Tobacco Packaging and Mass Media Campaigns: Research Needs for Articles 11 and 12 of the WHO Framework Convention on Tobacco Control
Bibliographic record
Abstract
INTRODUCTION: Communicating the health risks of smoking remains a primary objective of tobacco-control policy. Articles 11 and 12 of the World Health Organization's Framework Convention on Tobacco Control establish standards for two important forms of communication: packaging regulations (Article 11), and mass media campaigns (Article 12). METHODS: A narrative review approach was used to identify existing evidence in the areas of package labeling regulations (including health warnings, constituent and emission messages, and prohibitions on misleading information) and communication activities (including mass media campaigns and news media coverage). When available, recent reviews of the literature were used, updated with more recent high-quality studies from published literature. RESULTS: Implementation of Articles 11 and 12 share several important research priorities: (a) identify existing consumer information needs and gaps, (b) research on the message source to identify effective types of content for health warnings and media campaigns, (c) research on how messages are processed and the extent to which the content and form of messages need to be tailored to different cultural and geographic groups, as well as subgroups within countries, and (d) research to identify the most cost-effective mix and best practices for sustaining health communications over time. CONCLUSION: A unifying theme of effective health communication through tobacco packaging and mass media campaigns is the need to provide salient, timely, and engaging reminders of the consequences of tobacco use in ways that motivate and support tobacco users trying to quit and make tobacco use less appealing for those at risk of taking it up.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.082 | 0.181 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".