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Record W2127411283 · doi:10.1093/her/cyu036

Reactions to graphic health warnings in the United States

2014· article· en· W2127411283 on OpenAlexfundno aff
James Nonnemaker, Conrad J. Choinière, Matthew C. Farrelly, Kian Kamyab, Kevin Davis

Bibliographic record

VenueHealth Education Research · 2014
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersU.S. Public Health ServiceHamilton Health Sciences Foundation
KeywordsYoung adultCognitionMedicinePsychologyClinical psychologyGerontologyPsychiatry

Abstract

fetched live from OpenAlex

This study reports consumer reactions to the graphic health warnings selected by the Food and Drug Administration to be placed on cigarette packs in the United States. We recruited three sets of respondents for an experimental study from a national opt-in e-mail list sample: (i) current smokers aged 25 or older, (ii) young adult smokers aged 18-24 and (iii) youth aged 13-17 who are current smokers or who may be susceptible to initiation of smoking. Participants were randomly assigned to be exposed to a pack of cigarettes with one of nine graphic health warnings or with a text-only warning statement. All three age groups had overall strong negative emotional (ß = 4.7, P < 0.001 for adults; ß = 4.6, P < 0.001 for young adults and ß = 4.0, P < 0.001 for youth) and cognitive (ß = 2.4, P < 0.001 for adults; ß = 3.0, P < 0.001 for young adults and ß = 4.6, P < 0.001 for youth) reactions to the proposed labels. The strong negative emotional and cognitive reactions following a single exposure to the graphic health warnings suggest that, with repeated exposures over time, graphic health warnings may influence smokers' beliefs, intentions and behaviors.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.191
GPT teacher head0.540
Teacher spread0.349 · 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 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

Citations41
Published2014
Admission routes1
Has abstractyes

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