Evidence map›Paper›PMID 31623274›Full record

ArticleBrain sciences2019

An Investigation of Limbs Exercise as a Treatment in Improving the Psychomotor Speed in Older Adults with Mild Cognitive Impairment.

Hao Jiang, Shihui Chen, Lina Wang, Xiaolei Liu

Open access · goldAbstract read
In one paragraph

Article in Brain sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
1.0field-weighted citation impact, top 22% 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.

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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

4 authors at 4 institutions in 2 countries.

Hao JiangSchool of Humanities and Social Science, Chinese University of HK (Shenzhen), Shenzhen 518172, China.
Shihui ChenDepartment of Kinesiology, Texas A & M University, Texarkana, TX 75503, USA. schen@tamut.edu.
Lina WangNursing Department of Medical College, Huzhou University, Huzhou 313000, China.
Xiaolei LiuDepartment of Traditional Sports, Beijing Sport University, Beijing 100084, China.
Beijing Sport University · CNChinese University of Hong Kong, Shenzhen · CNHuzhou University · CNTexas A&M University – Texarkana · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study investigated the effects of therapeutic structured limb exercises intended to improve psychomotor speed in older adults with mild cognitive impairment (MCI).

methodsForty-four patients with mild cognitive impairment who met the inclusion criteria were selected and assigned randomly to either an experimental group (22 patients) or a control group (22 patients). The numbers of participants were selected based on the calculated sample effect size (

resultsThe patients with MCI in the experimental group achieved significantly improved scores in the FTT, the PPT and all dimensions of the MoCA. Moreover, these patients exhibited significant increases in the alpha and beta EEG wave power values in all brain areas of MCI patients, indicating that limb exercise training positively influenced their brain functions.

conclusionsThe results conclude that a structured therapeutic limb exercise intervention can effectively improve psychomotor speed in patients with MCI and mitigate declines in cognitive function. This training intervention appears to be effective as a treatment for community-dwelling patients with MCI.

Indexed as

dementia and Alzheimer’s diseaselimbs exercisemild cognitive impairmentpsychomotor speed

Identifiers

PMID31623274
PMCPMC6827026
OpenAlexW2981035814

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.