A Rapid Evidence Assessment of Immersive Virtual Reality as an Adjunct Therapy in Acute Pain Management in Clinical Practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Immersive virtual reality (IVR) therapy has been explored as an adjunct therapy for the management of acute pain among children and adults for several conditions. Therapeutic approaches have traditionally involved medication and physiotherapy but such approaches are limited over time by their cost and side effects. This review seeks to critically evaluate the evidence for and against IVR as an adjunctive therapy for acute clinical pain applications. METHODS: A rapid evidence assessment (REA) strategy was used. CINAHL, Medline, Web of Science, IEEE Xplore Digital Library, and the Cochrane Library databases were screened in from December 2012 to March 2013 to identify studies exploring IVR therapies as an intervention to assist in the management of pain. Main outcome measures were for acute pain and functional impairment. RESULTS: Seventeen research studies were included in total including 5 RCTs, 6 randomized crossover studies, 2 case series studies, and 4 single-patient case studies. This included a total of 337 patients. Of these studies only 4 had a low risk of bias. There was strong overall evidence for immediate and short-term pain reduction, whereas moderate evidence was found for short-term effects on physical function. Little evidence exists for longer-term benefits. IVR was not associated with any serious adverse events. DISCUSSION: This review found moderate evidence for the reduction of pain and functional impairment after IVR in patients with acute pain. Further high-quality studies are required for the conclusive judgment of its effectiveness in acute pain, to establish potential benefits for chronic pain, and for safety.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.250 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it