Quitting behaviors and cessation assistance used among smokers with anxiety or depression: Findings among six countries of the EUREST-PLUS ITC Europe Surveys
Notice bibliographique
Résumé
Introduction The current study explores quitting behaviours and use of cessation assistance among adult tobacco users with probable anxiety or depression (PAD) and in six European (EU) Member States (MS). Material and Methods The EUREST-PLUS ITC Wave 1 Europe Survey was conducted with a nationally representative cross-sectional sample of 6,011 adult cigarette smokers from six European Union (EU) Member States (MS) (Germany, Greece, Hungary, Poland, Romania, Spain) in 2016. Results Our study found that one in five smokers sampled from six EU MS had a diagnosis, treatment or positive screen for anxiety or depression, with rates of PAD varying between EU MS. Results of the multivariable logistic regression analysis showed that respondents with PAD were more likely to have made a quit attempt in the last 12 months (AOR 1.75; 95%CI 1.45-2.11), compared to respondents without PAD. Among those respondents with PAD who used support the most frequently reported quit method was prescription-based quit smoking pharmacotherapy (15.4%) followed by e-cigarettes (13.7%) and NRT (11.3%). Person-to-person behavioral support (i.e. local quit services, face-to-face advice from a doctor or other health care professional, telephone or quitline services) was reported significantly more frequently among respondents with PAD compared to those without PAD. Conclusions Given both pharmacological and non-pharmacological quit smoking aids have been shown to be safe, acceptable and effective for people with and without mental illness it is important that their use be promoted among smokers with anxiety and depression alongside behavioral counseling. Our findings support the need for interventions targeting health care professionals in providing smoking cessation assistance among this population of smokers. Acknowledgements EUREST-PLUS is a Horizon2020 project conducted by researchers throughout Europe from both the six participating countries as well as other institution partners within Europe and abroad. Partnering organizations include the European Network on Smoking Prevention (Belgium), Kings College London (United Kingdom), German Cancer Research Centre (Germany), University of Maastricht (The Netherlands), University of Athens (Greece), Aer Pur Romania (Romania), European Respiratory Society (Switzerland), the University of Waterloo (Canada), the Catalan Institute of Oncology (Catalonia, Spain), Smoking or Health Hungarian Foundation (Hungary), Health Promotion Foundation (Poland), University of Crete (Greece), and Kantar Public Brussels (Belgium). Funding The EUREST-PLUS Project takes place with the financial support of the European Commission, Horizon 2020 HCO-6-2015 program (EUREST-PLUS: 681109; C. Vardavas) and the University of Waterloo (GT. Fong). Additional support was provided to the University of Waterloo by the Canadian Institutes of Health Research (FDN-148477). GT. Fong was supported by a Senior Investigator Grant from the Ontario Institute for Cancer Research. E. Fernández is partly supported by Ministry of Universities and Research, Government of Catalonia (2017SGR139) and by the Instituto Carlos III and co-funded by the European Regional Development Fund (FEDER) (INT16/00211 and INT17/00103), Government of Spain.
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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) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| 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 ».