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Digital Health Technologies for Alzheimer's Disease and Related Dementias: Initial Results from a Landscape Analysis and Community Collaborative Effort
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Abstract
Digital health technologies offer valuable advantages to dementia researchers and clinicians as screening tools, diagnostic aids, and monitoring instruments. To support the use and advancement of these resources, a comprehensive overview of the current technological landscape is essential. A multi-stakeholder working group, convened by the Digital Medicine Society (DiMe), conducted a landscape review to identify digital health technologies for Alzheimer's disease and related dementia populations. We searched studies indexed in PubMed, Embase, and APA PsycInfo to identify manuscripts published between May 2003 to May 2023 reporting analytical validation, clinical validation, or usability/feasibility results for relevant digital health technologies. Additional technologies were identified through community outreach. We collated peer-reviewed manuscripts, poster presentations, or regulatory documents for 106 different technologies for Alzheimer's disease and related dementia assessment covering diverse populations such as Lewy Body, vascular dementias, frontotemporal dementias, and all severities of Alzheimer's disease. Wearable sensors represent 32% of included technologies, non-wearables 61%, and technologies with components of both account for the remaining 7%. Neurocognition is the most prevalent concept of interest, followed by physical activity and sleep. Clinical validation is reported in 69% of evidence, analytical validation in 34%, and usability/feasibility in 20% (not mutually exclusive). These findings provide clinicians and researchers a landscape overview describing the range of technologies for assessing Alzheimer's disease and related dementias. A living library of technologies is presented for the clinical and research communities which will keep findings up-to-date as the field develops.
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Some digital tools provide objective and quantifiable measures at the earliest stages of disease that cannot be detected by current traditional methods.
“Some of these tools provide objective and quantifiable measures at the earliest stages of disease that cannot be detected by current traditional methods. 1”
From Developing digital health technologies for frontotemporal degeneration (2025) · cites this paper as [1]
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Metadata
- Authors
- Lott, S. A., Streel, E., Bachman, S. L., Bode, K., Dyer, J., Fitzer-Attas, C., Goldsack, J. C., Hake, A., Jannati, A., Fuertes, R. S., & Fromy, P.
- Affiliations
- Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
- Eli Lilly (United States) (US)
- Harvard University (US)
- Corresponding author
- Lott, Sarah Averill
- Venue
- The Journal of Prevention of Alzheimer's Disease
- Publisher
- Elsevier BV
- Published
- 2024-10
- Volume
- 11
- Issue
- 5
- Pages
- 1480-1489
- ISSN
- 2274-5807 (ISSN-L)
- PMC
- PMC11436391
- OpenAlex
- W4399239744
- Cited by
- 48
- References
- 48
- Citations by year
- 2026: 28 · 2025: 18 · 2024: 2
- FWCI
- 3.84
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Journal of Prevention of Alzheimer s Disease (publishedVersion, cc-by)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Eli Lilly and Company
- Biogen
- Northwestern University
- Eisai
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Geriatrics and Gerontology › Technology Use by Older Adults
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- digital health technologies, Alzheimer's disease, dementia, wearable sensors, dementia assessment, clinical validation, analytical method validation, dementia with Lewy bodies, vascular dementia, frontotemporal dementia, neurocognitive function, physical activity, sleep monitoring
- MeSH terms
- Wearable Electronic Devices, Digital Health, Alzheimer Disease, Dementia, Humans, Telemedicine, Biomedical Technology
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