[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100634581":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":12,"locations":19,"responsibleParty":36,"collaborators":10,"id":38,"slug":39,"hasResults":40,"nctId":41,"briefTitle":42,"officialTitle":43,"acronym":10,"eligibilityCriteria":44,"healthyVolunteers":45,"sex":46,"minAge":47,"maxAge":10,"enrollmentInfo":48,"targetDuration":51,"studyType":52,"phases":10,"briefSummary":53,"conditions":54,"keywords":57,"overallStatus":22,"whyStopped":10,"lastUpdateSubmitDate":65,"lastUpdatePostDateStruct":66,"startDateStruct":69,"completionDateStruct":71,"leadSponsor":73,"locationsCount":74},{"fullName":5,"class":6},"National Health Research Institutes, Taiwan","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":10},"Community-Dwelling Adults",null,"Adults aged 18 years and older recruited from community settings in Taiwan. Participants will complete a structured questionnaire, undergo hearing assessment, wear a smartwatch for 2 weeks, and authorize collection of personal health records and linked national health insurance data for health outcome follow-up.",[13],{"name":14,"role":15,"phone":16,"phoneExt":17,"email":18},"Ren-Hua Chung, PhD","CONTACT","886-37206166","36105","rchung@nhri.edu.tw",[20],{"facility":21,"status":22,"city":23,"state":24,"zip":25,"country":26,"countryCode":27,"cosmosGeoPoint":28,"geoPoint":33,"contacts":34},"National Health Research Institutes","RECRUITING","Zhunan","Miaoli","350","Taiwan","TW",{"type":29,"coordinates":30},"Point",[31,32],120.54147,22.57358,{"lat":32,"lon":31},[35],{"name":14,"role":15,"phone":16,"phoneExt":17,"email":18},{"type":37,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100634581","adult-disease-risk-prediction-using-wearables-hearing-and-health-data-100634581",false,"NCT07541547","Adult Disease Risk Prediction Using Wearables, Hearing, and Health Data","A Study to Build a Disease Risk Prediction Model for Adults by Integrating Data From Wearable Devices, Hearing Tests, and Multiple Health Databases","Inclusion Criteria:\n\n* Adults aged 18 years and older\n* Living in the community in Taiwan\n* Able to understand the study procedures and provide written informed consent\n* Able and willing to complete the study questionnaire, hearing assessment, and wearable device monitoring procedures\n* Has access to a smartphone and is able to install and use the study-related application, with assistance from study staff if needed\n\nExclusion Criteria:\n\n* Diagnosis of dementia\n* Too frail or has other health conditions that make participation in the study procedures not feasible\n* Bilateral deafness without use of any hearing assistive device\n* Does not have a smartphone or is unable to use a smartphone application required for the study procedures",true,"ALL","18 Years",{"count":49,"type":50},1500,"ESTIMATED","2 Weeks","OBSERVATIONAL","This prospective cohort study aims to develop and validate a personalized disease risk prediction model for adults by integrating multiple sources of health data. The study will recruit community-dwelling adults aged 18 years and older in Taiwan. After providing informed consent, participants will complete a structured questionnaire, undergo pure tone hearing testing, and wear a smartwatch for 2 weeks to collect continuous physiological data, including heart rate and physical activity. With participant authorization, the study will also collect data from personal health records and national health insurance databases to allow longer-term follow-up of health outcomes.\n\nThe main goals of the study are to examine the relationships among hearing, lifestyle factors, and wearable device data; to identify combinations of risk factors associated with progression from health to subclinical or chronic disease states; and to develop analytical methods for integrating heterogeneous health data from questionnaires, physiological monitoring, hearing tests, and medical databases. Machine learning methods will be used to identify important predictors and build risk prediction models.\n\nThe study hypothesis is that combining hearing measures, lifestyle information, wearable physiological data, and longitudinal medical record data will improve the ability to identify individuals at higher risk of future disease compared with using a single source of information alone. The long-term objective is to support early risk identification, personalized health management, and prevention strategies in community adults.",[55,56],"Chronic Disease","Risk Assessment",[58,56,55,59,60,61,62,63,64],"Wearable Devices","Disease Prediction","Machine Learning","Cohort Studies","Physiological Monitoring","Personal Health Records","Health Insurance Claims","2026-04-13",{"date":67,"type":68},"2026-04-21","ACTUAL",{"date":70,"type":68},"2026-01-09",{"date":72,"type":50},"2029-01",{"name":5,"class":6},1]