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Record W2142320887 · doi:10.1186/1617-9625-11-20

Stronger pack warnings predict quitting more than weaker ones: finding from the ITC Malaysia and Thailand surveys

2013· article· en· W2142320887 on OpenAlexafffund
Ahmed Ibrahim Fathelrahman, Lin Li, Ron Borland, Hua‐Hie Yong, Maizurah Omar, Rahmat Awang, Buppha Sirirassamee, Geoffrey T. Fong, David Hammond

Bibliographic record

VenueTobacco Induced Diseases · 2013
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Waterloo
FundersNational Institutes of HealthCancer Council VictoriaUniversity of Waterloo
KeywordsTobacco controlSmoking cessationEnvironmental healthPsychologyAdvertisingMedicineBusinessPublic healthPathology

Abstract

fetched live from OpenAlex

BACKGROUND: We examined the impact of cigarette pack warning labels on interest in quitting and subsequent quit attempts among adult smokers in Malaysia and Thailand. METHODS: Two overlapping cohorts of adults who reported smoking factory- made cigarettes from Malaysia and Thailand were interviewed face-to-face (3189 were surveyed at baseline and 1781 re-contacted at Wave 2; 2361 current smokers were surveyed at Wave 2 and 1586 re-contacted at Wave 3). In Thailand at baseline, large text only warnings were assessed, while at Wave 2 new large graphic warnings were assessed. In Malaysia, during both waves small text only warnings were in effect. Reactions were used to predict interest in quitting, and to predict making quit attempts over the following inter-wave interval. RESULTS: Multivariate predictors of "interest in quitting" were comparable across countries, but predictors of quit attempts varied. In both countries, cognitive reactions to warnings (adjusted ORs; 1.57 & 1.69 for Malaysia at wave 1 and wave 2 respectively and 1.29 & 1.19 for Thailand at wave 1 and wave 2 respectively), forgoing a cigarette (except Wave 2 in Malaysia) (adjusted ORs; 1.77 for Malaysia at wave 1 and 1.54 & 2.32 for Thailand at wave 1 and wave 2 respectively), and baseline knowledge (except wave 2 in both countries) (adjusted ORs; 1.71 & 1.51 for Malaysia and Thailand respectively) were positively associated with interest in quitting at that wave. In Thailand only, "cognitive reactions to warnings" (adjusted ORs; 1.12 & 1.23 at wave 1 and wave 2 respectively), "forgoing a cigarette" (adjusted OR = 1.55 at wave 2 only) and "an interest in quitting" (adjusted ORs; 1.61 & 2.85 at wave 1 and wave 2 respectively) were positively associated with quit attempts over the following inter-wave interval. Salience was negatively associated with subsequent quit attempts in both Malaysia and Thailand, but at Wave 2 only (adjusted ORs; 0.89 & 0.88 for Malaysia and Thailand respectively). CONCLUSION: Warnings appear to have common mechanisms for influencing quitting regardless of warning strength. The larger and more informative Thai warnings were associated with higher levels of reactions predictive of quitting and stronger associations with subsequent quitting, demonstrating their greater potency.

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 score0.010
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.280
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 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

Citations42
Published2013
Admission routes2
Has abstractyes

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