Evidence map›Paper›PMID 40697626›Full record

ArticleFrontiers in pain research (Lausanne, Switzerland)2025

Feasibility and user experience of augmented reality psychoeducation and mindfulness body scan for chronic low back pain.

Robin Conen, Nikolai Hepke, Jörg Lohscheller, Steffen Mueller, Ana N Tibubos

Abstract read
In one paragraph

Article in Frontiers in pain research (Lausanne, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

5 authors.

Robin ConenDepartment of Diagnostics in Healthcare & eHealth, Trier University, Trier, Germany.
Nikolai HepkeDepartment of Computer Science, Trier University of Applied Sciences, Trier, Germany.
Jörg LohschellerDepartment of Computer Science, Trier University of Applied Sciences, Trier, Germany.
Steffen MuellerDepartment of Computer Science/Therapeutic Sciences, Trier University of Applied Sciences, Trier, Germany.
Ana N TibubosDepartment of Diagnostics in Healthcare & eHealth, Trier University, Trier, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic low back pain (CLBP) is prevalent and a multimodal therapy is indicated, including psychological treatment. Effective conventional treatments involve psychoeducation and mindfulness-based body scans, while virtual reality offers superior but temporary pain relief. Augmented Reality (AR), which combines conventional and virtual methods, is a novel therapeutic strategy. Methods: We investigated the viability and acceptability of an AR intervention for CLBP by incorporating psychoeducation and mindfulness-based body scan techniques. 40 participants in two studies with a one-arm design underwent an educational AR intervention (Study I, Results: The results demonstrated high feasibility with low dropout rates (Study I: 10%, Study II: 0%). User experience ratings ranged from "Above Average" to "Excellent," with the advanced intervention receiving higher ratings. While Study I showed no significant changes in affect pre- vs. post-intervention, Study II exhibited a significant reduction in negative affect and improved valence. Qualitative analysis provided insights into technical requirements and user perceptions. Discussion: The AR prototype emerges as a promising psychoeducational tool for CLBP, aligning with current treatment guidelines and providing a basis for future controlled clinical trials. Limitations include the absence of a high-pain intervention group, as Study I reported a pain intensity of Clinical Trial Registration: Open Science Framework.io; https://doi.org/10.17605/OSF.IO/DSW5X and https://doi.org/10.17605/OSF.IO/XVJBZ.

Indexed as

augmented realitychronic low back painfeasibilitymindfulness body scanpain educationuser experience

Identifiers

PMID40697626
PMCPMC12281825

What OpenQuestion holds

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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.