Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing 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.
Kathleen A LaneDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Sujuan GaoDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Omolola A Adeoye-OlatundePurdue University College of Pharmacy, Center for Health Excellence, Quality and Innovation, Purdue University, West Lafayette, Indiana, USA.
Patrick ShihLuddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, Indiana, USA.
David K JohnsonDepartment of Neurology, University of California Davis School of Medicine, Walnut Creek, California, USA.
Andrew J SaykinIndiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Sophia WangCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Funding
National Alzheimer's Coordinating CenterU24AG072122 · NIA · UNIVERSITY OF WASHINGTON · PI STEPHENS, KARI A · 2021 to 2025
$45.8M
Research Education ComponentP30AG062422 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Serggio Carlo Lanata · 2019 to 2026
$36.9M
Research Education ComponentP30AG062421 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI BRADFORD C DICKERSON · 2019 to 2026
$36.5M
UCSD Shiley-Marcos Alzheimer's Disease Research Center P30P30AG062429 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Steven Dyal Edland · 2019 to 2026
$34.9M
Wisconsin Alzheimer's Disease Research CenterP30AG062715 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI AMY J. KIND · 2019 to 2026
$34.5M
Research Education ComponentP30AG062677 · NIA · MAYO CLINIC ROCHESTER · PI Walter K. Kremers · 2019 to 2026
$33.5M
Research Education ComponentP30AG066514 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI NIKOLAOS K ROBAKIS · 2020 to 2026
$31.0M
Yale Alzheimer Disease Research CenterP30AG066508 · NIA · YALE UNIVERSITY · PI STEPHEN M STRITTMATTER · 2020 to 2026
$30.2M
Research Education CoreP30AG066462 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Andrew Franklin Teich · 2020 to 2026
$30.1M
Research Education ComponentP30AG066468 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HOWARD J AIZENSTEIN · 2020 to 2026
$29.4M
Research Education ComponentP30AG066507 · NIA · JOHNS HOPKINS UNIVERSITY · PI Corinne Pettigrew · 2020 to 2026
$29.3M
University of Washington Alzheimer's Disease Research CenterP30AG066509 · NIA · UNIVERSITY OF WASHINGTON · PI SUMAN JAYADEV · 2020 to 2026
backgroundAs Alzheimer's disease and related dementias studies incorporate remote assessments, people at higher risk, such as individuals from minority racial and ethnic groups, may be disadvantaged due to imbalances in access.
methodsUsing data from the National Alzheimer's Coordinating Center Uniform Data Set, logistic regression models using generalized estimating equations with a random effect for study site were used to test the association of race and ethnicity, education, and their interactions with technology preferences and internet access.
resultsA total of 3,803 participants across 17 ADRCs (mean age 73.3 years [standard deviation [SD] = 9.9], education 16.4 years [SD = 2.7], 79% non-Hispanic White) were included. The effect of education on internet access via desktop, laptop computer, and tablet was greater in non-White participants than in non-Hispanic White participants. A similar pattern was observed for interest in using devices for study visits. DISCUSSION: Education may have a role in racial and ethnic differences in technological access and preferences.
Indexed as
Alzheimer DiseaseInternet AccessAgedAged, 80 and overEducational StatusEthnicityFemaleHumansInternetMaleRacial GroupsUnited StatesaccessAlzheimer's diseaserace and ethnicitytechnology
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.
Technology access and preferences for remote assessments at Alzheimer's Disease Research Centers. · full record | OpenQuestion