[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100656618":3},{"organization":4,"outcomesModule":7,"designInfo":40,"detailedDescription":39,"studyPopulation":39,"armGroups":49,"interventions":66,"overallOfficials":39,"centralContacts":76,"locations":39,"responsibleParty":86,"collaborators":39,"id":90,"slug":91,"hasResults":92,"nctId":93,"briefTitle":94,"officialTitle":95,"acronym":39,"eligibilityCriteria":96,"healthyVolunteers":92,"sex":97,"minAge":39,"maxAge":39,"enrollmentInfo":98,"targetDuration":39,"studyType":101,"phases":102,"briefSummary":104,"conditions":105,"keywords":109,"overallStatus":113,"whyStopped":39,"lastUpdateSubmitDate":114,"lastUpdatePostDateStruct":115,"startDateStruct":118,"completionDateStruct":120,"leadSponsor":122,"locationsCount":39},{"fullName":5,"class":6},"Sun Yat-sen University","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":39},[9],{"measure":10,"description":11,"timeFrame":12},"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 \\\u003C 4 ppm and saliva cotinine concentration \\\u003C 115 ng\u002Fml","6 month follow-up after randomization",[14,18,21,25,29,33,36],{"measure":15,"description":16,"timeFrame":17},"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.","1 week, 1 month, 3 months, and 6-month follow-up",{"measure":19,"description":20,"timeFrame":17},"Smoking Reduction Rate","Defined as a reduction in daily cigarette consumption by ≥50% compared to baseline levels.",{"measure":22,"description":23,"timeFrame":24},"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.","Baseline, 1 week, 1 month, 3 months, and 6-months follow-up",{"measure":26,"description":27,"timeFrame":28},"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\u002Fdiscomfort, and anxiety\u002Fdepression. 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",{"measure":30,"description":31,"timeFrame":32},"Total Duration of AI Agent Use","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",{"measure":34,"description":35,"timeFrame":32},"Mean AI Agent Response Time","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.",{"measure":37,"description":38,"timeFrame":32},"Mean AI Agent Session Duration","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.",null,{"allocation":41,"interventionModel":42,"interventionModelDescription":43,"primaryPurpose":44,"observationalModel":39,"timePerspective":39,"maskingInfo":45},"RANDOMIZED","PARALLEL","This study is a three-arm, parallel-group randomized controlled trial (RCT). Eligible participants will be randomized in a 1:1:1 ratio to one of three groups: the AI Agent intervention group, the professional counseling group (active control), or the routine health education group (blank control). All groups will receive their respective interventions (or standard care) concurrently and will be followed up for 6 months.","TREATMENT",{"masking":46,"maskingDescription":39,"whoMasked":47},"SINGLE",[48],"PARTICIPANT",[50,56,62],{"label":51,"type":52,"description":53,"interventionNames":54},"AI Agent Intervention Group","EXPERIMENTAL","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).\n\nKey features include:\n\n24\u002F7 Personalized Interaction: Offers open-ended dialogue, personalized advice, and proactive pushes (e.g., health education cards, check-in incentives).\n\nStage-Matched Guidance:\n\nInitiation Phase: Focuses on participatory dialogue to weigh pros\u002Fcons and behavioral confidence building through goal setting.\n\nMaintenance Phase: Focuses on emotional transformation (managing withdrawal\u002Femotions), practice for change, and modifying the social\u002Fphysical environment (e.g., matching cessation resources, peer support).\n\nDynamic Adaptation: The agent dynamically adjusts its strategies based on the user's interaction frequency and quitting progress.",[55],"Behavioral: MTM-Based AI Agent for smoking cessation",{"label":57,"type":58,"description":59,"interventionNames":60},"Counseling Group","ACTIVE_COMPARATOR","Participants in this group receive smoking cessation counseling by WeChat from specialists.\n\nProactive Intervention: Specialists contact participants twice a month.