[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100621650":3},{"organization":4,"outcomesModule":7,"designInfo":43,"detailedDescription":46,"studyPopulation":46,"armGroups":52,"interventions":63,"overallOfficials":46,"centralContacts":46,"locations":46,"responsibleParty":69,"collaborators":46,"id":71,"slug":46,"hasResults":72,"nctId":73,"briefTitle":74,"officialTitle":75,"acronym":76,"eligibilityCriteria":77,"healthyVolunteers":72,"sex":78,"minAge":79,"maxAge":80,"enrollmentInfo":81,"targetDuration":46,"studyType":84,"phases":85,"briefSummary":87,"conditions":88,"keywords":90,"overallStatus":94,"whyStopped":46,"lastUpdateSubmitDate":95,"lastUpdatePostDateStruct":96,"startDateStruct":99,"completionDateStruct":101,"leadSponsor":103,"locationsCount":46},{"fullName":5,"class":6},"Peking University","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":38},[9],{"measure":10,"description":11,"timeFrame":12},"Change in Glycosylated Hemoglobin (HbA1c) Levels","Glycosylated Hemoglobin (HbA1c) reflects the average plasma glucose concentration over the preceding 3 months. It serves as the gold standard biomarker for long-term glycemic control in diabetes management. Data will be obtained from venous blood samples collected at community health centers. A lower HbA1c percentage indicates better glycemic control.","Baseline, Month 3, and Month 6",[14,17,20,23,26,29,32,35],{"measure":15,"description":16,"timeFrame":12},"Change in Body Mass Index (BMI)","Calculated as weight in kilograms divided by the square of height in meters (kg\u002Fm\\^2). BMI is used as an indicator of body fatness and weight management status. A lower BMI (within the healthy range) generally indicates better weight control outcomes.",{"measure":18,"description":19,"timeFrame":12},"Change in Blood Pressure","Measured as Systolic and Diastolic Blood Pressure in mmHg using a standard sphygmomanometer. Lower blood pressure values (approaching the normal range) indicate better cardiovascular risk management.",{"measure":21,"description":22,"timeFrame":12},"Incidence of Diabetes Complications","The occurrence of new or worsening diabetes-related complications, including but not limited to neuropathy, retinopathy, nephropathy, and cardiovascular events. Data will be collected through medical record reviews and patient self-reports. A lower incidence rate indicates better disease management",{"measure":24,"description":25,"timeFrame":12},"Quality of Life (EQ-5D-5L)","Assessed using the EuroQol 5-Dimension 5-Level (EQ-5D-5L) questionnaire. It covers five dimensions: mobility, self-care, usual activities, pain\u002Fdiscomfort, and anxiety\u002Fdepression. Responses are converted into a single utility index score ranging from less than 0 to 1. Higher scores indicate better health-related quality of life.",{"measure":27,"description":28,"timeFrame":12},"Self-Management Behaviors (SDSCA)","Assessed using the Summary of Diabetes Self-Care Activities (SDSCA) questionnaire. This instrument measures the frequency of self-care activities (including diet, exercise, blood sugar testing, and foot care) over the past 7 days. Higher scores indicate better adherence to diabetes self-management activities.",{"measure":30,"description":31,"timeFrame":12},"Treatment Satisfaction (DTSQs)","Assessed using the Diabetes Treatment Satisfaction Questionnaire (DTSQs). This tool evaluates the patient's satisfaction with their current treatment regimen, including perception of hyperglycemia\u002Fhypoglycemia and convenience. Higher scores indicate greater satisfaction with the treatment.",{"measure":33,"description":34,"timeFrame":12},"Digital Literacy (C-eHEALS)","Assessed using the Chinese eHealth Literacy Scale (C-eHEALS). This scale measures the participants' combined knowledge, comfort, and perceived skills at finding, evaluating, and applying electronic health information to health problems. Higher scores indicate higher levels of electronic health literacy.",{"measure":36,"description":37,"timeFrame":12},"Medical Costs","Total direct and indirect costs related to diabetes management. Direct costs include expenses for examinations, medications, outpatient\u002Finpatient visits, transportation, and caregiver fees. Indirect costs include caregiver time costs. Data will be collected via patient questionnaires and healthcare utilization records. Lower costs indicate a reduced economic burden.",[39],{"measure":40,"description":41,"timeFrame":42},"Frequency of Dietary Uploads (Adherence)","Measured as the total count of dietary records (photos or text entries) uploaded by each participant via the \"Diet-Medicine Companion\" (Shi Yi Ban Lv) mini-program. Data is automatically logged by the system's backend server. This metric serves as a direct objective indicator of participant engagement and adherence to the intervention protocol (which requires daily uploads). Higher numbers indicate better adherence.","Throughout the 6-month intervention