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The overall aim of this study is to find out if people with cognitive difficulties will wear and use different types of digital technology, and if they will allow data from that technology and their clinical profile to be collected. Participants will be patients in Essex Memory clinic and their partners/carers. The digital technology used will include a smartwatch, a sleep headband and two smartphone applications, which have been selected as part of the Early Detection of Neurodegenerative Disease (EDoN) initiative. The investigators will also investigate how the digital data can be analyzed together with routinely captured clinical data using machine learning models, a complex type of statistical analysis.
The aim of the wider EDoN initiative is to combine digital and clinical data to develop machine learning models which can predict individuals' risk of developing dementia decades before the onset of symptoms.
Full description
Study Design & Methods of Data Collection: This study is designed as an observational, pilot and feasibility study. Recruitment will be over 18 months with clinical data collected at baseline and up to 5 years follow up, and digital data collected at baseline, 3, 6, 9 and 12 months.
Setting: Essex Memory Clinics within the Essex Partnership University NHS Foundation Trust which serves older adults living in greater London and Essex areas.
Participants: The investigators aim to recruit a minimum of 100 participants, comprising of a 3:1 ratio of patients to controls respectively (refer to section 6 for eligibility criteria). Participants will include patients of the memory clinic with cognitive complaints, mild cognitive impairment or dementia, and their partners/carers/family members/friends as controls. As this is a feasibility study, this sample is not based on a power calculation, but findings will inform future work in this area. Sampling will follow a convenience strategy, appropriate for a feasibility study.
Methods: Overall feasibility of implementing digital tools within a clinical population will be evaluated through a combination of direct usage data from the devices and apps and via questionnaires. Digital tools (Fitbit, Dreem headband, Mezurio app, Longevity app) will be provided to participants at a baseline visit at the participant's home.
The broad, but not exclusive, areas of interest will include:
Digital Tools: In order to develop disease-specific fingerprint models, it is necessary to collect a wide range of measures which may be affected by early disease processes. Therefore, a combination of digital tools will be utilised, including remote active and passive smartphone-based assessments and remote passive data collection with devices (e.g., a smartwatch and an EEG headband). These technologies will be targeted at functions with a direct relationship to the brain-regions first affected by dementia-related pathology in addition to using digital devices to measure new signals of interest. The investigators will aim to keep the participant burden as low as possible by mainly including passive measures (e.g., monitoring sleep EEG) and by limiting the amount of time participants are engaged in active assessments (e.g., a smartphone-based memory test) to approximately 10 minutes per day.
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Data sourced from clinicaltrials.gov
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