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Record W4402983781 · doi:10.1080/00207144.2024.2391365

Virtual Reality Combined with Mind-Body Therapies for the Management of Pain: A Scoping Review

2024· review· en· W4402983781 on OpenAlexaff
Mélanie Louras, Audrey Vanhaudenhuyse, Rajanikant Panda, Floriane Rousseaux, Michele Carella, Olivia Gosseries, Vincent Bonhomme, Marie-Élisabeth Faymonville, Aminata Bicego

Bibliographic record

VenueInternational Journal of Clinical and Experimental Hypnosis · 2024
Typereview
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersFondazione Europea Ricerca BiomedicaFonds Léon FredericqKoning BoudewijnstichtingFondation contre le CancerFundação BialStichting Tegen KankerFonds De La Recherche Scientifique - FNRSMind Science Foundation
KeywordsHypnosisPain managementPsychologyVirtual realityPsychotherapistMind–body problemMedicineAlternative medicinePhysical therapyComputer scienceEpistemologyHuman–computer interactionPhilosophy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.192
GPT teacher head0.493
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractyes

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