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Record W7114997733 · doi:10.1093/pch/pxaf116.116

116 Virtual reality vs non-immersive distraction during orthopedic procedures for children’s pain and anxiety (PINS Trial): Secondary analyses of an RCT

2025· article· en· W7114997733 on OpenAlexaffabout

Bibliographic record

VenuePaediatrics & Child Health · 2025
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversité du Québec en OutaouaisUniversity of CalgaryMcGill UniversityCentre Hospitalier Universitaire Sainte-JustineUniversité du Québec en Abitibi-TémiscamingueUniversité de Montréal
Fundersnot available
KeywordsDistractionRandomized controlled trialOrthopedic surgeryAnxietySedationPatient satisfactionVisual analogue scaleIntervention (counseling)

Abstract

fetched live from OpenAlex

Abstract Background Children undergoing outpatient orthopedic procedures often experience severe pain and anxiety. Orthopedic bone pin and suture removal are frequently performed without any analgesia or non-pharmacological interventions, causing significant anxiety and pain for children. Furthermore, traditional methods such as analgesics and topical anesthetics often fall short in addressing children’s specific needs and require a delay. Narcotics and sedation require close monitoring and may have side effects. This randomized clinical trial (RCT) explored Virtual Reality (VR) as a child-friendly, distraction-based intervention for pain and anxiety management. Objectives This RCT primarily aimed to compare the effectiveness of VR to non-immersive distraction in reducing pain and anxiety during outpatient paediatric orthopedic procedures. This abstract provides results of secondary outcomes. Design/Methods We conducted a prospective RCT across three paediatric centres in Montreal with 188 children aged 6-17 years old undergoing bone pin or suture removal. The experimental group used VR distraction, while participants in the control group played a video game on a tablet. Secondary outcomes assessed at either T0 (Baseline) and/or T1 (post-procedure) were: 1- Pain characteristics using the Graphic Rating Scale, 2- Anxiety with a salivary biomarker (Alpha-Amylase added measure at mid-trial), 3- Satisfaction levels, and 4- Side effects using a checklist. Analyses were completed with 80% power and a 2.5% significance level. Results There was no significant difference between the VR and Tablet groups on the mean score of pain (p = 0.90). Participants in the VR group thought less about pain (4.2±3.0 v. 4.4±2.9; p=0.57), had lower pain unpleasantness (4.5±3.0 v. 5.0±3.0; p=0.22), and lower worst pain (4.8±2.9 v. 5.6±3.0; p=0.069), but results were not statistically significant. VR users tended to have more fun during the sessions (8.0±2.6 v. 7.3±3.1; p=0.098) and were significantly more satisfied with the treatment received (9.2±1.2 v. 8.6±1.9; p=0.015). Tablet users had slightly more nausea (0.2±1.0 v. 0.1±0.6 for VR; p=0.37). SAA levels were lower at T2 in the VR group but the difference was not significant (p=0.26). Conclusion Secondary analyses related to this study found that children using VR reported lower pain, higher pleasure, and very few side effects, highlighting VR’s potential to improve paediatric patient experiences in clinical settings. While adding alpha-amylase measures mid-trial limited power, it demonstrated feasibility for future VR studies. These results underscore VR's promise to create a more positive environment for children, warranting further research on its benefits in paediatric healthcare procedures.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.016
GPT teacher head0.338
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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