Evidence map›Paper›PMID 42614598›Full record

ArticleFrontiers in digital health2026

Effect of virtual reality-integrated mindfulness-based cognitive therapy on pain and psychological symptoms in chronic non-specific low back pain: protocol for a randomized controlled trial.

Panqi Wang, Junpeng Yuan, Qin Gu, Guoyang Dai, Xinran Zhu, Zhenxiu Liu, Youjia Yu, Xiaohong Jin

Registry-linked trialAbstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07589790 (Effect of Virtual Reality-Based Mindfulness-Based Cognitive Therapy in Patients With Chronic Nonspecific Low Back Pain), which is not on this 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.

NCT07589790 narecruitingnot on this map

Effect of Virtual Reality-Based Mindfulness-Based Cognitive Therapy in Patients With Chronic Nonspecific Low Back Pain: Protocol for a Prospective, Multi-Center, Open-Label Randomized Controlled Trial

TypeinterventionalSponsorThe First Affiliated Hospital of Soochow UniversityRan2026 to 2027Enrolled214ConditionsChronic Non-specific Low Back PainArmsVirtual Reality-Based Mindfulness Cognitive Therapy (VR-MBCT), Waitlist Usual Care Control Group
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

8 authors.

Panqi Wang *Department of Pain Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Junpeng Yuan *Department of Pain Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Qin Gu *Department of Pain Medicine, Suzhou Xiangcheng People's Hospital, Suzhou, China.
Guoyang Dai *Department of Pain Medicine, The Fourth Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Xinran ZhuDepartment of Pain Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Zhenxiu LiuDepartment of Pain Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Youjia YuDepartment of Anesthesiology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Xiaohong JinDepartment of Pain Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic non-specific low back pain (CNLBP) is a common condition associated with persistent pain, functional limitation, reduced quality of life, and substantial healthcare and socioeconomic burden. Mindfulness-based cognitive therapy (MBCT) has been increasingly used in chronic pain management and may provide a promising therapeutic approach for CNLBP. The emergence of virtual reality (VR) further provides an immersive, standardized, and accessible platform for delivering MBCT. This study aims to evaluate the effects and safety of a CNLBP-specific VR-integrated MBCT intervention in patients with CNLBP. Methods: This multi-center, prospective, parallel-group, open-label randomized controlled trial will recruit 214 patients with CNLBP from the pain clinics of three hospitals. Participants will be randomly assigned in a 1:1 ratio to either an 8-week VR-MBCT group consisting of weekly in-clinic VR sessions supplemented by structured audio-guided home practice, or a usual care control group receiving usual care alone, such as pharmacotherapy and physical therapy, using stratified block randomization according to study center and age (≥60 years or <60 years), with block sizes of 2 and 4. The primary outcomes are the proportions of patients achieving at least a 30% improvement from baseline in functional disability, assessed by the Oswestry Disability Index (ODI), and in self-reported back pain bothersomeness, assessed on a 0-10 scale, at week 8. Secondary outcomes include pain intensity, anxiety, depression, sleep quality, kinesiophobia, pain catastrophizing, work productivity, system usability, and use of concomitant treatments. Safety outcomes will include VR-related adverse events, such as vertigo, vomiting and nausea, headache and falls. Assessments will be conducted at baseline, week 4, week 8, and week 26. Data will be analyzed according to the intention-to-treat principle using generalized estimating equations (GEEs). Discussion: This study aims to provide preliminary evidence regarding the efficacy and safety of VR-integrated MBCT as an adjunct to usual care in patients with CNLBP. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT07589790, identifier NCT07589790.

Indexed as

back pain bothersomenesschronic non-specific low back painmindfulness-based cognitive therapyoswestry disability indexvirtual reality

Identifiers

PMID42614598
PMCPMC13482564

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.