Multi-Theory Model-Based AI Agent Intervention for Smoking Cessation in Early-Stage Cancer Patients
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
AgeNot listed
SponsorSun Yat-sen University
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Age ≥18 years, diagnosed with early-stage cancer (AJCC 8th edition clinical stage cTNM 0-II);
Smoked in the past 30 days, with an average daily consumption of > 1 cigarette, and an exhaled Carbon Monoxide (CO) level ≥ 4 ppm;
Able to communicate using WeChat;
Able to understand and read Chinese, and possess conversational Mandarin skills;
Disqualifiers
Individuals who are unable to communicate due to severe mental or physical illness;
Individuals currently participating in other tobacco control research projects;
Individuals whose cancer has metastasized.
Trial design
Design model
Parallel
Treatments tested in this trial
MTM-Based AI Agent for smoking cessation
BehavioralAn 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.
Counseling
BehavioralWeChat-based counseling provided by smoking cessation specialists twice a month, following WHO guidelines.
Treatment groups
156 Participants
are divided into 3 treatment groupsGroup A: AI Agent Intervention GroupExperimental treatment 1 intervention
Group B: Counseling GroupActive comparator 1 intervention
Group C: Health Education GroupNo intervention 0 interventions
Trial outcomes
Primary outcomes
1
Biochemically validated 7-Day Point Prevalence Abstinence Rate
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
Time frame
6 month follow-up after randomizationSecondary outcomes
1
Self-Reported 7-Day Point Prevalence Abstinence Rate
The proportion of participants who self-report having smoked no cigarettes in the past 7 days, without biochemical verification at interim time points.
Time frame
1 week, 1 month, 3 months, and 6-month follow-up2
Smoking Reduction Rate
Defined as a reduction in daily cigarette consumption by ≥50% compared to baseline levels.
Time frame
1 week, 1 month, 3 months, and 6-month follow-up3
Change in Smoking Self-Efficacy
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.
Time frame
Baseline, 1 week, 1 month, 3 months, and 6-months follow-up4
Change in Quality of Life
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.
Time frame
Baseline,1 week, 1 month, 3 months, and 6-months follow-upLocations
Sponsors and contacts
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Source ClinicalTrials.gov
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