Evidence map›Paper›PMID 42719037›Full record

ArticleAlzheimer's & dementia (New York, N. Y.)

Remote digital cognitive assessment in a trial-ready Alzheimer's disease cohort: A scalable approach for early intervention studies.

Andrew J Aschenbrenner, Hannah Wilks, Matthew Welhaf, Samhita Katteri, Sarah H Stout, Martin J Sliwinski, Tammie L S Benzinger, Brian Gordon, Yan Li, Richard J Perrin and 16 more

Abstract read
In one paragraph

Article in Alzheimer's & dementia (New York, N. Y.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Technology-natives and technology-adopters: Age differences in remote cognitive assessment in Alzheimer disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

26 authors.

Andrew J AschenbrennerDepartment of Neurology University of Kansas Medical Center Kansas City Kansas USA.ORCID https://orcid.org/0000-0002-4317-7282
Hannah WilksDepartment of Psychological and Brain Sciences Washington University in St. Louis St. Louis Missouri USA.
Matthew WelhafDepartment of Psychology North Carolina A&T State University Greensboro North Carolina USA.
Samhita KatteriDepartment of Psychological and Brain Sciences Washington University in St. Louis St. Louis Missouri USA.
Sarah H StoutDepartment of Neurology Washington University in St. Louis St. Louis Missouri USA.
Martin J SliwinskiHuman Development and Family Studies Pennsylvania State University University Park Pennsylvania USA.
Tammie L S BenzingerDepartment of Radiology Washington University in St. Louis St. Louis Missouri USA.
Brian GordonDepartment of Radiology Washington University in St. Louis St. Louis Missouri USA.
Yan LiDepartment of Neurology Washington University in St. Louis St. Louis Missouri USA.
Richard J PerrinDepartment of Pathology & Immunology Washington University in St. Louis St. Louis Missouri USA.
Alan RentonDepartment of Neuroscience Ichan School of Medicine at Mount Sinai New York New York USA.
Guoqiao WangDepartment of Neurology Washington University in St. Louis St. Louis Missouri USA.
Chengjie XiongDepartment of Biostatistics Washington University in St. Louis St. Louis Missouri USA.
Christopher H van DyckDepartment of Psychiatry Yale University New Haven Connecticut USA.
Ricardo AllegriDepartment of Cognitive Neurology Neuropsychiatry and Neuropsychology Insituto de Investigaciones Neurologicas Fleni Buenos Aires Argentina.
William S BrooksNeuroscience Research Australia Sydney New South Wales Australia.
Jacob A BecharaNeuroscience Research Australia Sydney New South Wales Australia.
Suman JayadevDepartment of Neurology University of Washington School of Medicine Seattle Washington USA.
Johannes LevinDepartment of Neurology LMU University Hospital German Center for Neurodegenerative Diseases & Munich Cluster for Systems Neurology (SyNergy) Munich Germany.
Catherine J MummeryDepartment of Neurology University College London London UK.
Raquel Sanchez-ValleNeurology Service Hospital Clínic i Provincial de Barcelona August Pi i Sunyer Biomedical Research Institute-Universitat de Barcelona Barcelona Spain.
David AguillonGrupo de Neurociencias de Antioquia Facultad de Medicina Universidad de Antioquia Medellín Colombia.
Eric M McDadeDepartment of Neurology Washington University in St. Louis St. Louis Missouri USA.
Randall J BatemanDepartment of Neurology Washington University in St. Louis St. Louis Missouri USA.
Dominantly Inherited Alzheimer Network Trials Unit (DIAN‐TU)
Jason HassenstabDepartment of Psychological and Brain Sciences Washington University in St. Louis St. Louis Missouri USA.

Funding

DIAN-TU Next Generation Prevention Trial - Data Request Management SupplementR01AG053267 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2017 to 2023
$34.9M
Dominantly Inherited Alzheimer's Network Trials Unit - Adaptive Prevention TrialR01AG046179 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2014 to 2019
$26.6M
DOMINANTLY INHERITED ALZHEIMER NETWORK TRIAL: AN OPPORTUNITY TO PREVENT DEMENTIAU01AG042791 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2013 to 2018
$8.9M
DIAN-TU: Next Generation Prevention TrialR56AG053267 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2016 to 2016
$3.2M
NIA NIH HHS R01 AG046179NIA NIH HHS R01 AG053267NIA NIH HHS R56 AG053267NIA NIH HHS U01 AG042791
6 · The paper itself

Abstract

introductionEarly detection of cognitive decline in Alzheimer's disease (AD), particularly in preclinical stages, is critical for evaluating therapeutic interventions. Traditional cognitive assessments often require lengthy in-person visits, and may therefore limit scalability for younger, trial-ready populations for primary and secondary prevention studies. We evaluated the feasibility, reliability, and validity of high-frequency remote digital cognitive assessments in individuals with autosomal dominant AD (ADAD).

methodsOne hundred twenty-three mutation carriers and non-carriers from the Dominantly Inherited Alzheimer Network Trials Unit from 20 international sites (Ages 19-66 years) completed remote assessments via personal smartphones, prompted four times daily for 7 days (≈ 3 minutes per session), and conventional in-clinic cognitive testing at baseline. Adherence, between-person reliability, test-retest reliability (intraclass correlation coefficients [ICCs]), construct validity (confirmatory factor analysis), and sensitivity to clinical disease progression were evaluated.

resultsRemote measures demonstrated excellent reliability (ICCs > 0.90 after just 10 sessions) and strong construct validity, with tasks loading onto memory, attention, and executive function domains. A composite of the remote tests slightly outperformed a traditional composite at separating mutation carriers from non-carriers. Average adherence to the study protocol was 42%, lower that observed in previous studies of older adults. DISCUSSION: High-frequency remote cognitive assessment is feasible, reliable, and valid in a relatively young international ADAD cohort. This approach offers substantial utility for clinical trials, including improved accessibility and enhanced reliability, supporting its integration into early-intervention studies.

Indexed as

Alzheimer's diseaseclinical trialscognitive testingdigital assessmentremote monitoring

Identifiers

PMID42719037
PMCPMC13554964

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.