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Record W2789657054 · doi:10.1111/add.14182

Do predictors of smoking relapse change as a function of duration of abstinence? Findings from the United States, Canada, United Kingdom and Australia

2018· article· en· W2789657054 on OpenAlexfundaboutno aff
Hua‐Hie Yong, Ron Borland, K. Michael Cummings, Timea Partos

Bibliographic record

VenueAddiction · 2018
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of HealthCancer Research UKCanadian Institutes of Health ResearchUniversity of WaterlooMedical Research CouncilUniversity of South CarolinaCancer Council VictoriaKing's College LondonNational Health and Medical Research CouncilPfizer
KeywordsMedicineAbstinenceSmoking cessationDemographyHazard ratioNicotine dependenceLongitudinal studyDemographicsCohortTobacco controlQuit smokingConfidence intervalPsychiatryInternal medicinePublic health

Abstract

fetched live from OpenAlex

AIMS: To estimate predictors of time to smoking relapse and test if prediction varied by quit duration. DESIGN: Longitudinal cohort data from the International Tobacco Control Four-Country survey with annual follow up collected between 2002 and 2015. SETTING: Canada, United States, United Kingdom and Australia. PARTICIPANTS: A total of 9171 eligible adult smokers who had made at least one quit attempt during the study period. MEASUREMENTS: Time to relapse was the main outcome. Predictor variables included pre-quit baseline measures of nicotine dependence, smoking and quitting-related motivations, quitting capacity and social influence, and also two post-quit measures, use of stop-smoking medications and quit duration (1-7 days, 8-14 days, 15-31 days, 1-3 months, 3-6 months, 6-12 months, 1-2 years and 2+ years), along with socio-demographics. FINDINGS: All factors were predictive of relapse within the first 6 months of quitting but only wanting to quit, quit intentions and number of friends who smoke were still predictive of relapse in the 6-12-month period of quitting [hazard ratios (HR) = 1.20, P < 0.05; 1.13, P < 0.05; and 1.21, P < 0.001, respectively]. Number of friends smoking was the only remaining predictor of relapse in the 1-2 years quit period (HR = 1.19, P = 0.001) with none predictive beyond the 2-year quit period. Use of stop-smoking medications during quit attempts was related negatively to relapse during the first 2 weeks of quitting (HR = 0.71-0.84), but related positively to relapse in the 1-6-month quit period (HR = 1.29-1.54). Predictive effects of all factors showed significant interaction with quit duration except for perceiving smoking as an important part of life, prematurely stubbing out a cigarette and wanting to quit. CONCLUSIONS: Among adult smokers in the United States, Canada, United Kingdom and Australia, factors associated with smoking relapse differ between the early and later stages of a quit attempt, suggesting that the determinants of relapse change as a function of abstinence duration.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.601
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.053
GPT teacher head0.285
Teacher spread0.233 · 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

Citations55
Published2018
Admission routes2
Has abstractyes

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