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Record W4399467648 · doi:10.1093/ntr/ntae139

Differential Responses to Cigarette Package Labeling Alternatives Among Adults Who Smoke: Results From a Randomized Trial

2024· article· en· W4399467648 on OpenAlexaff
James F. Thrasher, Emily E Hackworth, Stuart G. Ferguson, Liyan Xiong, Minji Kim, Chih‐Hsiang Yang, David Hammond, Yanwen Sun, James W. Hardin, Jeff Niederdeppe

Bibliographic record

VenueNicotine & Tobacco Research · 2024
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsRegional Municipality of WaterlooUniversity of Waterloo
FundersNational Cancer InstituteNational Institutes of Health
KeywordsRandomized controlled trialDifferential effectsPsychologySmoking cessationModerationMedicineDemographyEnvironmental healthSocial psychology

Abstract

fetched live from OpenAlex

INTRODUCTION: Little experimental research has evaluated whether the effects of cigarette package inserts with efficacy messages and/or pictorial health warning labels (PHWLs) differ across key subgroups of adults who smoke. AIMS AND METHODS: Adults who reported currently smoking (n = 367) were randomly assigned to one of four groups: Small text-only HWLs on pack sides (control); inserts with efficacy messages and small HWLs (inserts-only); PHWLs showing harms of smoking (PHWLs-only); both (inserts + PHWLs). Participants received a 14-day supply of cigarettes labeled to reflect their group. Every evening over 2 weeks, participants reported forgoing and stubbing out cigarettes before they finished smoking over the prior 24 hours, combined into a binary indicator of either behavior (eg, forgoing/stubbing). Separate mixed-effects logistic models were estimated to evaluate moderation of labeling group contrasts (ie, PHWLs vs not; inserts vs. not; inserts-only vs. inserts + PHWLs; PHWLs-only vs. inserts + PHWLs) by baseline covariates (self-efficacy to quit, intention to quit, education, health literacy, and time discounting), predicting day-level forgoing/stubbing. RESULTS: Education moderated PHWL effects, with PHWLs predicting more forgoing/stubbing only among those with low education (OR = 4.68, p < .001). Time discounting moderated insert effects, with inserts promoting forgoing/stubbing only among those with low time discounting (ie, lower impulsivity; OR = 4.35, p < .001). CONCLUSIONS: Inserts with efficacy messages appear effective mostly among people with low time discounting, whereas PHWLs appear most effective among those with low education, suggesting their potential to address education-related disparities. Labeling strategies appeared equally effective across subgroups defined by self-efficacy to quit, quit intention, and health literacy. Combining inserts with PHWLs did not appear to mitigate moderation effects. IMPLICATIONS: This randomized trial with adults who smoke suggests that cigarette packs with inserts describing cessation benefits and tips can promote cessation-related behaviors (ie, forgoing or stubbing out cigarettes) among those with low-time discounting (ie, low impulsivity). Alternative interventions may be needed for people with high-time discounting, as found in cessation trials. PHWLs appear most effective among those with low education, potentially addressing education-related disparities. No differential effects were found for those with different levels of self-efficacy to quit, quit intentions, or health literacy. Combining inserts and PHWLs may not be more effective than either alone.

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)0.010
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.082
GPT teacher head0.406
Teacher spread0.325 · 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 designRandomized trial
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

Citations4
Published2024
Admission routes1
Has abstractyes

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