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Record W4407017752 · doi:10.2196/63098

Cooperative Virtual Reality Gaming for Anxiety and Pain Reduction in Pediatric Patients and Their Caregivers During Painful Medical Procedures: Protocol for a Randomized Controlled Trial

2025· article· en· W4407017752 on OpenAlexvenueno aff
Stefan Liszio, Franziska Bäuerlein, J. Hildebrand, Carolin van Nahl, Maic Masuch, Oliver Basu

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyRandomized controlled trialPsychological interventionMedicinePhysical therapyDistressIntervention (counseling)Protocol (science)Clinical trialClinical psychologyPsychiatryAlternative medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: The hospital experience is often marked by fear and pain, particularly for children undergoing medical procedures. Sedation is commonly used to alleviate patient anxiety, but it poses additional health risks. Caregivers, usually the parents, also experience emotional distress during the child's hospital stay, which can further exacerbate the child's anxiety and pain. While various interventions exist to ease patient distress, few consider the emotional well-being of caregivers. OBJECTIVE: This study aims to explore the effectiveness of a cooperative virtual reality (VR) game as a novel nonpharmacological solution to reduce anxiety and pain for both pediatric patients and their caregivers during medical procedures. Specifically, we aim to investigate whether the VR game "Sweet Dive VR" (SDVR), designed for children aged between 6 and 12 years to play with 1 caregiver, can alleviate anxiety and pain during different types of needle punctures and Kirschner-wire removal. METHODS: A prospective multicenter randomized clinical trial will be conducted. Eligible participants will be identified by scanning the hospital information system, and group allocation will follow stratified randomization. During the medical procedure, patients in the VR condition will play SDVR with a caregiver present, while patients in the control group will listen to a recording of gently crashing waves. Data collection will be carried out through self-reports of patients and caregivers using visual analog scales and questionnaires at 2 measurement time points: before and after the intervention. In addition, observation by the interviewers will occur during the intervention to capture emotional and pain reactions as well as interaction quality between patients and caregivers and smoothness of the procedure flow using a structured observation protocol. The measured variables will encompass patient affect and pain, caregiver affect, player experience, patient experience, and the flow of the procedure. RESULTS: As of November 2024, we enrolled 39 patients and caregivers, 28 of whom completed the study. Data collection is still ongoing. CONCLUSIONS: Cooperative VR gaming, as exemplified by SDVR, emerges as a promising intervention to address anxiety and pain in pediatric patients while involving caregivers to support the emotional well-being of both parties. Our approach strives to foster positive shared experiences and to maintain trust between children and caregivers during emotionally challenging medical situations. TRIAL REGISTRATION: German Clinical Trial Register (DRKS) DRKS00033544; https://drks.de/search/en/trial/DRKS00033544. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/63098.

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)0.024
metaresearch head score (Gemma)0.020
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.059
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.020
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0120.005
Bibliometrics0.0030.003
Science and technology studies0.0030.003
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0590.008

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 head0.052
GPT teacher head0.464
Teacher spread0.411 · 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
GenreProtocol

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

Citations6
Published2025
Admission routes1
Has abstractyes

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