Evidence map›Paper›PMID 41340844›Full record

ArticleJMIR XR and spatial computing2025

At-Home Virtual Reality Intervention for Patients With Chronic Musculoskeletal Pain: Single-Case Experimental Design Study.

Syl Slatman, Lieke Heesink, Reinoud Achterkamp, José Broeks, Nelson Monteiro de Oliveira, Remko Ter Riet, Marjolein Stegeman, Monique Tabak

Abstract read
In one paragraph

Article in JMIR XR and spatial computing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
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.

Syl SlatmanBiomedical Signals and Systems Group, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Drienerlolaan 5, Enschede, 7522NB, Netherlands.ORCID https://orcid.org/0000-0002-8529-310X
Lieke HeesinkHealth Technology and Services Research, Faculty of Behavioural, Management and Social Sciences, University of Twente, Hallenweg 5, Enschede, 7522NH, Netherlands, 31 534899128.ORCID https://orcid.org/0000-0002-3652-2164
Reinoud AchterkampDepartment of Chronic Pain, Roessingh Rehabilitation Center, Enschede, Netherlands.ORCID https://orcid.org/0000-0002-2953-2161
José BroeksDepartment of Chronic Pain, Roessingh Rehabilitation Center, Enschede, Netherlands.ORCID https://orcid.org/0009-0006-4725-7884
Nelson Monteiro de OliveiraNocepta, Hengelo, Netherlands.ORCID https://orcid.org/0009-0003-1276-4702
Remko Ter RietNocepta, Hengelo, Netherlands.ORCID https://orcid.org/0009-0005-3011-8231
Marjolein StegemanDepartment of Chronic Pain, Roessingh Rehabilitation Center, Enschede, Netherlands.ORCID https://orcid.org/0009-0000-5345-5242
Monique TabakBiomedical Signals and Systems Group, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Drienerlolaan 5, Enschede, 7522NB, Netherlands.ORCID https://orcid.org/0000-0001-5082-1112

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Virtual reality (VR) could possibly alleviate complaints related to chronic musculoskeletal pain (CMP); however, little is known about how it affects pain-related variables on an individual level and how patients experience this intervention. Objective: This study aimed to gain detailed insight into the influence of an at-home VR intervention for pain education and management on pain-related variables, and to explore its feasibility and general experience. Methods: The study applied a single-case experimental design in which an at-home VR intervention was used for 4 weeks by patients with CMP who were on a waiting list for regular pain treatment. Outcome measures included pain-related variables, functioning, and objectively measured outcomes (ie, stress, sleep, and steps). Outcomes were analyzed using data visualization (based on line plots) and statistical methods (ie, Tau-U and reliable change index) on an individual and group level. In addition, a focus group was conducted to assess feasibility and general experience to substantiate findings from the single-case experimental design study. This focus group was analyzed using inductive thematic analysis. Results: A total of 7 participants (female: n=6, 86%) with a median age of 45 (range 31-61) years participated in this study. A dataset with 42 measurement moments was collected with a median of 280 (range 241-315) data points per participant. No statistically significant or clinically relevant differences between the intervention and no-intervention phases were found. Results of the visual analysis of the diary data showed that patients responded differently to the intervention. Results of the focus group with 3 participants showed that the VR intervention was perceived as a feasible and valued additional intervention. Conclusions: Although patients expressed a positive perspective on this VR intervention, it did not seem to influence pain-related outcomes. Individual patients responded differently to the intervention, which implies that this intervention might not be suitable for all patients. Future studies should examine which CMP patients VR is effective for and explore its working mechanisms. In addition, future larger trials should be conducted to complement this study's findings on the effectiveness of this intervention for patients with CMP and whether VR prevents deterioration on the waiting list compared with a control group.

Indexed as

chronic musculoskeletal painCMPmusculoskeletal painSCEDself-managementsingle-case experimental designuser experiencevirtual realityVR

Identifiers

PMID41340844
PMCPMC12671306

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.