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Record W4310334087 · doi:10.22037/aaem.v10i1.1756

Effect of Virtual Reality-Based Interventions on Pain During Wound Care in Burn Patients; a Systematic Review and Meta-Analysis.

2022· review· en· W4310334087 on OpenAlexaff
Narges Norouzkhani, Raziyeh Chaghian Arani, Hamidreza Mehrabi, Parissa Bagheri Toolaroud, Pooyan Ghorbani Vajargah, Amirabbas Mollaei, Seyed Javad Hosseini, Mahbobeh Firooz, Atefeh Falakdami, Poorya Takasi, Alireza Feizkhah, Hessamoddin Saber, Haniye Ghaffarzade, Ava Nemalhabib, Alborz Ghaffari, Joseph Osuji, Mohammadreza Mobayen, Samad Karkhah

Bibliographic record

VenuePubMed · 2022
Typereview
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsMount Royal University
Fundersnot available
KeywordsMedicinePsychological interventionMeta-analysisVirtual realityCritical appraisalChecklistPhysical therapyRandomized controlled trialSystematic reviewBurn woundWound careIntervention (counseling)Debridement (dental)MEDLINESurgeryWound healingPsychologyInternal medicineNursingAlternative medicine

Abstract

fetched live from OpenAlex

Introduction: Burn patients undergo daily painful wound care procedures, including washing, debridement, and dressing. This systematic review and meta-analysis aimed to examine the effect of virtual reality (VR)-based interventions on pain during wound care in burn patients. Methods: A comprehensive systematic search was conducted on international electronic databases such as Scopus, PubMed, and Web of Science with keywords extracted from Medical Subject Headings such as "Virtual reality", "Virtual reality therapy", "Virtual reality exposure therapy", "Virtual reality immersion therapy", "Exergaming", "Active-video gaming", "Burns", "Wound healings", "Pain", and "Pain management" from the earliest to May 6, 2022. The Joanna Briggs Institute (JBI) critical appraisal checklist was used to assess the quality of randomized control trials and quasi-experimental studies. Results: :91.2%). Conclusion: It is suggested that health policymakers and managers equip burn wards with immersive VR devices to provide the basis for this intervention when caring for patients with burn wounds.

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)0.010
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.004
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.076
GPT teacher head0.352
Teacher spread0.276 · 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.

Study designSystematic review
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

Citations63
Published2022
Admission routes1
Has abstractyes

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