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.
This quasi-experimental study aims to develop and evaluate an AI-enhanced smartphone app designed to support adolescents aged 14-20 in quitting e-cigarettes. Given the high prevalence of e-cigarette use among youth, this app-based intervention focuses on providing personalized, real-time support for cravings and motivation to quit. The app integrates interactive features to engage users and is designed for scalability, enabling wide-reaching impact in various settings such as schools, clinics, and communities. Study Phases and Objectives Phase 1: Development and Usability Testing Phase 1 focuses on refining an existing beta version of the app. In this formative stage, the app's design, content, and features will be adjusted based on adolescent feedback to ensure it is user-friendly and engaging. Participants will test the app and provide insights through usability surveys and interviews, which will inform necessary changes. Key activities in this phase include: * Gathering feedback on usability and design. * Modifying app features to better meet the preferences and needs of adolescent users. * Finalizing the app to meet high usability benchmarks for deployment in the next phase. Phase 2: Clinical Feasibility Testing In Phase 2, the app's effectiveness will be tested using a quasi-randomized design with two groups: one group of participants will begin using the app immediately, while the second group will start after a three-month delay. This approach will help determine if earlier access to the intervention leads to improved outcomes in terms of e-cigarette cessation. The study will assess how the app impacts participants' readiness to quit, actual quitting attempts, and ongoing motivation over time. Engagement levels with the app's features, such as real-time craving support and AI-driven educational modules, will also be tracked to evaluate the intervention's overall feasibility and appeal. App Features and Personalization The app's core features include: 1. Goal Setting and Progress Tracking: Users set personal quitting goals, track their progress, and access daily training modules to build skills for managing cravings and quitting. 2. Real-Time Craving Management: The "urge" feature provides immediate support during cravings, using mindfulness exercises and coping strategies tailored to each user's needs. 3. AI Chatbot Support: A chatbot offers 24/7 assistance, answering questions and providing motivation based on users' quitting status and individual characteristics. These AI-driven tools are customized according to user data and interactions within the app, ensuring the intervention feels personal and responsive to each user's progress. Data Collection and Analysis Data will be collected on app usage, engagement with specific features, and changes in e-cigarette use over time. Analysis will include both user feedback and statistical evaluation of the app's impact on participants' quitting success. Insights from this data will contribute to the ongoing refinement of the app and inform its potential for broader use as an adolescent-focused e-cigarette cessation tool. Anticipated Impact This study aims to create a user-friendly, scalable app that leverages AI to support adolescents in quitting e-cigarettes effectively. If successful, this digital intervention could be a valuable resource for youth cessation programs and serve as a model for similar health-related app-based interventions.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Enrollment
100
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.
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.
University at Buffalo, School of Nursing
Buffalo, New York, United States
Usability
The usability of the intervention will be assessed using the mHealth App Usability Questionnaire, a 21-item instrument designed for interactive mobile health apps. It measures three domains: ease of use and satisfaction, system information arrangement, and usefulness. Each item is rated on a 5-point Likert scale, yielding a total score range of 21 to 105, with higher scores indicating better usability. An open-ended question will also be included at the end of the survey to gather suggestions for app improvement.
Time frame: 30-Day Follow-up
Engagement - Frequency of App Use
Automatically recorded log data from the app will track each login event by a participant.
Time frame: 30-Day and 3-Month Follow-up
Engagement - Minutes of App Use
Cumulative minutes of app usage will be captured via app log data.
Time frame: 30-Day and 3-Month Follow-up
E-cigarette Use
Self-reported number of days participants used e-cigarettes in the past 30 days. Responses range from 0 to 30 days.
Time frame: 30-day and 3-month follow up
Quit attempts
Self-reported number of quit attempts in the past 30 days, along with the longest duration of abstinence.
Time frame: 30-Day and 3-Month Follow-up
Readiness to Quit
Readiness to quit will be assessed using a modified Contemplation Ladder. The Contemplation Ladder ranges from 0 (no thought of quitting) to 10 (taking action to quit). Higher scores indicate greater readiness.
Time frame: 30-Day and 3-Month Follow-up
Nicotine Dependence
Measured using the Penn State Electronic Cigarette Dependence Index (PSECDI), a 10-item scale with a total score range of 0 to 20. Higher scores indicate higher levels of nicotine dependence.
Time frame: 30-Day and 3-Month Follow-up
Beliefs About E-Cigarettes
Assessed using a questions from the National Youth Tobacco Survey about e-cigarette harm, addictiveness, and benefits.
Time frame: 30-Day and 3-Month Follow-up
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.