Ignite Creation Date:
2025-12-25 @ 4:35 AM
Ignite Modification Date:
2025-12-26 @ 3:37 AM
Study NCT ID:
NCT06450418
Status:
RECRUITING
Last Update Posted:
2025-09-18
First Post:
2024-02-09
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Digital App for Speech & Health Monitoring
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003704', 'term': 'Dementia'}, {'id': 'D016472', 'term': 'Motor Neuron Disease'}, {'id': 'D009103', 'term': 'Multiple Sclerosis'}, {'id': 'D010300', 'term': 'Parkinson Disease'}], 'ancestors': [{'id': 'D001927', 'term': 'Brain Diseases'}, {'id': 'D002493', 'term': 'Central Nervous System Diseases'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D019965', 'term': 'Neurocognitive Disorders'}, {'id': 'D001523', 'term': 'Mental Disorders'}, {'id': 'D019636', 'term': 'Neurodegenerative Diseases'}, {'id': 'D009468', 'term': 'Neuromuscular Diseases'}, {'id': 'D020278', 'term': 'Demyelinating Autoimmune Diseases, CNS'}, {'id': 'D020274', 'term': 'Autoimmune Diseases of the Nervous System'}, {'id': 'D003711', 'term': 'Demyelinating Diseases'}, {'id': 'D001327', 'term': 'Autoimmune Diseases'}, {'id': 'D007154', 'term': 'Immune System Diseases'}, {'id': 'D020734', 'term': 'Parkinsonian Disorders'}, {'id': 'D001480', 'term': 'Basal Ganglia Diseases'}, {'id': 'D009069', 'term': 'Movement Disorders'}, {'id': 'D000080874', 'term': 'Synucleinopathies'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITHOUT_DNA', 'description': 'Participants can additionally and optionally consent for blood samples to be obtained during the study. These samples will be collected and stored with the intention of exploring emerging blood-based biomarkers.'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 150}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2024-07-12', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-09', 'completionDateStruct': {'date': '2026-06', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-09-17', 'studyFirstSubmitDate': '2024-02-09', 'studyFirstSubmitQcDate': '2024-06-03', 'lastUpdatePostDateStruct': {'date': '2025-09-18', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2024-06-10', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-06', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Primary outcome measures', 'timeFrame': '24 months', 'description': 'Area under the curve (AUC) of the receiver operating characteristic (ROC) curve for each of the 4 binary classifiers distinguishing between a disease-positive group and a healthy control group.'}], 'secondaryOutcomes': [{'measure': 'Secondary outcome measure', 'timeFrame': '24 months', 'description': 'Sensitivity, specificity, positive and negative predictive values for each of the 4 binary classifiers distinguishing between a disease-positive group and a healthy control group.'}, {'measure': 'Secondary outcome measure', 'timeFrame': '24 months', 'description': 'Mean squared error of 4 regression models making predictions of condition-specific clinical rating scores (ACE-III, ALSFRS-R, EDSS, MDS-UPDRS)'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Dementia', 'Motor Neuron Disease', 'Multiple Sclerosis', 'Parkinson Disease']}, 'referencesModule': {'references': [{'pmid': '41360452', 'type': 'DERIVED', 'citation': 'Tam J, Weaver C, Ihenacho A, Newton J, Virgo B, Barrett S, Neale J, Perry D, Smith A, Chandran S, Watts O, Pal S; DASH Consortium. Digital App for Speech and Health Monitoring Study (DASH): protocol for a prospective longitudinal case-control observational study for developing speech datasets in neurodegenerative disorders and dementia. BMJ Open. 2025 Dec 5;15(12):e100222. doi: 10.1136/bmjopen-2025-100222.'}]}, 'descriptionModule': {'briefSummary': "Many people living with neurodegenerative conditions like dementia, motor neuron disease (MND), multiple sclerosis (MS), and Parkinson's disease (PD), suffer from speech problems. Using common digital technologies such as smartphone apps, the investigators can record and analyse speech in detail to provide new information for people living with these conditions, researchers, and healthcare professionals. This study will investigate the use of these digital speech recordings to help diagnose and monitor these conditions.