\n\nContent: 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).\n\nReactive Support: Participants can proactively contact the specialists during working hours (Mon-Fri, 8:00-17:00) for inquiries.",[61],"Behavioral: Counseling",{"label":63,"type":64,"description":65,"interventionNames":39},"Health Education Group","NO_INTERVENTION","Participants receive standard care only, which consists of routine brief smoking cessation advice from physicians during their regular hospital visits.\n\nThis 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).",[67,72],{"type":68,"name":69,"description":70,"armGroupLabels":71,"otherNames":39},"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\u002F7 personalized smoking cessation support based on the Multi-Theory Model (MTM).\n\nKey Functions:\n\nInitiation Phase: Participatory dialogue to weigh pros\u002Fcons and goal setting to build behavioral confidence.\n\nMaintenance Phase: Emotional transformation support, habit tracking (practice for change), and social\u002Fphysical environment resource matching (e.g., peer support).\n\nDynamic Adaptation: Adjusts content and push frequency based on user interaction and quitting stage.",[51],{"type":68,"name":73,"description":74,"armGroupLabels":75,"otherNames":39},"Counseling","WeChat-based counseling provided by smoking cessation specialists twice a month, following WHO guidelines.",[57],[77,82],{"name":78,"role":79,"phone":80,"phoneExt":39,"email":81},"Wei Xia, PhD","CONTACT","8618823359471","xiaw23@mail.sysu.edu.cn",{"name":83,"role":79,"phone":84,"phoneExt":39,"email":85},"Jiebing Luo","8618885639072","luojiebing2002@163.com",{"type":87,"investigatorFullName":88,"investigatorTitle":89,"investigatorAffiliation":5,"oldNameTitle":39,"oldOrganization":39},"PRINCIPAL_INVESTIGATOR","Wei XIA, PhD","Associate Professor","100656618","multi-theory-model-based-ai-agent-intervention-for-smoking-cessation-in-early-stage-cancer-patients-100656618",false,"NCT07827066","Multi-Theory Model-Based AI Agent Intervention for Smoking Cessation in Early-Stage Cancer Patients","Construction and Effectiveness of a Multi-Theory Model-Based AI Agent Intervention for Smoking Cessation Among Early-Stage Cancer Patients","Inclusion Criteria:\n\n1. Age ≥18 years, diagnosed with early-stage cancer (AJCC 8th edition clinical stage cTNM 0-II);\n2. Smoked in the past 30 days, with an average daily consumption of \\> 1 cigarette, and an exhaled Carbon Monoxide (CO) level ≥ 4 ppm;\n3. Able to communicate using WeChat;\n4. Able to understand and read Chinese, and possess conversational Mandarin skills;\n5. Willing to participate in this study and sign the informed consent form.\n\nExclusion Criteria:\n\n1. Individuals who are unable to communicate due to severe mental or physical illness;\n2. Individuals currently participating in other tobacco control research projects;\n3. Individuals whose cancer has metastasized.","ALL",{"count":99,"type":100},156,"ESTIMATED","INTERVENTIONAL",[103],"NA","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:\n\nDoes the AI agent intervention improve the biochemically verified 7-day point prevalence abstinence rate at the 6-month follow-up compared to control groups?\n\nIs the AI agent intervention feasible and acceptable for early-stage cancer patients?\n\nResearchers 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.\n\nParticipants will:\n\nBe randomly assigned to one of three groups to receive either AI agent support via WeChat, professional counseling via Phone, or routine health education.\n\nInteract 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).\n\nComplete 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).\n\nProvide exhaled carbon monoxide (CO) and saliva cotinine samples for biochemical verification if they report successful smoking cessation.",[106,107,108],"Smoking Cessation","Early-Stage Cancer","AI Agent",[108,110,111,112],"Multi-Theory Model","Tobacco Cessation","Mobile Health","NOT_YET_RECRUITING","2026-09-17",{"date":116,"type":117},"2026-09-18","ACTUAL",{"date":119,"type":100},"2026-10-01",{"date":121,"type":100},"2027-08-31",{"name":5,"class":6}]