A Pilot Randomized Controlled Trial of Virtual Reality Distraction to Reduce Procedural Pain During Subcutaneous Port Access in Children and Adolescents With Cancer
Bibliographic record
Abstract
OBJECTIVES: We aimed to determine the feasibility of virtual reality (VR) distraction for children with cancer undergoing subcutaneous port (SCP) access. We also aimed to estimate preliminary treatment effects of VR compared with an active distraction control (iPad). MATERIALS AND METHODS: A single-site pilot randomized controlled trial comparing VR to iPad distraction was conducted. Eligible children and adolescents were aged 8 to 18 years undergoing treatment for cancer with upcoming SCP needle insertions. Intervention acceptability was evaluated by child, parent, and nurse self-report. Preliminary effectiveness outcomes included child-reported pain intensity, distress, and fear. Preliminary effectiveness was determined using logistic regression models with outcomes compared between groups using preprocedure scores as covariates. RESULTS: Twenty participants (mean age 12 y) were randomized to each group. The most common diagnosis was acute lymphocytic leukemia (n=23, 58%). Most eligible children and adolescents (62%) participated, and 1 withdrew after randomization to the iPad group. Nurses, parents, and children reported the interventions in both groups to be acceptable, with the VR participants reporting significantly higher immersion in the distraction environment (P=0.0318). Although not statistically significant, more VR group participants indicated no pain (65% vs. 45%) and no distress (80% vs. 47%) during the procedure compared with the iPad group. Fear was similar across groups, with ~60% of the sample indicating no fear. DISCUSSION: VR was feasible and acceptable to implement as an intervention during SCP access. Preliminary effectiveness results indicate that VR may reduce distress and distress compared with iPad distraction. These data will inform design of a future full-scale randomized controlled trial.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".