A Randomized Controlled Trial on the Use of Virtual Reality for Needle-Related Procedures in Children and Adolescents in the Emergency Department
Bibliographic record
Abstract
Abstract Objective: A large number of children report fear and distress when undergoing blood work and intravenous placement. In pediatric departments, Child Life interventions are considered to be the gold standard in nonmedical pain management techniques. Virtual reality (VR) has also been identified as an effective tool for pain distraction in children undergoing painful medical procedures. The aim of this study was to document the efficacy of VR as a mode of distraction during a medical procedure compared with two comparison conditions: watching television (TV, minimal control condition) and distraction provided by the Child Life (CL, gold standard control condition) program. Materials and Methods: A total of 59 children aged 8–17 years (35% female) were recruited through the emergency department (ED) of the Children's Hospital of Eastern Ontario and randomly assigned to one of the three conditions. The key outcome measures were visual analog scale ratings of pain intensity and fear of pain, administrated before and right after the procedure. Patient satisfaction was also measured after the intervention. Results: A significant reduction in fear of pain and pain intensity was reported in all three conditions. A larger and statistically significant reduction in fear of pain was observed among children who used VR distraction compared with the CL and TV conditions, but this effect was not observed for pain intensity. The children's satisfaction with the VR procedure was significantly higher than for TV and comparable to CL. Discussion: The advantages of using VR in the ED to manage pain in children are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".