Clinical Research Directory
Browse clinical research sites, groups, and studies.
AI-Enhanced App-based Intervention for Adolescent E-cigarette Cessation
Sponsor: State University of New York at Buffalo
Summary
The goal of this quasi-experimental study is to test if a smartphone app can help adolescents aged 14-20 quit e-cigarettes. The main questions it aims to answer are: * Can the app help adolescents manage cravings and increase their readiness to quit? * Does the personalized and real-time support provided by the app improve their success in quitting e-cigarettes? Researchers will compare two groups: an immediate-intervention group that starts using the app right away and a delayed-intervention group that begins after three months, to see if the timing of app access influences outcomes in e-cigarette cessation. Participants will: * Set personal goals and track their daily progress within the app. * Use a real-time "urge" feature that provides immediate support during cravings. * Engage with a chatbot for quick answers and motivational support around quitting. This study aims to create an accessible, personalized tool to help adolescents reduce or quit e-cigarette use, exploring its feasibility as a broader intervention model.
Key Details
Gender
All
Age Range
14 Years - 20 Years
Study Type
INTERVENTIONAL
Enrollment
100
Start Date
2026-04-01
Completion Date
2028-06
Last Updated
2026-02-19
Healthy Volunteers
No
Conditions
Interventions
AI-enhanced smartphone app
A smartphone app has been developed and is in keeping with guideline recommendations for the treatment of e-cigarette products. This app has a user-friendly Graphic User Interface (GUI) to allow users to build their own accounts and individualized contents conveniently, based on the input the users initially provide including e-cigarette use patterns, readiness to quit e-cigarette, beliefs about e-cigarette, nicotine addiction, self-efficacy, other substance use status, and parental or peer e-cigarette use status. The proposed AI model in this app will learn information from the input data, including progress toward e-cigarette cessation (e,g, changes of readiness of quitting, quit attempts), and additional data including emotional status, stress level, feedback to the previous learning modules, and then predict the result on the fly. Based on the predicted result, the app will send in-time motivational messages and mindfulness training modules.
AI-enhanced smartphone app, but with delayed access
Participants in the control group will be placed on a three-month waitlist. After this period, they will receive access to the same app-based intervention as the immediate intervention group, allowing a comparison between immediate and delayed access.
Locations (1)
University at Buffalo, School of Nursing
Buffalo, New York, United States