Virtual Reality Combined with Mind-Body Therapies for the Management of Pain: A Scoping Review
Bibliographic record
Abstract
When used separately, virtual reality (VR) and mind-body therapies (MBTs) have the potential to reduce pain across various acute and chronic conditions. While their combination is increasingly used, no study offers a consolidated presentation of VR and MBTs. This study aims to propose an overview of the effectiveness of VR combined with MBTs (i.e., meditation, mindfulness, relaxation, and hypnosis) to decrease the pain experienced by healthy volunteers or patients. We conducted a scoping review of the literature using PubMed, Science Direct and Google Scholar and included 43 studies. Findings across studies support that VR combined with MBTs is a feasible, well-tolerated, and potentially useful to reduce pain. Their combination also had a positive effect on anxiety, mood, and relaxation. However, insufficient research on this VR/MBTs combination and the lack of multidimensional studies impede a comprehensive understanding of their full potential. More randomized controlled studies are thus needed, with usability evaluation protocols to better understand the effects of VR/MBTs on patients wellbeing and to incorporate them into routine clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".