Multi-Theory Model-Based AI Agent Intervention for Smoking Cessation in Early-Stage Cancer Patients

September 17, 2026 updated by: Wei XIA, PhD, Sun Yat-sen University

Construction and Effectiveness of a Multi-Theory Model-Based AI Agent Intervention for Smoking Cessation Among Early-Stage Cancer Patients

The goal of this clinical trial is to evaluate the effectiveness of a Multi-Theory Model (MTM)-based AI agent intervention for smoking cessation in early-stage cancer patients (clinical stage cTNM 0~II) who currently smoke. The main questions it aims to answer are:

Does the AI agent intervention improve the biochemically verified 7-day point prevalence abstinence rate at the 6-month follow-up compared to control groups?

Is the AI agent intervention feasible and acceptable for early-stage cancer patients?

Researchers will compare the AI agent intervention group to an professional counseling group and a routine health education groupto see if the AI agent yields higher smoking cessation rates and better maintenance of abstinence.

Participants will:

Be randomly assigned to one of three groups to receive either AI agent support via WeChat, professional counseling via Phone, or routine health education.

Interact with the AI agent (if in the intervention group) which provides personalized guidance, emotional support, and resource matching based on the Multi-Theory Model constructs (e.g., participatory dialogue, emotional transformation).

Complete questionnaires regarding smoking behavior, nicotine dependence, self-efficacy, and quality of life at baseline and follow-ups (1 week, 1 month, 3 months, and 6 months).

Provide exhaled carbon monoxide (CO) and saliva cotinine samples for biochemical verification if they report successful smoking cessation.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

156

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  1. Age ≥18 years, diagnosed with early-stage cancer (AJCC 8th edition clinical stage cTNM 0-II);
  2. Smoked in the past 30 days, with an average daily consumption of > 1 cigarette, and an exhaled Carbon Monoxide (CO) level ≥ 4 ppm;
  3. Able to communicate using WeChat;
  4. Able to understand and read Chinese, and possess conversational Mandarin skills;
  5. Willing to participate in this study and sign the informed consent form.

Exclusion Criteria:

  1. Individuals who are unable to communicate due to severe mental or physical illness;
  2. Individuals currently participating in other tobacco control research projects;
  3. Individuals whose cancer has metastasized.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: AI Agent Intervention Group

Participants in this group will access a customized "Smoking Cessation AI Agent" via the WeChat platform. The agent utilizes a Large Language Model with Retrieval-Augmented Generation (RAG) to provide professional, evidence-based support grounded in the Multi-Theory Model (MTM).

Key features include:

24/7 Personalized Interaction: Offers open-ended dialogue, personalized advice, and proactive pushes (e.g., health education cards, check-in incentives).

Stage-Matched Guidance:

Initiation Phase: Focuses on participatory dialogue to weigh pros/cons and behavioral confidence building through goal setting.

Maintenance Phase: Focuses on emotional transformation (managing withdrawal/emotions), practice for change, and modifying the social/physical environment (e.g., matching cessation resources, peer support).

Dynamic Adaptation: The agent dynamically adjusts its strategies based on the user's interaction frequency and quitting progress.
Behavioral: MTM-Based AI Agent for smoking cessation

An AI agent powered by a Large Language Model with Retrieval-Augmented Generation (RAG). It provides 24/7 personalized smoking cessation support based on the Multi-Theory Model (MTM).

Key Functions:

Initiation Phase: Participatory dialogue to weigh pros/cons and goal setting to build behavioral confidence.

Maintenance Phase: Emotional transformation support, habit tracking (practice for change), and social/physical environment resource matching (e.g., peer support).

Dynamic Adaptation: Adjusts content and push frequency based on user interaction and quitting stage.
Active Comparator: Counseling Group

Participants in this group receive smoking cessation counseling by WeChat from specialists.

Proactive Intervention: Specialists contact participants twice a month.

Content: Brief counseling (approx. 30 seconds to 5 minutes) based on WHO guidelines, including assessing smoking status, difficulties, and progress, and providing customized advice (e.g., motivation boosting, coping strategies for withdrawal).

