Cancer patient attitudes and preferences towards smoking status assessment.
Notice bibliographique
Résumé
110 Background: Continued smoking after a cancer diagnosis is associated with poorer outcomes. As smoking cessation is an important part of cancer care, understanding pt attitudes towards smoking status assessment will help with integrating smoking cessation programs into survivorship care. Methods: Cancer pts were surveyed on their smoking history, assessment rates and attitudes/preferences towards smoking status assessment. Multivariate logistic regression models assessed for factors associated with screening preferences. Results: Among 501 pts, 115 smoked at diagnosis, 60% quit after; 53% had a tobacco related (lung/head and neck) cancer (TRC); 40% reported that their smoking status was assessed only on their first clinic visit, while 32% were assessed at a few visits and 12% all visits. Most felt smoking status should be assessed at the first visit (95%), while half (58%) felt it should be assessed each visit. Most felt comfortable with being assessed (96%), felt it was important for clinicians to be aware of smoking status (98%) and that smoking cessation discussions should occur at the first visit (87%). Most preferred being assessed by their oncologist (88%); less than half preferred being asked by another healthcare provider (44%), on paper (29%) or e-surveys (32%). Compared to ex/never smokers, current smokers were assessed more often at every/most visits (36% vs 20% P= 0.001) and were less comfortable with being assessed (88% vs 98% P< 0.001). Among current smokers, lung cancer pts were more agreeable (58%) to being assessed each visit compared to head/neck (aOR 2.48 95% CI [0.9-6.5] P= 0.06) and non TRCs (aOR 2.63 [1.0-6.8] P= 0.05). Among all, pts who are older (aOR 1.03 [1.0-1.1]), curative (aOR 1.92 [1.1-3.2]) and smoked less (aOR 0.98 per pkyr [0.97-0.99]) were more agreeable to assessment at each visit. Most pts also felt oncologists should screen for second hand smoke exposure (92%), felt its assessment was important (93%) and should help others who smoke to quit (68%). Conclusions: Most cancer pts felt that assessment of smoking status was important, were comfortable being assessed and preferred being assessed directly by their oncologist. Routine screening of those currently smoking is recommended to help with cessation.
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 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,006 | 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 ».