Estimated Exposure to Televised Alcohol Advertisements Among Children and Adolescents
Notice bibliographique
Résumé
Importance: Alcohol advertising on television in China has the potential to target children and adolescents with harmful content. Understanding the extent of this advertising is critical for informing and improving current regulatory approaches. Objective: To measure the exposure of alcohol advertisements on television channels popular among children and adolescents in Beijing, China. Design, Setting, and Participants: This cross-sectional study of television advertisements used the 4 most popular television channels for viewers aged 3 to 18 years (2 children's channels and 2 general channels) in Beijing and accessed advertisements recorded from October 19, 2020, to January 17, 2021. Television advertisements were recorded during 4 randomly selected weekdays and 4 randomly selected weekend days (from 6:00 am to 11:59 pm). Data were analyzed from October 1, 2023, to December 31, 2024. Exposures: Television alcohol advertisements, with food and nonalcoholic beverages (F&B) advertisements classified as not permitted in marketing to children included as comparison. Main Outcomes and Measures: Primary outcomes included frequency and distribution of alcohol advertisements, rate per channel-hour, and potential exposure during peak viewing times (PVT). Secondary outcomes included comparison with F&B advertisements classified as not permitted based on the World Health Organization Western Pacific Region Office Nutrient Profile Model integrated with the International Network for Food and Obesity/Non-communicable Diseases Research, Monitoring and Action Support (INFORMAS) food classification system and analysis of 6 marketing strategies. Results: Among 13 864 total advertisements included in the analysis, 5368 were food advertisements. Among the food advertisements, 321 (6.0%; 95% CI, 5.4%-6.7%) were alcohol advertisements and 2001 (37.3%; 95% CI, 36.0%-38.6%) were F&B advertisements classified as not permitted. On general channels, a mean (SD) of 1.1 (1.7) alcohol advertisements per channel-hour were identified, with significantly higher rates during PVT compared with non-PVT (2.0 [2.4] vs 0.7 [0.9] per channel-hour; P < .001). The highest rate occurred between 9:00 and 9:59 pm, with a mean (SD) of 3.7 (2.8) advertisements per channel-hour and an estimated mean (SD) of 14 303 014 (11 659 096) impressions among children and adolescents. All 321 alcohol advertisements (100%; 95% CI, 98.9%-100%) and 1997 F&B advertisements classified as not permitted (99.8%; 95% CI, 99.5%-99.9%) used at least 1 marketing strategy, predominantly brand benefit claims, which were used in 307 alcohol advertisements (95.6%; 95% CI, 92.8%-97.4%) and 1915 F&B advertisements classified as not permitted (95.7%; 95% CI, 94.7%-96.5%). Conclusions and Relevance: In this cross-sectional study of television advertising, alcohol advertisements on general channels exceeded regulatory limits, especially during PVT. These findings suggest that current regulations allow exposure of children and adolescents to alcohol marketing and should be strengthened.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».