Electronic nicotine delivery system flavors, devices, and brands used by adults in the United States who smoke and formerly smoked in 2022: Findings from the United States International Tobacco Control Four Country Smoking and Vaping Survey
Notice bibliographique
Résumé
• One in five adults in the United States who smoked or quit smoking were vaping nicotine in 2022. • Fruit was the most commonly used category of ENDS flavoring, and tanks were the most commonly used device. • Disposables were more often used by younger adults, and tanks by older adults. • A majority of adults who were vaping in 2022—and smoked or formerly smoked—were using a variety of flavors, devices, and brands. • Research is needed to determine whether enforcement actions that would remove unauthorized ENDS products may have unintended consequences. This study estimated prevalence of current electronic nicotine delivery systems (ENDS) used by US adults who smoked cigarettes or formerly smoked in 2022 and assessed ENDS flavors, devices, and brands used most often. Data are from the 2022 US ITC Smoking and Vaping Survey. Respondents were recruited from a web panel of a nationally representative sample of US adults ages 18+ who smoked, formerly smoked, and/or vaped ENDS. Using weighted data, we estimated prevalence of current vaping among adults who smoke or formerly smoked (N = 2,016). Among the subset who vaped (n = 554), we assessed flavors and devices used most often. Using unweighted data, we assessed the frequency (count) of reported brands used most often. In 2022, 22.0 % of US adults who smoked or formerly smoked were vaping at least monthly. A significantly higher proportion of adults who formerly smoked and/or were younger (18–39) were vaping than adults who were smoking and/or were older (40+) (both p < 0.001). Tank devices were used most often (34.7 %), followed by disposables (27.4 %), pre-filled pods/cartridges (23.0 %), and refillable pods/cartridges (14.9 %). The five most commonly used flavors were fruit (33.9 %), tobacco (20.1 %), menthol (12.2 %), candy/sweets (10.8 %), and mixed ice flavors (10.0 %). The top 5 brands were JUUL, Smok, Vuse, Geekvape, and Blu. In 2022, a majority of adults who smoked cigarettes or who had quit smoking used a variety of flavors and devices that go beyond the choices that FDA currently has authorized for sale.
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 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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 | 0,001 |
| 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 ».