A Randomized Controlled Trial of Commercially Available Virtual Reality for Intravenous Cannulation-Related Distress in Children
Bibliographic record
Abstract
OBJECTIVE: To assess whether commercially available virtual reality (VR)-based distraction reduces distress when added to standard of care (SOC) for children undergoing intravenous insertion (IVI) in the pediatric emergency department. STUDY DESIGN: Children aged 6-17 years requiring IVI were recruited for a two-arm randomized controlled trial. The primary outcome was child distress, measured using the Observational Scale of Behavioral Distress-Revised (score range 0-23.5). Secondary outcomes included children's procedural pain (verbal Numerical Rating Scale, score range 0-10) and fear (Children's Fear Scale, score range 0-4). RESULTS: Mean (SD) children age was 11.1 years (2.9) and 54% (45/82) were female. Mean (SD) preprocedural Observational Scale of Behavioral Distress-Revised scores were similarly low in both the VR [0.39 (0.70)] and SOC arms [0.18 (0.49)] (P = .16). Use of VR during IVI was not associated with lower mean (SD) total procedural distress [1.1 (1.5)] vs SOC [0.7 (1.4)] (P = .08), mean (SD) procedural pain intensity [3.0 (2.9)] vs SOC [2.1 (2.3)] (P = .14), or mean (SD) Children's Fear Scale score [0.97 (1.33)] vs SOC [0.97 (1.15)]. Technical issues with the VR equipment were reported in 26% (10/39) of cases. CONCLUSIONS: VR distraction therapy employing commercially available software was not associated with reduction in procedural distress, pain or fear, above that provided with SOC, for children undergoing IVI in the pediatric emergency department. Given no differences and frequency of technical issues, other forms of distraction may be more appropriate in this setting. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT04291404.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".