Evidence map›Paper›PMID 37971862›Full record

ArticleNeuropsychology2024

Capturing learning curves with the multiday Boston Remote Assessment of Neurocognitive Health (BRANCH): Feasibility, reliability, and validity.

Emma L Weizenbaum, Daniel Soberanes, Stephanie Hsieh, Cassidy P Molinare, Rachel F Buckley, Rebecca A Betensky, Michael J Properzi, Gad A Marshall, Dorene M Rentz, Keith A Johnson and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Neuropsychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.6field-weighted citation impact, top 6% of its field
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

19 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Combining p-tau217 and digital cognitive testing to predict cognitive decline.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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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

13 authors at 3 institutions in 1 country.

Emma L WeizenbaumDepartment of Psychiatry, Massachusetts General Hospital, Harvard Medical School.ORCID 0000-0002-3353-1428
Daniel SoberanesDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Stephanie HsiehDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Cassidy P MolinareDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Rachel F BuckleyDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Rebecca A BetenskyDepartment of Biostatistics, School of Global Public Health, New York University.
Michael J ProperziDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School.
Gad A MarshallDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Dorene M RentzDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Keith A JohnsonDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School.
Reisa A SperlingDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Rebecca E AmariglioDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Kathryn V PappDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School.ORCID 0000-0003-1687-4370
Brigham and Women's Hospital · USHarvard University · USNew York University · US

Funding

Vascular factors, physical activity, and inflammation as modulators of neurodegenerative and cognitive trajectories (Project 2)P01AG036694 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Hyun-Sik Yang · 2010 to 2026
$50.2M
Research Education ComponentP30AG062421 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Christine S Ritchie · 2019 to 2026
$36.5M
Research Education ComponentP30AG066512 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Mary Sherman Mittelman · 2020 to 2026
$28.4M
Novel automated performance-based ADL outcomes for early AD clinical trialsR01AG053184 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI MARSHALL, GAD ASHER · 2018 to 2023
$4.5M
Characterizing the evolution of Subjective Cognitive Decline in preclinical Alzheimer's diseaseR01AG058825 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI AMARIGLIO, REBECCA E · 2019 to 2024
$4.0M
Neural Correlates of Apathy Across the Alzheimer's Disease ContinuumR01AG067021 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI MARSHALL, GAD ASHER · 2020 to 2025
$3.6M
Ahead of the Curve: Early detection and monitoring of learning decrements in Alzheimers diseaseR01AG084017 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI Kathryn Victoria Papp · 2024 to 2026
$2.5M
NIA NIH HHS P01 AG036694NIA NIH HHS P30 AG062421NIA NIH HHS P30 AG066512NIA NIH HHS R01 AG053184NIA NIH HHS R01 AG058825NIA NIH HHS R01 AG067021NIA NIH HHS R01 AG084017
6 · The paper itself

Abstract

objectiveUnsupervised remote digital cognitive assessment makes frequent testing feasible and allows for measurement of learning over repeated evaluations on participants' own devices. This provides the opportunity to derive individual multiday learning curve scores over short intervals. Here, we report feasibility, reliability, and validity, of a 7-day cognitive battery from the Boston Remote Assessment for Neurocognitive Health (Multiday BRANCH), an unsupervised web-based assessment.

methodMultiday BRANCH was administered remotely to 181 cognitively unimpaired older adults using their own electronic devices. For 7 consecutive days, participants completed three tests with associative memory components (Face-Name, Groceries-Prices, Digit Signs), using the same stimuli, to capture multiday learning curves for each test. We assessed the feasibility of capturing learning curves across the 7 days. Additionally, we examined the reliability and associations of learning curves with demographics, and traditional cognitive and subjective report measures.

resultsMultiday BRANCH was feasible with 96% of participants completing all study assessments; there were no differences dependent on type of device used (

conclusionsMultiday BRANCH is a feasible, reliable, and valid cognitive measure that may be useful for identifying subtle changes in learning and memory processes in older adults. In the future, we will determine whether Multiday BRANCH is predictive of the presence of preclinical Alzheimer's disease. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Indexed as

Learning CurveMemoryAgedBostonFeasibility StudiesHumansReproducibility of Results

Identifiers

PMID37971862
PMCPMC10841660
OpenAlexW4388734475

What OpenQuestion holds

Textmetadata
LicenceTDM
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Registered trials

None linked

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.