[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"wearables\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:wearables":28},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,2,0,[8,50],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":13,"acronym":4,"eligibilityCriteria":14,"healthyVolunteers":11,"sex":15,"minAge":16,"maxAge":4,"enrollmentInfo":17,"targetDuration":4,"studyType":20,"phases":21,"briefSummary":23,"conditions":24,"keywords":32,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":39,"lastUpdatePostDateStruct":40,"startDateStruct":43,"completionDateStruct":45,"leadSponsor":47,"locationsCount":5},"100608933","evaluating-health-outcomes-of-ai-based-fitness-wearables-and-app-programs-in-older-adults-living-alone-with-cognitive-decline-100608933",false,"NCT07207993","Evaluating Health Outcomes of AI-Based Fitness Wearables and App Programs in Older Adults Living Alone With Cognitive Decline","Inclusion Criteria:\n\n* Participant must be at least 65 years of age older\n* Participant must be living alone in the U.S. for the next 6 months\n* Participant must have report mild cognitive decline \\[We will use a short self-report AD8 measure of cognitive concerns. Those scoring positive on the AD8 (≥2) will qualify as mild cognitive decline\\];\n* Participant must own an Android\u002FApple smartphone\n* Participant must have access to internet or Wi-Fi access\n* Participant must be capable of engaging in some PA as determined by the PA Readiness Questionnaire or physician approval\n* Participant must currently participate in weekly moderate-to-vigorous PA (MVPA) or less than 150 minutes\n* Participant must have basic English communication skills.\n\nExclusion Criteria:\n\n* Foreign residents or visitors","ALL","65 Years",{"count":18,"type":19},64,"ESTIMATED","INTERVENTIONAL",[22],"NA","The overarching goal of our research is to develop personalized and accessible healthy aging lifestyle interventions aimed at promoting physical activity (PA) and improving health among community-dwelling older adults living alone with cognitive decline (LACD). To achieve this goal, the purpose of this project is to determine whether wearable and app-based mHealth intervention component(s) will contribute to increased PA and improved health outcomes in older adults LACD. Our specific aims are to: identify and evaluate mHealth intervention components that practically and significantly contribute to enhanced mechanistic outcomes (e.g., self-efficacy, outcome expectations) and increased PA (primary outcome) in older adults LACD over a 6-month period; determine the optimal combinations of intervention components for future efficacy testing; elucidate the mechanism of behavioral change (MoBC) and potential outcomes of these intervention components, namely, the mediating effects of MoBC variables (e.g., self-efficacy, outcome expectations) on the relationship between intervention components and change in PA. The first two aims are primary and fully-powered. The third aim is exploratory. The aims will support a refined, data-driven intervention design for a subsequent larger trial.",[25,26,27,28,29,30,31],"Older Adults With Cognitive Decline","Older Adults","AI-Based Fitness","Wearables","Cognitive Decline","Physical Activity","Physical Inactivity",[33,34,27,30,31,35,36,37],"Older adults","Cognitive decline","Living alone with cognitive decline","LACD","U.S Older adults","RECRUITING","2026-06-10",{"date":41,"type":42},"2026-06-15","ACTUAL",{"date":44,"type":42},"2026-06-08",{"date":46,"type":19},"2028-06-08",{"name":48,"class":49},"The University of Tennessee, Knoxville","OTHER",{"id":51,"slug":52,"hasResults":11,"nctId":53,"briefTitle":54,"officialTitle":55,"acronym":56,"eligibilityCriteria":57,"healthyVolunteers":58,"sex":15,"minAge":59,"maxAge":16,"enrollmentInfo":60,"targetDuration":4,"studyType":20,"phases":62,"briefSummary":63,"conditions":64,"keywords":71,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":76,"lastUpdatePostDateStruct":77,"startDateStruct":79,"completionDateStruct":81,"leadSponsor":83,"locationsCount":85},"100546699","identifying-wearable-biomarkers-to-monitor-dietary-intake-100546699","NCT06398340","Identifying Wearable Biomarkers to Monitor Dietary Intake","Identifying Physiological Biomarkers for Monitoring Dietary Behaviours","FoodSense","Inclusion Criteria:\n\n* Male or female\n* Age between 18-65 years (inclusive)\n* Body mass index (BMI) of 18-30 kg\u002Fm2\n* Willingness and ability to give written informed consent.\n* Willingness and ability to understand, to participate and to comply with the study requirements\n\nExclusion Criteria:\n\n* Outside of specified age and BMI range\n* Chronic medical conditions including for eating disorders, diabetes, obesity, hypertension, cancer, acute infectious disease, renal disease, cardiovascular disease, and chronic gastrointestinal condition.\n* Taking part in another research study or donating any blood in the last 3 months",true,"18 Years",{"count":61,"type":19},10,[22],"Background: Measuring what people eat is a challenge in nutrition research. Traditional methods, like food diaries, rely on self-reporting of individuals, and suffer from poor accuracy and recall bias.\n\nAims: This project aims to identify physiological biomarkers related to food and energy intake, which may be used to develop an objective tool to estimate individuals' food intake in future. Eating behaviours are accompanied by significant physiological changes such as skin temperature, blood oxygen saturation, pulse rate etc. The investigators intend to investigate whether monitoring these physiological changes can help us estimate eating behaviour, such as meal size, eating speed, and duration of meals.\n\nStudy design: Ten healthy adults will be invited for two study visits at NIHR Imperial Clinical Research Facility. Each visit will last for approximately 2 hr. They will consume a high- and low-calorie meal designed by nutritional researchers in a randomised order. During eating events, the investigators will track their physiological changes via a bedside monitor and wearable sensors. Blood samples will be taken from participants to measure their glycaemic response. Associations between energy load, glycaemic response, and physiological changes will be investigated. Our findings may promote an accelerated development of a wearable tool for dietary assessment in future.",[65,66,67,28,68,69,70],"Energy Intake","Metabolism","Digestion","Dietary Intake Assessment","Healthy Volunteers","Blood Glucose",[72,73,74,75],"Dietary intake monitoring","wearable sensors","digital health","blood glucose","2025-02-17",{"date":78,"type":42},"2025-02-18",{"date":80,"type":42},"2024-08-19",{"date":82,"type":19},"2025-07-31",{"name":84,"class":49},"Imperial College London",1]