Clinical trial NCT06629467: Cognitive Behavioral Treatment with Activity Trackers for Smoking Cessation
Official title: Cognitive Behavioral Treatment with Activity Trackers for Smoking Cessation
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Tobacco Use Cessation
Physical Activity
Keywords: Tobacco
Physical activity
Activity tracker
Cognitive-behavioral therapy
Lead sponsor: University of Oviedo
Sponsor class: OTHER
First posted: 2024-10-08
Enrollment: 128
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: TREATMENT

Brief summary: 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 smoking cessation. Physical activity trackers have been demonstrated to increase PA levels in different studies with various populations, as a sole intervention or in combination with interventions targeting PA.

This study aims to examine the feasibility, effect, and cost-effectiveness of cognitive-behavioral therapy (CBT) + Personalized physical activity (PA) + Physical Activity Tracker use (Fitbit Versa 3®) 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.

In this study, an estimated sample of 128 adult smokers will be randomly allocated to one of the following conditions: 1) CBT for smoking cessation + personalized PA plan + Fitbit Versa 3®; 2) CBT for smoking cessation + personalized PA plan.

Mail goals: 1) To examine the feasibility (i.e., adherence, perceived utility, satisfaction) of integrating Fitbit Versa 3® into a CBT protocol for smoking cessation; 2) to examine the effectiveness of CBT for smoking cessation + personalized PA plan + Fitbit Versa 3® and CBT for smoking cessation + personalized PA plan in terms of smoking abstinence rates (point-prevalence and days of continuous abstinence), PA (i.e., steps per day, moderate to vigorous physical activity) and mental health outcomes (anxiety and depression symptoms, emotional dysregulation); 3) to examine the cost-effectiveness of CBT for smoking cessation + personalized PA plan + Fitbit Versa 3® vs. CBT for smoking cessation + personalized PA plan in terms of smoking abstinence rates (point-prevalence and days of continuous abstinence), PA (i.e., steps per day, moderate to vigorous physical activity) and mental health outcomes (anxiety and depression symptoms, emotional dysregulation).

Detailed description: Fitbit® wearables devices inform on several objective data related to physical activity and sleep habits, amongst others. Incipient research has piloted its use for vulnerable populations such as emerging adults and clinical patients. In the field of substance use, some studies looked at the effects of activity trackers on physical activity but did not evaluate its effects on other clinically relevant variables, such as smoking abstinence. Increases in activity and improvements in mood are associated with smoking abstinence and, arguably, using Fitbit Versa 3® devices would produce any effect on cigarette smoking via these variables.

A 6-week protocol will be employed including a cognitive behavioral therapy-based smoking cessation treatment. Participants will be recruited from the community and will be randomly allocated to the following conditions once an in-person assessment is completed: 1) CBT for smoking cessation + personalized PA plan + Fitbit Versa 3®; 2) CBT for smoking cessation + personalized PA plan. According to the power analysis, to detect an effect size of d = 0.5 (medium size effect) with a test power of 0.8 the total number of allocated participants will be 128. This sample size was estimated to be sufficient for the statistical pipeline.

Analyses will be conducted using the Statistical Package for the Social Science (SPSS), R Studio, JASP, and JAMOVI. A set of univariate (i.e., descriptive statistics and frequencies) and multivariate analyses (i.e. t-test) will be carried out with regard to participants; characteristics and treatment outcomes. Generalized Estimating Equations (GEE) will be conducted to examine changes in smoking abstinence after controlling for relevant covariates (e.g., nicotine dependence, sex). DATCAP will be used to perform the cost-effectivity

Eligibility criteria: Inclusion Criteria:

* Being aged 18 or over.
* Smoking at least 10 cigarettes per day.

Exclusion Criteria:

* Being currently receiving other psychological or pharmacological treatment for smoking cessation.
* Being diagnosed with substance use disorder or severe psychiatric disorder.
* Active suicidal ideation.

Primary outcomes:
measure: Acceptability of the activity tracker
timeFrame: End-of-treatment (6-weeks)
measure: Tobacco use
timeFrame: From Enrollment to End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
measure: Feasibility of treatment and activity tracker use
timeFrame: End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
measure: Physical activity
timeFrame: In-treatment, from enrollment to end-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
measure: Activity tracker perceived utility
timeFrame: End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
Secondary outcomes:
measure: Anxiety symptoms
timeFrame: From Enrollment to End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
measure: Depression symptoms
timeFrame: From Enrollment to End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
measure: Hypothetical demand for cigarettes
timeFrame: Enrollment
measure: Emotional dysregulation of negative valence emotions
timeFrame: From Enrollment to End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
measure: Emotional dysregulation of positive valence emotions
timeFrame: From Enrollment to End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
measure: Delay Discounting
timeFrame: From Enrollment to End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
measure: Suicide ideation
timeFrame: From Enrollment to End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
measure: Life Quality
timeFrame: From Enrollment to End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
measure: Sleep quality
timeFrame: In treatment (6 weeks), from Enrollment to End-of-treatment (6-weeks), one-, three-, six-, -month follow-up.
Other outcomes:
Locations:
city: Oviedo
country: Spain
facility: Clinical Unit of Addictive Behaviors
state: Asturias
Study officials:
References:
citation: Abrantes AM, Van Noppen D, Bailey G, Uebelacker LA, Buman M, Stein MD. A Feasibility Study of a Peer-Facilitated Physical Activity Intervention in Methadone Maintenance. Ment Health Phys Act. 2021 Oct;21:100419. doi: 10.1016/j.mhpa.2021.100419. Epub 2021 Aug 14.
citation: Carreiro S, Chintha KK, Shrestha S, Chapman B, Smelson D, Indic P. Wearable sensor-based detection of stress and craving in patients during treatment for substance use disorder: A mixed methods pilot study. Drug Alcohol Depend. 2020 Apr 1;209:107929. doi: 10.1016/j.drugalcdep.2020.107929. Epub 2020 Mar 3.
citation: Goldfine C, Lai JT, Lucey E, Newcomb M, Carreiro S. Wearable and Wireless mHealth Technologies for Substance Use Disorder. Curr Addict Rep. 2020 Sep;7(3):291-300. doi: 10.1007/s40429-020-00318-8. Epub 2020 Jun 11.
citation: Purani H, Friedrichsen S, Allen AM. Sleep quality in cigarette smokers: Associations with smoking-related outcomes and exercise. Addict Behav. 2019 Mar;90:71-76. doi: 10.1016/j.addbeh.2018.10.023. Epub 2018 Oct 17.