Virtual reality vs. Tablet video for venipuncture education in children: A randomized clinical trial
Bibliographic record
Abstract
Pediatric patients usually experience high levels of pain and distress due to venipuncture. This randomised study aimed to evaluate the effects of virtual reality-based preprocedural education in comparison with video-based education in terms of pain and distress experienced by children scheduled to undergo venipuncture. Ninety children aged 4-8 years who were scheduled to undergo venipuncture surgery were randomly assigned to either a video or virtual reality group. Children in the video group received preprocedural education on venipuncture via a video displayed on a tablet and those in the virtual reality group received the same education via a head-mounted virtual reality display unit. The educational content for the two groups was identical. An independent assessor blinded to the group assignment observed the children's behavior and determined their Children's Hospital of Eastern Ontario Pain Scale scores, parental satisfaction score, procedure-related outcomes, venipuncture time, number of repeated procedures and difficulty score for the procedure. The virtual reality group experienced less pain and distress, as indicated by their Children's Hospital of Eastern Ontario Pain Scale scores compared with the video group (5.0 [5.0-8.0] vs. 7.0 [5.0-9.0], P = 0.027). There were no significant intergroup differences in parental satisfaction scores or procedure-related outcomes. For pediatric patients scheduled to undergo venipuncture, preprocedural education via a head-mounted display for immersive virtual reality was more effective compared with video-based education via a tablet in terms of reducing pain and distress.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".