\n\nTo take part, participants will have either a diagnosis of dementia, motor neuron disease, Parkinson's disease or Multiple Sclerosis, OR they will have no diagnosis of a neurological condition. Researchers will compare people with a diagnosis of a Neurological condition to those without.", 'detailedDescription': "This project aims to create novel speech-based solutions for: 1) Early detection, 2) Monitoring and 3) Stratification of neurodegenerative disorders including dementia, motor neuron disease (MND), Parkinson's disease (PD), and multiple sclerosis(MS). The investigators will develop and validate proof of concept and early-stage algorithms derived from acoustic data, which will be scaled and tested in deeply-phenotyped population.\n\n2.2 Objectives Primary Objectives\n\n1. To deploy and iterate a digital platform, co-produced with people living with neurodegenerative disorders, for acquisition of speech data from well characterised cohorts of people living with neurodegenerative disorders (dementia, motor neuron disease, multiple sclerosis, Parkinson's disease), and a healthy control cohort (comprising relatives/carers and volunteers without a neurological diagnosis), linked to our highly curated clinical registries at the Anne Rowling Regenerative Neurology Clinic.\n2. To collect a large body of acoustic speech data from well characterised cohorts of people living with neurodegenerative disorders (dementia, MND/ALS, multiple sclerosis, Parkinson's disease), and a healthy control cohort (comprising relatives/carers and volunteers without a neurological diagnosis), linked to highly curated clinical registries.\n3. To apply machine learning approaches directly to acoustic and linguistic signals from voices from people with dementia, MND, MS, Parkinson's, and healthy controls (comprising relatives/carers and volunteers without a neurological diagnosis), and to characterise prosodic patterns (rhythm, intonation, and fluency) without explicit reference to the text which is spoken, providing powerful cues about the health of the speaker.\n4. Compare speech based digital outcome measures to current clinical standards to characterise and validate their clinimetric properties.\n\nSecondary Objectives\n\n1. Assess the feasibility and acceptability of a digital outcome measure platform in people living with neurodegenerative conditions, for use in clinical care and research.\n2. To create a repository of well characterised acoustic voice samples for open access sharing/collaboration with research and industry partners."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'minimumAge': '16 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Participants with Neurodegenerative Disorders and their relatives or carers without a diagnosis of a Neurodegenerative disorder.', 'healthyVolunteers': True, 'eligibilityCriteria': "Inclusion Criteria - Any one of the following:\n\n* A person with a diagnosis of Motor Neuron Disease, Dementia, Multiple Sclerosis, or Parkinson's Disease.\n* A relative or carer of the above who does not report to have a neurological condition.\n* A healthy volunteer who does not report to have a neurological condition.\n\nExclusion Criteria:\n\n* Age \\<16 years\n* Significant and uncorrected visual or hearing impairment (precluding use of the App).\n* Lack capacity to consent to project due to cognitive impairment (precluding understanding of the study and use of the App)."}, 'identificationModule': {'nctId': 'NCT06450418', 'briefTitle': 'Digital App for Speech & Health Monitoring', 'organization': {'class': 'OTHER', 'fullName': 'University of Edinburgh'}, 'officialTitle': 'Digital App for Speech & Health Monitoring in Neurodegenerative Disorders', 'orgStudyIdInfo': {'id': 'AC24003'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Carers/Realtives/ Healthy - No Diagnosis of a Neurodegenerative Disorder'}, {'label': 'Motor Neuron Disease'}, {'label': 'Multiple Sclerosis'}, {'label': 'Dementia'}, {'label': "Parkinson's Disease"}]}, 'contactsLocationsModule': {'locations': [{'city': 'Edinburgh', 'status': 'RECRUITING', 'country': 'United Kingdom', 'contacts': [{'name': 'Suvankar Pal', 'role': 'CONTACT'}], 'facility': 'NHS Lothian', 'geoPoint': {'lat': 55.95206, 'lon': -3.19648}}], 'centralContacts': [{'name': 'Christine R Weaver, MSc', 'role': 'CONTACT', 'email': 'cweaver@ed.ac.uk', 'phone': '01314659512'}], 'overallOfficials': [{'name': 'Suvankar Pal, Prof', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Edinburgh'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Edinburgh', 'class': 'OTHER'}, 'collaborators': [{'name': 'NHS Lothian', 'class': 'OTHER_GOV'}], 'responsibleParty': {'type': 'SPONSOR'}}}}