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

17 september 2026 bijgewerkt door: 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.

Studie Overzicht

Toestand

Nog niet aan het werven

Conditie

Interventie / Behandeling

Studietype

Ingrijpend

Inschrijving (Geschat)

156

Fase

  • Niet toepasbaar

Contacten en locaties

In dit gedeelte vindt u de contactgegevens van degenen die het onderzoek uitvoeren en informatie over waar dit onderzoek wordt uitgevoerd.

Studiecontact

Studie Contact Back-up

Deelname Criteria

Onderzoekers zoeken naar mensen die aan een bepaalde beschrijving voldoen, de zogenaamde geschiktheidscriteria. Enkele voorbeelden van deze criteria zijn iemands algemene gezondheidstoestand of eerdere behandelingen.

Geschiktheidscriteria

Leeftijden die in aanmerking komen voor studie

  • Kind
  • Volwassen
  • Oudere volwassene

Accepteert gezonde vrijwilligers

Nee

Beschrijving

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.

Studie plan

Dit gedeelte bevat details van het studieplan, inclusief hoe de studie is opgezet en wat de studie meet.

Hoe is de studie opgezet?

Ontwerpdetails

  • Primair doel: Behandeling
  • Toewijzing: Gerandomiseerd
  • Interventioneel model: Parallelle opdracht
  • Masker: Enkel

Wapens en interventies

Deelnemersgroep / Arm
Interventie / Behandeling
Experimenteel: 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.
Gedragsmatig: 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.
Actieve vergelijker: 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.
Gedragsmatig: Counseling
WeChat-based counseling provided by smoking cessation specialists twice a month, following WHO guidelines.
Geen tussenkomst: 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).

Wat meet het onderzoek?

Primaire uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Biochemically validated 7-Day Point Prevalence Abstinence Rate
Tijdsspanne: 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

Secundaire uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Self-Reported 7-Day Point Prevalence Abstinence Rate
Tijdsspanne: 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
Tijdsspanne: 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
Tijdsspanne: 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
Tijdsspanne: 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
Tijdsspanne: 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
Tijdsspanne: 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
Tijdsspanne: 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

Medewerkers en onderzoekers

Hier vindt u mensen en organisaties die betrokken zijn bij dit onderzoek.

Sponsor

Sun Yat-sen University

Studie record data

Deze datums volgen de voortgang van het onderzoeksdossier en de samenvatting van de ingediende resultaten bij ClinicalTrials.gov. Studieverslagen en gerapporteerde resultaten worden beoordeeld door de National Library of Medicine (NLM) om er zeker van te zijn dat ze voldoen aan specifieke kwaliteitscontrolenormen voordat ze op de openbare website worden geplaatst.

Bestudeer belangrijke data

Studie start (Geschat)

1 oktober 2026

Primaire voltooiing (Geschat)

1 augustus 2027

Studie voltooiing (Geschat)

31 augustus 2027

Studieregistratiedata

Eerst ingediend

28 juli 2026

Eerst ingediend dat voldeed aan de QC-criteria

17 september 2026

Eerst geplaatst (Werkelijk)

18 september 2026

Updates van studierecords

Laatste update geplaatst (Werkelijk)

18 september 2026

Laatste update ingediend die voldeed aan QC-criteria

17 september 2026

Laatst geverifieerd

1 september 2026

Meer informatie

Termen gerelateerd aan deze studie

Trefwoorden

Aanvullende relevante MeSH-voorwaarden

Andere studie-ID-nummers

  • L2025SYSU-HL-048

Plan Individuele Deelnemersgegevens (IPD)

Bent u van plan om gegevens van individuele deelnemers (IPD) te delen?

JA

Beschrijving IPD-plan

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-tijdsbestek voor delen

One year after the results of the study are published

IPD-toegangscriteria voor delen

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

IPD delen Ondersteunend informatietype

  • LEERPROTOCOOL
  • SAP
  • ANALYTIC_CODE

Informatie over medicijnen en apparaten, studiedocumenten

Bestudeert een door de Amerikaanse FDA gereguleerd geneesmiddel

Nee

Bestudeert een door de Amerikaanse FDA gereguleerd apparaatproduct

Nee

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