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Record W2004572177 · doi:10.1093/ntr/ntq111

Use of a national quitline and variation in use by smoker characteristics: ITC Project New Zealand

2010· article· en· W2004572177 on OpenAlexfundno aff
Nick Wilson, Deepaka Weerasekera, R. Borland, Richard Edwards, Chris Bullen, Jun Li

Bibliographic record

VenueNicotine & Tobacco Research · 2010
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersNational Cancer InstituteHealth Research Council of New ZealandCanadian Institutes of Health ResearchNational Institutes of HealthUniversity of Waterloo
KeywordsLibrary sciencePublic healthPopulationMedia studiesHistoryMedicineSociologyDemography

Abstract

fetched live from OpenAlex

INTRODUCTION: We aimed to describe use of a national quitline service and the variation in its use by smoker characteristics (particularly ethnicity and deprivation). The setting was New Zealand (NZ), which takes proactive measures to attract disadvantaged smokers to this service. METHODS: The NZ arm of the International Tobacco Control Policy Evaluation Survey (ITC Project) utilizes the New Zealand Health Survey (a national sample) from which we surveyed adult smokers in two waves (N = 1,376 and N = 923) 1 year apart. RESULTS: Quitline use in the last 12 months rose from 8.1% (95% CI = 6.3%-9.8%) in Wave 1 to 11.2% (95% CI = 8.4%-14.0%) at Wave 2. Māori (the indigenous people of NZ) were significantly more likely to call the Quitline than were European/other smokers. Relatively higher call rates also occurred among those reporting higher deprivation, financial stress, a past mental health disorder, a past drug-related disorder, and higher psychological distress (Kessler 10-item index). Independent associations in the multivariate analyses of Quitline use were being Māori, reporting financial stress, and ever having been diagnosed with a mental health disorder. DISCUSSION: This national Quitline service is successfully stimulating disproportionately more calls by Māori smokers and those with some measures of disadvantage. It may therefore be contributing to reducing health inequalities. It appears possible to target quitlines to reach those smokers in greatest need.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.101
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.001
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 head0.151
GPT teacher head0.413
Teacher spread0.262 · 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

Citations17
Published2010
Admission routes1
Has abstractyes

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