Evidence map›Paper›PMID 38910947›Full record

ArticleJournal of Alzheimer's disease reports2024

The Effect of Computerized Cognitive Training, with and without Exercise, on Cortical Volume and Thickness and Its Association with Gait Speed in Older Adults: A Secondary Analysis of a Randomized Controlled Trial.

Ryan G Stein, Lisanne F Ten Brinke, Nárlon C Boa Sorte Silva, Chun Liang Hsu, Todd C Handy, Ging-Yuek R Hsiung, Teresa Liu-Ambrose

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of Alzheimer's disease reports, 2024. 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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

7 authors.

Ryan G SteinAging, Mobility, and Cognitive Health Laboratory, University of British Columbia, Vancouver, BC, Canada.
Lisanne F Ten BrinkeAging, Mobility, and Cognitive Health Laboratory, University of British Columbia, Vancouver, BC, Canada.
Nárlon C Boa Sorte SilvaAging, Mobility, and Cognitive Health Laboratory, University of British Columbia, Vancouver, BC, Canada.
Chun Liang HsuDepartment of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
Todd C HandyDepartment of Psychology, Faculty of Art, University of British Columbia, Vancouver, British Columbia, Canada.
Ging-Yuek R HsiungDjavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada.
Teresa Liu-AmbroseAging, Mobility, and Cognitive Health Laboratory, University of British Columbia, Vancouver, BC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Slower walking is associated with changes in cortical volume and thickness. Computerized cognitive training (CCT) and exercise improve cortical volume and thickness and thus, may promote gait speed. Slowing of gait is predictive of Alzheimer's disease. Objective: To examine: 1) the effect of CCT, with or without physical exercise, on cortical volume and thickness and; 2) the association of changes in cortical volume and thickness with changes in gait speed. Methods: A subset of 124 adults (

resultsBAT versus CCT increased left rostral middle frontal gyrus volume (

conclusionsCCT with physical exercise, but not CCT alone, improves cortical volume and thickness in older adults. These changes may contribute to the maintenance of gait speed in aging.

Indexed as

Alzheimer’s diseaseclinical trialcognitive trainingexercisegaitmagnetic resonance imaging

Identifiers

PMID38910947
PMCPMC11191637

What OpenQuestion holds

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LicenceCC BY-NC
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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.