Immersive virtual reality vs. non‐immersive distraction for pain management of children during bone pins and sutures removal: A randomized clinical trial protocol
Bibliographic record
Abstract
AIMS: To examine the efficacy of an immersive virtual reality distraction compared with an active non-immersive distraction, such as video games on a tablet, for pain and anxiety management and memory of pain and anxiety in children requiring percutaneous bone pins and/or suture removal procedures. DESIGN: Three-centre randomized clinical trial using a parallel design with two groups: experimental and control. METHODS: Study to take place in the orthopaedic department of three children hospital of the Montreal region starting in 2019. Children, from 7-17 years old, requiring bone pins and/or suture removal procedures will be recruited. The intervention group (N = 94) will receive a virtual reality game (Dreamland), whereas the control group (N = 94) will receive a tablet with video games. The primary outcomes will be both the mean self-reported pain score measured by the Numerical Rating Scale and mean anxiety score, measured by the Child Fear Scale. Recalls of pain and anxiety will be measured 1 week after the procedure using the same scales. We aim to recruit 188 children to achieve a power of 80% with a significance level (alpha) of 5%. DISCUSSION: While multiple pharmacological methods have previously been tested for children, no studies have evaluated the impact of immersive virtual reality distraction for pain and anxiety management in the orthopaedic setting. IMPACT: Improved pain management can be achieved using virtual reality during medical procedures for children. This method is innovative, non-pharmacological, adapted to the hospital setting, and user-friendly. TRIAL REGISTRATION: NCT03680625, registered on clinicaltrials.gov.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".