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Record W1974410313 · doi:10.1503/cmaj.071241

Intentions of smokers to use free nicotine replacement therapy

2008· article· en· W1974410313 on OpenAlexaffvenue
John Cunningham, Peter Selby

Bibliographic record

VenueCanadian Medical Association Journal · 2008
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsCentre for Addiction and Mental Health
FundersSanofiPfizer
KeywordsNicotine replacement therapyNicotineMedicineSmoking cessationQuit smokingTelephone surveyPublic healthFamily medicinePhysical therapyPsychiatryNursingAdvertising

Abstract

fetched live from OpenAlex

Public health initiatives to distribute nicotine replacement therapy free of charge as a means of promoting smoking cessation are ongoing. Are there enough smokers interested in using nicotine replacement therapy to have a substantial impact on the prevalence of smoking if this aid were distributed free to all interested smokers? We conducted a telephone survey of 825 randomly selected daily smokers aged 18 years or older who had smoked at least 10 cigarettes per day at some point in their lives. Overall, 58.9% of the respondents said they would be interested in nicotine replacement therapy if it were offered for free. Of those interested, almost all (93.8%) said that they would use the nicotine replacement therapy to help them quit for good. There were differences in the levels of interest: smokers who intended to quit were more interested in using the nicotine replacement therapy than those who planned to reduce or maintain their 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.035
GPT teacher head0.284
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2008
Admission routes2
Has abstractyes

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