Reactive Support: Participants can proactively contact the specialists during working hours (Mon-Fri, 8:00-17:00) for inquiries.
Behavioral: Counseling
WeChat-based counseling provided by smoking cessation specialists twice a month, following WHO guidelines.
No Intervention: Health Education Group

Participants receive standard care only, which consists of routine brief smoking cessation advice from physicians during their regular hospital visits.

This group does not receive any additional active intervention, education, or follow-up counseling from the research team, except for data collection at scheduled follow-up points (baseline, 1 week, 1 month, 3 months, and 6 months).

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Biochemically validated 7-Day Point Prevalence Abstinence Rate
Time Frame: 6 month follow-up after randomization
Participants are considered abstinent if they self-report having smoked 0 cigarettes (not even a puff) in the past 7 days, confirmed by a biochemical validation of exhaled Carbon Monoxide (CO) concentration < 4 ppm and saliva cotinine concentration < 115 ng/ml
6 month follow-up after randomization

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Self-Reported 7-Day Point Prevalence Abstinence Rate
Time Frame: 1 week, 1 month, 3 months, and 6-month follow-up
The proportion of participants who self-report having smoked no cigarettes in the past 7 days, without biochemical verification at interim time points.
1 week, 1 month, 3 months, and 6-month follow-up
Smoking Reduction Rate
Time Frame: 1 week, 1 month, 3 months, and 6-month follow-up
Defined as a reduction in daily cigarette consumption by ≥50% compared to baseline levels.
1 week, 1 month, 3 months, and 6-month follow-up
Change in Smoking Self-Efficacy
Time Frame: Baseline, 1 week, 1 month, 3 months, and 6-months follow-up
Measured using the Smoking Self-Efficacy Questionnaire (SEQ-12). The scale contains 12 items rated on a 5-point Likert scale. Total scores range from 12 to 60, with higher scores indicating greater confidence in the ability to refrain from smoking in various situations.
Baseline, 1 week, 1 month, 3 months, and 6-months follow-up
Change in Quality of Life
Time Frame: Baseline,1 week, 1 month, 3 months, and 6-months follow-up
Health-related quality of life will be assessed using the EuroQol 5-Dimension 5-Level (EQ-5D-5L) questionnaire. The EQ-5D-5L assesses five dimensions of health: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Responses will be converted to an EQ-5D-5L index score using the prespecified value set, with higher scores indicating better health-related quality of life. The outcome will be reported as the change in EQ-5D-5L index score from baseline.
Baseline,1 week, 1 month, 3 months, and 6-months follow-up
Total Duration of AI Agent Use
Time Frame: From randomization through 6 months
AI agent use will be assessed using automatically recorded backend system logs. The cumulative duration of AI agent use for each participant during the follow-up period will be calculated. The unit of measure is minutes.
From randomization through 6 months
Mean AI Agent Response Time
Time Frame: From randomization through 6 months
Mean AI agent response time will be calculated using backend system timestamps as the average time between submission of a participant message and generation of the corresponding AI agent response. The unit of measure is seconds.
From randomization through 6 months
Mean AI Agent Session Duration
Time Frame: From randomization through 6 months
Mean session duration will be calculated from backend system logs as the total duration of AI agent use divided by the number of usage sessions for each participant. The unit of measure is minutes per session.
From randomization through 6 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sun Yat-sen University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

October 1, 2026

Primary Completion (Estimated)

August 1, 2027

Study Completion (Estimated)

August 31, 2027

Study Registration Dates

First Submitted

July 28, 2026

First Submitted That Met QC Criteria

September 17, 2026

First Posted (Actual)

September 18, 2026

Study Record Updates

Last Update Posted (Actual)

September 18, 2026

Last Update Submitted That Met QC Criteria

September 17, 2026

Last Verified

September 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • L2025SYSU-HL-048

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

The data will be shared one year after the results of the study'are published. The researchers can access the data by contacting the PI at xiaw23@mail.sysu.edu.cn with the research purpose described.

IPD Sharing Time Frame

One year after the results of the study are published

IPD Sharing Access Criteria

The researchers can access the data by contacting the PI at xiaw23@mail.sysu.edu.cn with the research purpose described.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP
  • ANALYTIC_CODE

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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