Evidence map›Paper›PMID 42291765›Full record

ArticleDigital health

Effectiveness of 3D virtual reality motionless imagery exercise through an avatar for mental health in older people: A randomized controlled trial.

Myung-Chul Lee, Chang-Hoon Park, Kyung-Hun Han

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Myung-Chul LeeDepartment of Sport Science, Pusan National University, Busan, South Korea.ORCID https://orcid.org/0000-0002-5471-7811
Chang-Hoon ParkDepartment of Game Software, Hoseo University, Asan, South Korea.
Kyung-Hun HanDepartment of Sport Science, Pusan National University, Busan, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study developed a 3D virtual reality (VR)-based Mental Imagery Exercise with Avatars (MIEA) and evaluated its effectiveness in improving cognitive, emotional, and physical outcomes in older adults. Methods: The experiment involved 38 older adults aged between 65 and 84 years. The study subjects were divided into experimental and control groups, with 19 individuals in each group. Both groups engaged in the VR intervention for 20 minutes, three times a week, for six weeks. The experimental group selected an avatar matching their gender and engaged in virtual exercise using a jogging track, while the control group performed virtual exercise on the same jogging track without an avatar. Results: Most cognitive assessments showed significant improvements over time, except for the Stop Signal Task. Significant time-by-group interactions were observed in the Stroop Test, immediate and delayed recall in the K-AVLT, working memory in the Digit Span Task, and semantic fluency in the COWAT. Emotional well-being analysis showed a significant improvement in physical self-efficacy over time, along with a time-by-group interaction. Group differences were significant for stress, positive affect, and negative affect. Electromyography (EMG) data from the left gastrocnemius indicated significant time effects and time-by-group interaction, suggesting physiological changes associated with the intervention. Conclusions: The results indicated that 3D MIEA provides certain psychological benefits associated with exercise and 3D MIEA may offer potential utility for individuals who are unable to engage in physical exercise.

Indexed as

3D virtual realitycognitive functionemotional well-beingimagery trainingmental healtholder people

Identifiers

PMID42291765
PMCPMC13263507

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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.