[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100619654":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":23,"centralContacts":27,"locations":37,"responsibleParty":55,"collaborators":57,"id":60,"slug":61,"hasResults":62,"nctId":63,"briefTitle":64,"officialTitle":65,"acronym":66,"eligibilityCriteria":67,"healthyVolunteers":62,"sex":68,"minAge":69,"maxAge":10,"enrollmentInfo":70,"targetDuration":10,"studyType":73,"phases":10,"briefSummary":74,"conditions":75,"keywords":77,"overallStatus":40,"whyStopped":10,"lastUpdateSubmitDate":81,"lastUpdatePostDateStruct":82,"startDateStruct":85,"completionDateStruct":87,"leadSponsor":89,"locationsCount":90},{"fullName":5,"class":6},"Northumbria Healthcare NHS Foundation Trust","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Patient-carer dyads",null,"Carers (n=20-30 dyads): Recruited via Northumbria NHS Memory Clinics. Eligible carers will be adults (≥18 years) who know the patient well, have basic English literacy, and can provide informed consent.\n\n• Patients (n=20-30): Individuals (≥65 years) attending a memory clinic for cognitive assessment.\n\n1. Baseline Data Collection:\n\n   * Demographics (age, gender, ethnicity, socioeconomic status).\n   * Clinical diagnosis (where available).\n   * Cognitive test scores (MoCA\u002FACE).\n2. LUMEN Interaction:\n\n   o Carers will use LUMEN on a laptop or tablet to provide structured collateral histories (\\~20-30 min).\n3. Usability and Cognitive Load Assessment:\n\n   * SUS (System Usability Scale): 10-item Likert-scale questionnaire assessing ease of use (score ≥70 = good usability).\n   * NASA-TLX (Task Load Index): Evaluates perceived cognitive workload (scores 0-29 = low workload).\n4. Qualitative Evaluation:\n\n   * Semi-structured interviews (n=10 carers).",[13],"Other: LUMEN prototype software interaction",{"label":15,"type":10,"description":16,"interventionNames":17},"Clinicians","4.1. Participants and Recruitment\n\n• Clinicians (n=8-10): Specialists in dementia care (neurologists, psychiatrists, geriatricians, advanced nurse practitioners) with ≥2 years of experience.\n\n4.2. Study Procedures\n\n1. Baseline Data Collection:\n\n   o Demographics (age, gender, ethnicity, socioeconomic status).\n2. LUMEN Interaction:\n\n   o Clinicians will review LUMEN-generated histories to assess completeness and clinical utility.\n3. Usability and Cognitive Load Assessment:\n\n   * SUS (System Usability Scale): 10-item Likert-scale questionnaire assessing ease of use (score ≥70 = good usability).\n   * NASA-TLX (Task Load Index): Evaluates perceived cognitive workload (scores 0-29 = low workload).\n4. Qualitative Evaluation:\n\n   * Semi-structured interviews (n=4-5 clinicians).",[13],[19],{"type":6,"name":20,"description":21,"armGroupLabels":22,"otherNames":10},"LUMEN prototype software interaction","This is a prototype software which seeks to gather collateral information relevant to a dementia clinical assessment.",[15,9],[24],{"name":25,"affiliation":5,"role":26},"Judith R Harrison, MBChB PhD","PRINCIPAL_INVESTIGATOR",[28,33],{"name":29,"role":30,"phone":31,"phoneExt":10,"email":32},"Judith R Harrison, MBChB","CONTACT","+441912081314","Judith.Harrison@newcastle.ac.uk",{"name":34,"role":30,"phone":35,"phoneExt":10,"email":36},"Lisa Gallagher","+44191 293 4087","Lisa.gallagher@northumbria-healthcaretrust.nhs.uk",[38],{"facility":39,"status":40,"city":41,"state":10,"zip":42,"country":43,"countryCode":44,"cosmosGeoPoint":45,"geoPoint":50,"contacts":51},"North Tyneside General Hospital is Rake Lane","RECRUITING","North Shields","NE29 8NH","United Kingdom","UK",{"type":46,"coordinates":47},"Point",[48,49],-1.44925,55.01646,{"lat":49,"lon":48},[52],{"name":53,"role":30,"phone":35,"phoneExt":10,"email":54},"Lorelle Dismore","lorelle.dismore@northumbria-healthcare.nhs.uk",{"type":56,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[58],{"name":59,"class":6},"Newcastle University","100619654","large-language-model-for-understanding-and-monitoring-elderly-neurocognition-100619654",false,"NCT07347431","Large Language Model for Understanding and Monitoring Elderly Neurocognition","LUMEN (Large Language Model for Understanding and Monitoring Elderly Neurocognition): A Clinical Feasibility Study With Nested Qualitative Evaluation for AI- Assisted Dementia Assessment","LUMEN","Carers of patients attending Memory Clinic appointments; Aged 18 or over; Both patients and cares can provide informed consent; Basic English literacy\n\nClinicians must have at least 2 years of specialist dementia care experience and be personally responsible for dementia diagnosis; Must be provide informed consent","ALL","65 Years",{"count":71,"type":72},60,"ESTIMATED","OBSERVATIONAL","Dementia affects millions of people worldwide, and early diagnosis is essential for getting the right care and support. Doctors rely on collateral histories (accounts from family members or caregivers) to understand changes in a person's memory and thinking. However, these histories can be incomplete, unstructured, or difficult to obtain, making diagnosis more challenging.\n\nThis study will test LUMEN (Large Language Model for Understanding and Monitoring Elderly Neurocognition), an AI-powered conversation tool designed to help caregivers describe their loved one's symptoms more effectively. By asking structured questions and guiding the conversation, LUMEN can create clear, well-organised reports for memory clinic doctors. This could make assessments quicker, more accurate, and less stressful for families.\n\nWe will test LUMEN in real-world clinics by asking caregivers and doctors to use it and provide feedback. We want to understand how easy it is to use, whether it could improve the quality of information shared, and how it fits into existing NHS memory clinic processes. We will also run co-production workshops with community groups to ensure the tool is accessible to people from diverse cultural and language backgrounds.\n\nThis research is exciting because it explores how artificial intelligence can improve dementia care. If successful, LUMEN could enhance the diagnostic process, reduce carer burden, and help more people access dementia support sooner. In the future, this tool could be used nationwide in memory clinics, improving care for thousands of families.",[76],"Dementia",[76,78,79,80],"Alzheimer's Disease","Artificial Intelligence","Large Language Models","2026-04-20",{"date":83,"type":84},"2026-04-21","ACTUAL",{"date":86,"type":84},"2026-03-19",{"date":88,"type":72},"2026-12-31",{"name":5,"class":6},1]