period",{"allocation":44,"interventionModel":45,"interventionModelDescription":46,"primaryPurpose":47,"observationalModel":46,"timePerspective":46,"maskingInfo":48},"RANDOMIZED","PARALLEL",null,"TREATMENT",{"masking":49,"maskingDescription":46,"whoMasked":50},"SINGLE",[51],"OUTCOMES_ASSESSOR",[53,59],{"label":54,"type":55,"description":56,"interventionNames":57},"Intervention","EXPERIMENTAL","Participants in this arm will receive the \"Diet-Medicine Companion\" (Shi Yi Ban Lv) intervention. This involves using an AI-powered WeChat mini-program for daily dietary logging and receiving real-time feedback. Participants also receive proactive monitoring and support from family doctors (case administrators), including telephone reminders if they are inactive for more than 7 days and targeted health guidance based on their data.",[58],"Device: AI-driven Dietary Management and Human-in-the-loop Support",{"label":60,"type":61,"description":62,"interventionNames":46},"Control","NO_INTERVENTION","Participants in this arm will receive standard community care (usual care) for type 2 diabetes management provided by their local community health centers. They will complete the same schedule of assessments (HbA1c tests and questionnaires) at baseline, 3 months, and 6 months but will not receive the AI mini-program intervention or the specific case administrator support provided to the experimental group.",[64],{"type":65,"name":66,"description":67,"armGroupLabels":68,"otherNames":46},"DEVICE","AI-driven Dietary Management and Human-in-the-loop Support","The intervention consists of a 6-month AI-enabled blended care program using the \"Diet-Medicine Companion\" (Shi Yi Ban Lv) WeChat mini-program.\n\nPatient Component (AI Support): Participants are required to upload dietary photos and blood glucose records via the mini-program at least once daily. The system, powered by a Large Language Model (LLM), provides immediate, personalized dietary feedback and answers diabetes-related queries via an AI chatbot.\n\nProvider Component (Human Support): Case administrators (family doctors) monitor patient data through a provider dashboard. The protocol involves \"human-in-the-loop\" support, where doctors provide telephone reminders if participants are inactive (no uploads) for more than 7 days. Doctors also intervene to provide medical guidance or health education based on specific system alerts or patient needs.",[54],{"type":70,"investigatorFullName":46,"investigatorTitle":46,"investigatorAffiliation":46,"oldNameTitle":46,"oldOrganization":46},"SPONSOR","100621650",false,"NCT07373379","Blended Resources for Integrated Diabetes Guidance and Empowerment","Effectiveness and Implementation of an AI-Driven Blended Care Model for Type 2 Diabetes Management in Primary Care: A Single-Blind, Cluster Randomized Controlled Trial in Zhangjiagang, China","BRIDGE","Inclusion Criteria:\n\n* Aged 18 to 70 years (inclusive).\n* Glycosylated hemoglobin (HbA1c) level ≥ 6.5%.\n* Resided in the local area for at least 6 months.\n* Capable of using a smartphone to take photos and use the WeChat mini-program.\n* Willing and able to provide informed consent.\n\nExclusion Criteria:\n\n* Diagnosed with Type 1 diabetes, gestational diabetes, or secondary diabetes.\n* Presence of severe diabetic complications.\n* Received radiotherapy or chemotherapy within the past 6 months.\n* Diagnosed with severe intellectual disabilities, Alzheimer's disease, or other serious psychiatric disorders.\n* Current participation in other research projects that may affect the results of this study.\n* Presence of other severe disabilities or medical conditions deemed unsuitable for participation by the investigators.","ALL","18 Years","70 Years",{"count":82,"type":83},1200,"ESTIMATED","INTERVENTIONAL",[86],"NA","The goal of this cluster randomized clinical trial is to learn if an AI-enabled blended care model (the BRIDGE program) works to treat type 2 diabetes in adults. It will also learn about the cost-effectiveness and implementation feasibility of this model in primary care settings. The main questions it aims to answer are:\n\nDoes the AI-driven intervention lower HbA1c levels (blood sugar) compared to standard care?\n\nDoes this model improve participants' quality of life, self-management behaviors, and digital literacy?\n\nResearchers will compare the \"Diet-Medicine Companion\" (Shi Yi Ban Lv) mini-program combined with family doctor support to standard community care to see if the blended care model works to manage diabetes.\n\nParticipants will:\n\nUse the \"Diet-Medicine Companion\" mini-program to upload diet photos daily and receive AI feedback for 6 months\n\nReceive periodic guidance and phone reminders from case administrators (family doctors)\n\nComplete questionnaires and blood tests (HbA1c) at baseline, 3 months, and 6 months",[89],"Type 2 Diabetes Mellitus",[89,91,92,93],"digital health","AI","blended care","NOT_YET_RECRUITING","2026-02-19",{"date":97,"type":98},"2026-02-23","ACTUAL",{"date":100,"type":83},"2026-03-01",{"date":102,"type":83},"2026-10-30",{"name":5,"class":6}]