some of the variability across the world in levels of quit smoking attempts and use of various forms of cessation support. DESIGN: Use of the International Tobacco Control Policy Evaluation Project surveys of smokers, using the 2007 survey wave (or later, where necessary). SETTINGS: Australia, Canada, China, France, Germany, Ireland, Malaysia, Mexico, the Netherlands, New Zealand, South Korea, Thailand, United Kingdom, Uruguay and United States. PARTICIPANTS: Samples of smokers from 15 countries. MEASUREMENTS: Self-report on use of cessation aids and on visits to health professionals and provision of cessation advice during the visits. FINDINGS: Prevalence of quit attempts in the last year varied from less than 20% to more than 50% across countries. Similarly, smokers varied greatly in reporting visiting health professionals in the last year (<20% to over 70%), and among those who did, provision of advice to quit also varied greatly. There was also marked variability in the levels and types of help reported. Use of medication was generally more common than use of behavioural support, except where medications are not readily available. CONCLUSIONS: There is wide variation across countries in rates of attempts to stop smoking and use of assistance with higher overall use of medication than behavioural support. There is also wide variation in the provision of brief advice to stop by health professionals.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.011
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 head0.080
GPT teacher head0.349
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

Citations119
Published2011
Admission routes3
Has abstractyes

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