Evidence map›Paper›PMID 41180479›Full record

SynthesisPeerJ2025

Effects of virtual reality exercise on fatigue, pain, and psychological status among cancer patients: a meta-analysis.

Ruihan Wang, Yunwei Wang, Shiming Li, Shuoqi Li

Abstract readMeta-Analysis
In one paragraph

Synthesis in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

4 authors.

Ruihan Wang *School of Sports Science, Nantong University, Nantong, China.
Yunwei Wang *School of Sports Science, Nantong University, Nantong, China.
Shiming LiDepartment of Physical Education, Ocean University of China, Qingdao, China.
Shuoqi LiSchool of Sports Science, Nantong University, Nantong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cancer and its associated therapies can result in pain, fatigue, and high psychological depression with anxiety levels. Therefore, this meta-analysis explored the effects of virtual reality (VR) exercise on fatigue and pain in cancer patients, and the secondary outcomes assessed the levels of depression and anxiety. Methodology: Eligible studies were searched for through four databases and then screened. The inclusion criteria are as follows: (1) Participants with cancer; (2) randomised controlled trial and single-arm trials; (3) the intervention group received VR exercise; (4) conducted pre- and post-test, which include fatigue, pain, depression and anxiety. The Cochrane bias risk assessment tool was used to evaluate the quality of the selected study. Standardized Mean Difference (SMD) was selected as the appropriate effect scale index, and Revman 5.4 software was used to analyze the mean difference of the selected article data. (Registration number: CRD420251037421). Results: The meta-analysis outcomes implied a greater reduction in fatigue following the virtual reality group (VRG) intervention in comparison to control group (COG) (SMD, 0.77 [0.50, 1.04], Conclusions: This review indicated that VR exercise reduced fatigue, pain, and anxiety in cancer patients. Nevertheless, the effect of VR exercise on relieving depression is not clear, which may be a potentially effective non pharmacological intervention in this population.

Indexed as

Exercise TherapyFatigueNeoplasmsPainPain ManagementVirtual RealityAnxietyDepressionHumansCancerExerciseFatiguePainVirtual reality

Identifiers

PMID41180479
PMCPMC12579480

What OpenQuestion holds

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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.