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

17. september 2026 oppdatert av: 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.

Studieoversikt

Status

Har ikke rekruttert ennå

Forhold

Intervensjon / Behandling

Studietype

Intervensjonell

Registrering (Antatt)

156

Fase

  • Ikke aktuelt

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiekontakt

Studer Kontakt Backup

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

  • Barn
  • Voksen
  • Eldre voksen

Tar imot friske frivillige

Nei

Beskrivelse

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.

Studieplan

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

  • Primært formål: Behandling
  • Tildeling: Randomisert
  • Intervensjonsmodell: Parallell tildeling
  • Masking: Enkelt

Våpen og intervensjoner

Deltakergruppe / Arm
Intervensjon / Behandling
Eksperimentell: 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.
Atferdsmessig: 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.
Aktiv komparator: 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.
Atferdsmessig: Counseling
WeChat-based counseling provided by smoking cessation specialists twice a month, following WHO guidelines.
Ingen inngripen: 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).

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Biochemically validated 7-Day Point Prevalence Abstinence Rate
Tidsramme: 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

Sekundære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Self-Reported 7-Day Point Prevalence Abstinence Rate
Tidsramme: 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
Tidsramme: 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
Tidsramme: 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
Tidsramme: 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
Tidsramme: 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
Tidsramme: 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
Tidsramme: 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

Samarbeidspartnere og etterforskere

Det er her du vil finne personer og organisasjoner som er involvert i denne studien.

Sponsor

Sun Yat-sen University

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Antatt)

1. oktober 2026

Primær fullføring (Antatt)

1. august 2027

Studiet fullført (Antatt)

31. august 2027

Datoer for studieregistrering

Først innsendt

28. juli 2026

Først innsendt som oppfylte QC-kriteriene

17. september 2026

Først lagt ut (Faktiske)

18. september 2026

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

18. september 2026

Siste oppdatering sendt inn som oppfylte QC-kriteriene

17. september 2026

Sist bekreftet

1. september 2026

Mer informasjon

Begreper knyttet til denne studien

Nøkkelord

Ytterligere relevante MeSH-vilkår

Andre studie-ID-numre

  • L2025SYSU-HL-048

Plan for individuelle deltakerdata (IPD)

Planlegger du å dele individuelle deltakerdata (IPD)?

JA

IPD-planbeskrivelse

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-delingstidsramme

One year after the results of the study are published

Tilgangskriterier for IPD-deling

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

IPD-deling Støtteinformasjonstype

  • STUDY_PROTOCOL
  • SEVJE
  • ANALYTIC_CODE

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Nei

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