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Record W2023807492 · doi:10.1093/ntr/ntq052

To what extent do smokers make spontaneous quit attempts and what are the implications for smoking cessation maintenance? Findings from the International Tobacco Control Four country survey

2010· article· en· W2023807492 on OpenAlexfundno aff
Jae Cooper, R. Borland, Hua‐Hie Yong, Ann McNeill, Rachael L Murray, Richard O'Connor, K. Michael Cummings

Bibliographic record

VenueNicotine & Tobacco Research · 2010
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersEconomic and Social Research CouncilMedical Research CouncilCanadian Institutes of Health ResearchNational Health and Medical Research CouncilNational Cancer InstituteCancer Research UK
KeywordsSmoking cessationAbstinenceTobacco controlQuit smokingMedicineDemographyPsychologyPsychiatryPublic health

Abstract

fetched live from OpenAlex

AIM: To assess the extent to which quit attempts are spontaneous and to evaluate if this is a determinant of smoking cessation maintenance, with better control for memory effects. METHODS: We use data from 3,022 smokers who made quit attempts between Waves 4 and 5 and/or Waves 5 and 6 of the International Tobacco Control Four country survey. Outcomes (quitting for 6 months) were confirmed at the next wave for cases where the attempt began within the previous 6 months. We assessed the length of delay between the decision to quit and implementation and whether the attempt followed a "spur-of-the-moment" decision or some serious prior consideration. Outcomes were modeled using generalized estimating equations. RESULTS: Prior consideration of quitting was unrelated to the outcome, but there were complex relationships for the delay between choosing a quit day and implementation. Those who reported quitting on the day they decided and those who delayed for 1 week or more had comparable rates of 6-month abstinence. Delaying for 1-6 days was associated with a greater relapse rate than those who quit on the day, although this effect became nonsignificant in multivariate analyses. CONCLUSIONS: Quitting is on most smokers' minds regularly and most attempts are not preceded by a long lead in period following the decision to try. Neither prior consideration nor delay between the decision to quit and implementation was clearly related to outcomes. Previous findings of greater success for spontaneous quit attempts may be because they conflate setting a date in advance with planning and also perhaps some differential memory effects.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
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 head0.080
GPT teacher head0.371
Teacher spread0.291 · 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

Citations53
Published2010
Admission routes1
Has abstractyes

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