Impact of anti-smoking advertising on health-risk knowledgeand quit attempts across 6 European countries from theEUREST-PLUS ITC Europe Survey
Notice bibliographique
Résumé
INTRODUCTION: Exposure to anti-smoking advertising and its effects differ across countries. This study examines the reported exposure to anti-smoking advertising among smokers and its relation to knowledge of smoking harms and quit attempts in six European countries. METHODS: Data come from Wave 1 of the International Tobacco Control (ITC) 6 European Country (6E) Survey (Germany, Greece, Hungary, Poland, Romania, Spain) carried out among smokers between June and September 2016 (n=6011). Key measures included whether participants had noticed anti-smoking advertising in the last six months in 6 different channels, their knowledge of 13 adverse smoking/second-hand smoking health effects and if they had made at least one quit attempt in the last 12 months. Multivariate logistic regression models were used in the analysis. RESULTS: Across the six countries, only 35.2% of smokers reported being exposed to any anti-smoking advertising. Television was the most common channel identified (25.7%), followed by newspapers and magazines (13.8%), while social media were the least reported (9.5%). Participants 18-24 years old were significantly more likely to have noticed advertisements on the Internet than participants >55 years old (24.3% vs 4.9%; OR=5.15). Participants exposed to anti-smoking advertising in all six channels were twice more likely to have a higher knowledge of smoking risks than those not exposed (2.4% vs 97.6%, respectively; OR=2.49). The likelihood of making a quit attempt was increased by 10% for each additional channel through which smokers were exposed to anti-smoking advertising. CONCLUSIONS: Knowledge of health risks of smoking tended to be higher in countries that aired a campaign in recent years. Exposure to anti-smoking advertising, in the six channels combined, was related to higher smoking knowledge of risks and to more quit attempts. Future anti-smoking mass media campaigns should consider advertising in all dissemination channels to increase the awareness of the dangers of smoking.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».