Cognitive Behavioral Treatment With Activity Trackers for Smoking Cessation
Cognitive Behavioral Treatment With Activity Trackers for Smoking Cessation
Given the high prevalence of deaths per year attributable to tobacco use, improving smoking cessation treatments is an important public health priority Worldwide. It is also known that practicing physical activity (PA) may help with smoking cessation. Physical activity trackers (PATs) have been demonstrated to increase PA levels among various populations, as a sole intervention or in combination with behavioral interventions targeting PA.
This study aims to examine the feasibility and effect of a cognitive-behavioral therapy (CBT) + Physical Activity Tracker use (Fitbit Versa 3®) for smoking cessation.
In this study, an estimated sample of 120 adult smokers of at least 10 cigarettes per day will be randomly allocated to one of the following conditions: 1) CBT for smoking cessation + PAT; 2) CBT for smoking cessation.
Mail goals: 1) To examine the feasibility (i.e., adherence, perceived utility, satisfaction) of integrating Fitbit Versa 3® into a CBT for smoking cessation; 2) to examine the effectiveness of CBT for smoking cessation + PAT and CBT for smoking cessation in terms of smoking abstinence rates (point-prevalence and days of continuous abstinence), PA (i.e., steps per day, moderate to vigorous physical activity), physiological outcomes (i.e. sleep quality, quality of life) and mental health outcomes (anxiety and depression symptoms, difficulties in emotional regulation); 3) to examine the association between PA levels and study outcomes
PATs provide information on several objective data related to PA and sleep habits, amongst others. Incipient research has piloted its use for vulnerable populations (e.g., mental health disorders, cancer patients), obtaining satisfactory effects on both feasibility and effectiveness outcomes. In the field of substance use, some studies looked at the effects of PATs on PA but did not evaluate them in a randomized clinical trial. Moreover, increases in PA and improvements in emotional variables may be associated with smoking abstinence, and, arguably, using PAT devices may have an indirect impact on smoking abstinence via these variables.
A 6-week protocol will be employed, including group-based cognitive behavioral therapy for smoking cessation treatment and PAT use. Participants will be recruited from the community and will be randomly allocated to the following conditions: 1) CBT for smoking cessation + PATs; 2) CBT for smoking cessation
A priori power analysis was conducted using Monte Carlo methods to estimate the statistical power of the generalized estimating equations (GEE) models used to analyze seven-day point-prevalence abstinence rates. Assessment point and treatment condition were included as fixed factors, and age was included as a covariate. Additional subject-level variability was incorporated to approximate within-subject correlation across repeated measurements. Under assumptions of a large effect size for time (approximately OR = 2.0), statistical power reached approximately 0.68 for a sample size of 120 participants, indicating moderate sensitivity to detect longitudinal changes in abstinence outcomes. In the case of PA (i.e., steps per day), a Monte Carlo simulation was conducted for a mixed linear model (MLM) including time and group as fixed effects. Age and baseline PA levels were included as covariates. Power exceeded 0.90 even at sample sizes of approximately 30 participants, so the design is fully powered. R 4.5.3 was used for the power analysis.
Analyses will be conducted using the Statistical Package for the Social Sciences (SPSS), R, JASP, and JAMOVI. A set of univariate (i.e., descriptive statistics and frequencies) and multivariate analyses (i.e., t-tests, GEE, and MLM)
Inclusion Criteria:
Exclusion Criteria: