Evidence map›Paper›PMID 40727050›Full record

ArticleFrontiers in psychology2025

Effects of motor imagery training on muscle strength and co-contraction for older adults.

Wan X Yao, Bernadett Mamone, Sha Ge, Mehmed B Bayram, Jiang Wu, Bo Y Jiang, John Q Zhang, Guang H Yue

Abstract read
In one paragraph

Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. 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

8 authors.

Wan X YaoDepartment of Kinesiology, College for Health, Community, and Policy, The University of Texas at San Antonio, San Antonio, TX, United States.
Bernadett MamoneNeurelis Inc., San Diego, CA, United States.
Sha GeCollege of Sports Science, Tianjin Normal University, Tianjin, China.
Mehmed B BayramCenter for Spinal Stimulation Research, Kessler Foundation, West Orange, NJ, United States.
Jiang WuIntegrative Health Center, trüHealthNow, Germantown, MD, United States.
Bo Y JiangSchool of Public Health, Jilin Medical University, Jilin, China.
John Q ZhangDepartment of Kinesiology, College for Health, Community, and Policy, The University of Texas at San Antonio, San Antonio, TX, United States.
Guang H YueRutgers New Jersey Medical School, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This pilot study aimed to evaluate the effectiveness of motor imagery training (MIT) in enhancing maximal voluntary contraction (MVC) force among healthy older adults and inducing neural adaptations measured by electromyography (EMG) signals of both agonist and antagonist muscles, as well as the co-contraction index (CCI). Methods: Conducted with a single MIT group using a within-subject design, the study involved 12 right-handed elderly participants, with nine completing the 8-week training (5 sessions/week and 30 min/session). Elbow flexion MVC force and MVC EMG for biceps brachii (agonist) and triceps brachii (antagonist) were recorded pre- and post-training. Results: Significant improvements in muscle strength were observed following the 8-week MIT, with a notable 22% increase ( Conclusion: These findings provide further evidence of MIT's efficacy in enhancing voluntary muscle strength through neural adaptations, particularly beneficial and safer for older individuals encountering challenges with conventional strength training methods.

Indexed as

agingmental practicemotor imagery trainingmuscle co-contractionmuscle strength

Identifiers

PMID40727050
PMCPMC12301351

What OpenQuestion holds

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LicenceCC BY
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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.