Developing tobacco risk communications for young adults susceptible to dual use of combustible cigarettes and nicotine vapes (Preprint)
Notice bibliographique
Résumé
Background: Dual use of combustible cigarettes and nicotine vapes is disproportionately high among lesbian, gay, bisexual, transgender, and queer (LGBTQ+) young adults. Mass-reach health communications may be effective at curbing dual use. Current research is exploring whether comparative risk messaging, which presents nicotine vapes as less harmful than cigarettes, reduces dual use. Objective: This formative message testing study focused on communicating the health risks of cigarette smoking and nicotine vaping use to young adults susceptible to dual use of these products, including LGBTQ+ young adults. Methods: Online focus groups were conducted with young adults to develop candidate messages (N=12). Interviews (N=13) qualitatively explored thematic content. An online rating survey (N=286) quantitatively assessed perceived message effectiveness (PME) of and reactance to candidate messages applying standard and comparative risk message framing, compared to adapted regulatory warnings used by the US Food and Drug Administration. Results: Qualitatively, interview and focus group participants found messages featuring novel information, including toxic constituents and physical harms (eg, hypertension), most effective. "Known" harms (eg, cancer) were described as effective by LGBTQ+ young adults due to the "shock value" of fear appeals. However, participants recommended pairing "known" harms with novel information; for example, addiction messaging was best received when described in the context of social or occasional use. Comparative messaging was appealing for harm reduction (ie, encouraging young adults who use cigarettes to quit smoking and use nicotine vapes), especially among LGBTQ+ participants. However, participants were concerned that comparative messages could unintentionally promote vaping among nicotine-naïve young adults. Qualitative participants preferred gain-framed efficacy messages that encouraged rather than demanded behavior change. Efficacy messages that emphasized "switching" were described as permissive for vaping, and participants were concerned that these may encourage sustained nicotine use. Some questioned whether vaping could effectively help young adults quit smoking. Survey results supported qualitative findings: messages with highest PME scores addressed toxic constituents, heart and lung disease, and cancer. Addiction messages were least effective. Among participants engaged in dual use, PME-smoking scores were higher when viewing candidate comparative messages than regulatory messages, but there were no significant differences between standard and comparative messages. The most effective candidate efficacy messages addressed quitting all smoking and vaping to reduce health risks. Messages that encouraged quitting smoking and switching to vapes were rated least effective. Conclusions: Comparative messaging was associated with higher PME-smoking among young adults engaged in dual use but did not consistently outperform standard messaging. Qualitative findings suggest that comparative framing may be misinterpreted as endorsing vaping as "safe" rather than "lower harm than cigarettes." Further research is needed to examine potential unintended consequences of comparative messaging, including sustained nicotine use among young adults who smoke or normalization of vaping among nicotine-naïve young adults.
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 | 0,001 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
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 ».