Thematic Analysis of Smoking Cessation and Future Cessation Interventions for Cancer Survivors: Convenience Sampling Study
Notice bibliographique
Résumé
Background: Smoking after a cancer diagnosis has significant health consequences, and there are substantial benefits if cancer survivors cease smoking. However, there are few smoking cessation interventions for cancer survivors that have been effective, and they are highly resource intensive. Thus, novel low resource cessation interventions are needed. One such intervention modality that has not been tested among cancer survivors is using pre-recorded videos to deliver information about skills and resources to achieve smoking cessation. Objective: This study aimed to assess barriers to smoking cessation, interest in a video-based smoking cessation intervention, and video content preferences (eg, topic, video length, age and gender of video presenter, presenter type [peer, medical professional]) among individuals with cancer who smoke cigarettes. Methods: Participants were recruited from a cancer center in the southeast United States that houses an opt-out tobacco treatment program in which tobacco treatment specialists proactively call all patients who have a current smoking status in their medical record. Patients were informed about the study, and their contact information was sent to the study team. Verbal consent was obtained from individuals who were cancer survivors, who were currently smoking, and who agreed to participate; semi-structured qualitative interviews were conducted (n=10). Participants were asked questions about smoking history, previous quit attempts, barriers to quitting smoking, previous experience with and openness to watching videos about quitting smoking, and participant preferences related to video content and presentation. Interviews were transcribed and coded by two reviewers, and a codebook was developed. A thematic analysis was then conducted. Results: Results indicated that all participants had previously tried to quit smoking, but other substance use (5/10; 50%), negative affect (eg, depression [4/10; 40%], anxiety [1/10; 10%], stress [2/10; 20%], and loneliness [1/10; 10%]), the social environment (eg, being around others who smoke [2/10; 20%] and risky social situations [2/10; 20%]), and habits surrounding smoking were significant barriers for cessation. All participants were open to watching smoking cessation videos and expressed a desire to see a peer with lived experience in the videos. Most (8/10; 80%) participants did not have preferences related to the age or gender of video presenters. Many participants had difficulty articulating content preferences for the videos. Conclusions: Cancer survivors who smoke may not be aware of their knowledge gaps related to smoking cessation, and videos may be an acceptable way to provide evidence-based information to fill knowledge gaps.
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 | 0,032 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,006 | 0,003 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».