Testing the Efficacy of a Scalable Telephone-Delivered Guided Imagery Tobacco Cessation Treatment: Protocol for a Randomized Clinical Trial
Notice bibliographique
Résumé
BACKGROUND: Tobacco use continues to be a leading preventable cause of death and disease in the United States, accounting for >480,000 deaths each year. Although treatments for tobacco use are effective for many, there is substantial variability in outcomes, and these approaches are not effective for all individuals seeking to quit smoking cigarettes. New, effective therapeutic approaches are needed to meet the preferences of people who want to stop smoking. Guided imagery (GI) is a mind-body technique that involves the guided visualization of specific mental images, which is enhanced with other sensory modalities and emotions. Preliminary evidence provides initial support for the use of GI as a treatment for cigarette smoking. Meta-analyses have shown that standard treatment for cigarette smoking delivered over the telephone via quitlines is effective. A telephone-based intervention that uses GI might provide another effective treatment option and increase the reach and effectiveness of quitlines. OBJECTIVE: This study aims to test the efficacy of Be Smoke Free, a telephone-delivered GI treatment for smoking cessation. METHODS: This multisite randomized clinical trial (RCT) will compare a novel telephone-delivered GI tobacco cessation treatment with a standard evidence-based behavioral treatment. The study will be conducted over 5 years. In phase 1, we refined protocols and procedures for the New York State and West Virginia sites for use in the RCT. During phase 2, we will conduct an RCT with 1200 participants: 600 (50%) recruited via quitlines and 600 (50%) recruited via population-based methods. Participants will be randomly assigned to either the GI condition or the behavioral condition; both treatments will be delivered by trained study coaches located at the University of Arizona. Assessments will be conducted at baseline and 3 and 6 months after enrollment by University of Arizona research staff. The primary outcome will be self-reported 30-day point prevalence abstinence 6 months after enrollment. Secondary outcomes include biochemically verified 7-day point prevalence abstinence 6 months after enrollment. RESULTS: Recruitment in West Virginia and New York began in October 2022. As of March 31, 2023, a total of 242 participants had been enrolled. Follow-up assessments began in November 2022. As of March 31, 2023, of the 118 eligible participants, 97 (82.2%) had completed the 3-month assessment, and 93% (26/28) of eligible participants had completed the 6-month assessment. Biochemical verification and qualitative interviews began in April 2023. Recruitment will continue through 2025 and follow-up assessments through 2026. Primary results are expected to be published in 2027. CONCLUSIONS: The Be Smoke Free study is a first-of-its-kind RCT that incorporates GI into telephone-based tobacco cessation treatment. If successful, Be Smoke Free will have substantial benefits for the long-term health of people who use tobacco across the United States. TRIAL REGISTRATION: ClinicalTrials.gov NCT05277831; https://clinicaltrials.gov/ct2/show/NCT05277831. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/48898.
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 | 0,050 | 0,054 |
| Méta-épidémiologie (sens strict) | 0,007 | 0,004 |
| Méta-épidémiologie (sens large) | 0,011 | 0,007 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,010 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,084 | 0,015 |
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 ».