Smoking Clinical Trial
Official title:
Adaptive Interventions for Smoking Cessation in Lung Cancer Screening Programs
In this sequential, multiple assignment, randomized trial (SMART) current smokers who are eligible for lung cancer screening will be identified using the electronic medical record at the University of Minnesota and Minneapolis VA (N=1000). All participants will receive 8 weeks of evidence-based first-line smoking cessation treatment. Participants will be eligible for three potential randomizations during one year of smoking intervention: 1) to timing of identifying early response to treatment at 4 vs. 8 weeks (all participants), 2) to telephone-based tobacco longitudinal care (TLC) vs. TLC plus pharmacist-administered Medication Therapy Management (incomplete responders to first-line treatment, Primary Aim), and 3) to monthly TLC contact vs. quarterly TLC contact (complete responders to first-line treatment, Secondary Aim). The primary outcome will be 6 months of prolonged abstinence measured 18 months after the beginning of treatment.
In this sequential, multiple assignment, randomized trial (SMART) current smokers who are eligible for lung cancer screening will be identified using the electronic medical record at the University of Minnesota and Minneapolis VA (N=1000). All participants will receive 8 weeks of evidence-based first-line smoking cessation treatment. Participants will be eligible for three potential randomizations during one year of smoking intervention: 1) to timing of identifying early response to treatment at 4 vs. 8 weeks (all participants), 2) to telephone-based tobacco longitudinal care (TLC) vs. TLC plus pharmacist-administered Medication Therapy Management (incomplete responders to first-line treatment, Primary Aim), and 3) to monthly TLC contact vs. quarterly TLC contact (complete responders to first-line treatment, Secondary Aim). The primary outcome will be 6 months of prolonged abstinence measured 18 months after the beginning of treatment (self-reported smoking abstinence using imputation for missing data). ;
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