AI-Enhanced App-based Intervention for Adolescent E-cigarette Cessation

NCT ID: NCT06965296

Last Updated: 2025-09-29

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 100 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2026-01-01
• Study Completion Date: 2028-06-30

Brief 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.

Detailed Description

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.

Conditions

Nicotine Dependence, Cigarettes

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: PREVENTION
• Blinding Strategy: NONE

Study Groups

Immediate-Intervention Group

Participants in this arm will begin using the AI-enhanced smartphone app immediately after enrollment. This arm serves to assess the initial impact and feasibility of the app as a tool for e-cigarette cessation among adolescents.

Group Type: EXPERIMENTAL

AI-enhanced smartphone app

Intervention Type: BEHAVIORAL

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.

Delayed-Intervention Group

Participants in this arm will wait three months after enrollment before using the AI-enhanced smartphone app. This arm serves as a delayed control, allowing comparison with the immediate-intervention group to understand the impact of timing on quitting success.

Group Type: ACTIVE_COMPARATOR

AI-enhanced smartphone app, but with delayed access

Intervention Type: BEHAVIORAL

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.

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.

Intervention Type: BEHAVIORAL

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.

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

• Adolescents who are 14 to 20 years old
• Currently use nicotine-containing e-cigarettes (those responding "Yes" to: Have you used an electronic vaping product such as PuffBar, ElfBar, Lost Mary, JUUL, Vuse, e-cigarettes, vapes, vape pens, e-cigars, e-hookahs, hookah pens, or mods at least 1 day in the last 30 days? [CDC, 2020])
• Interested in participating in an e-cigarette use cessation program
• Owners of an iPhone or Android smartphone who use their phone daily
• Able to read English

Exclusion Criteria

• Individuals who fall outside the age range of 14 to 20 years
• Those who have not used a nicotine-containing e-cigarette in the past 30 days
• Individuals not interested in participating in an e-cigarette cessation program
• Adolescents who do not own or regularly use an iPhone or Android smartphone
• Non-English speakers

• Minimum Eligible Age: 14 Years
• Maximum Eligible Age: 20 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

National Cancer Institute (NCI)

NIH

Sponsor Role: collaborator

Advanced Bionics

INDUSTRY

Sponsor Role: collaborator

State University of New York at Buffalo

OTHER

Sponsor Role: lead

Responsible Party

Eunhee Park

Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

University at Buffalo, School of Nursing

Buffalo, New York, United States

Countries

United States

Central Contacts

Eunhee Park, PhD, RN, APHN-BC

Role: CONTACT

eunheepa@buffalo.edu

716-829-3701

Facility Contacts

Eunhee Park, PhD, RN, APHN-BC

Role: primary

eunheepa@buffalo.edu

716-829-3701

References

Hebert ET, Ra CK, Alexander AC, Helt A, Moisiuc R, Kendzor DE, Vidrine DJ, Funk-Lawler RK, Businelle MS. A Mobile Just-in-Time Adaptive Intervention for Smoking Cessation: Pilot Randomized Controlled Trial. J Med Internet Res. 2020 Mar 9;22(3):e16907. doi: 10.2196/16907.

Reference Type: BACKGROUND

PMID: 32149716 (View on PubMed)

Billingham SA, Whitehead AL, Julious SA. An audit of sample sizes for pilot and feasibility trials being undertaken in the United Kingdom registered in the United Kingdom Clinical Research Network database. BMC Med Res Methodol. 2013 Aug 20;13:104. doi: 10.1186/1471-2288-13-104.

Reference Type: BACKGROUND

PMID: 23961782 (View on PubMed)

Bell ML, Whitehead AL, Julious SA. Guidance for using pilot studies to inform the design of intervention trials with continuous outcomes. Clin Epidemiol. 2018 Jan 18;10:153-157. doi: 10.2147/CLEP.S146397. eCollection 2018.

Reference Type: BACKGROUND

PMID: 29403314 (View on PubMed)

Baskerville NB, Struik LL, Guindon GE, Norman CD, Whittaker R, Burns C, Hammond D, Dash D, Brown KS. Effect of a Mobile Phone Intervention on Quitting Smoking in a Young Adult Population of Smokers: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2018 Oct 23;6(10):e10893. doi: 10.2196/10893.

Reference Type: BACKGROUND

PMID: 30355563 (View on PubMed)

Audrain-McGovern J, Rodriguez D, Pianin S, Alexander E. Initial e-cigarette flavoring and nicotine exposure and e-cigarette uptake among adolescents. Drug Alcohol Depend. 2019 Sep 1;202:149-155. doi: 10.1016/j.drugalcdep.2019.04.037. Epub 2019 Jul 19.

Reference Type: BACKGROUND

PMID: 31351341 (View on PubMed)

Provided Documents

Document Type: Study Protocol

View Document

Other Identifiers

1R34CA287720-01A1

Identifier Type: NIH

Identifier Source: org_study_id

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