The use of virtual reality in reducing anxiety during cast removal: A randomized controlled trial
Bibliographic record
Abstract
PURPOSE: While virtual reality (VR) has been shown to be an effective distractor in children across a range of procedures, no studies have looked at its use within paediatric orthopaedics. The purpose of this study was to look at the use of VR in reducing anxiety levels in children during cast removal. In addition, the study aimed to find ways to enhance the efficiency of future VR trials in paediatrics. METHODS: A non-blinded randomized control trial took place in children aged four to 18 years. Intraprocedural anxiety was measured using the Children's Emotional Manifestation Scale (CEMS), while pre- and post-procedural anxiety was measured using the Short State Anxiety Inventory Scale. Additional data was collected on trait anxiety, nausea levels, desire for future VR use and areas of improvement for future VR studies. RESULTS: A total of 90 subjects were included in the study (control n = 45, intervention n = 45) with a mean age of 10.25 years (sd 3.35). Post-procedural anxiety and intraprocedural anxiety were 18% (p = 0.03) and 24% (p = 0.01) lower in the VR group, respectively, with the CEMS facial component showing a 31% (p < 0.001) reduction in the VR group. In all, 99% (n = 89) of subjects experienced no nausea, with one patient experiencing mild nausea that may have been present prior to VR use. Finally, 90% (n = 81) of subjects said they would like to use VR again, 1% (n = 1) said 'no' and 9% (n = 8) said 'maybe'. CONCLUSION: VR appears to be an effective distraction technique in reducing anxiety levels in children during cast removal.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".