Virtual reality mobility for burn patients (<scp>VR‐MOBILE</scp>): A <scp>within‐subject‐</scp>controlled trial protocol
Bibliographic record
Abstract
In the acute phase, burn patients undergo several painful procedures. Pediatric burn care procedures conducted in hydrotherapy have been known to generate severe pain intensity and moderate to high levels of anxiety. Hydrotherapy treatments are done with the use of opioids and benzodiazepines for pain and anxiety. Unfortunately, nonpharmacological methods are rarely combined with pharmacological treatments despite evidence showing that distraction can serve as an effective method for pain management and can potentially decrease analgesic requirements in other painful medical procedures. Virtual reality (VR) is a method that uses distraction to interact within a virtual environment. The use of VR is promising for pain reduction in varying settings. Considering the lack of optimal pain and anxiety management during burn wound care and the positive effect of an immersive distraction for painful procedures, using VR for burn wound care procedures may show promising results. This is a within-subject randomized controlled trial design in which each participant will serve as his/her own control. A minimum of 20 participants, aged 7 to 17 years old undergoing a burn care session, will receive both standard and experimental treatments during the same session in a randomized order. The experimental treatment will consist of combining VR distraction using the video game Dreamland® to the current standard pharmacological care as per unit protocol. The control group will only receive the unit's standard pharmacological care. The mean difference in both pain intensity scores and in anxiety between the two different sequences will be the primary outcomes of this study. This study evaluates the effect of VR on burn wound care. If results from this study show a positive effect of VR compared to standard care, this protocol may provide guidance on how to implement this type of immersive care as part of the tools available for distraction of painful procedures for acute burn victims.
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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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.057 | 0.006 |
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".