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Record W7117103835 · doi:10.2196/83672

Efficacy of a Virtual Reality Game on Children’s Fear and Anxiety During Dental Procedures (VR-TOOTH): Protocol for a Randomized Controlled Trial

2025· article· en· W7117103835 on OpenAlexaffvenue
Julien Gardner, Vallerie Markopoulos, Wenjia Wu, Gabrielle Gilbert, Daphnée Pelletier, Charlotte Fafard, Anne Gagné, Estelle Guingo, Christine Genest, Marie-Ève Asselin, Pascale Ouimet, Kate St-Arneault, Sylvie Le May

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldDentistry
TopicDental Anxiety and Anesthesia Techniques
Canadian institutionsInstitut Universitaire en Santé Mentale de QuébecHEC MontréalUniversité de MontréalUniversité du Québec en Abitibi-TémiscamingueCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsRandomized controlled trialProtocol (science)AnxietyVirtual realityDental fearRandomizationVirtual Reality Exposure Therapy

Abstract

fetched live from OpenAlex

Background: Dental fear and anxiety (DFA) affects approximately a quarter of children and adolescents. It significantly contributes to pediatric patients avoiding dental care later in adulthood. Lack of cooperation due to DFA can create a stressful environment, often forcing dentists to end appointments prematurely and consider alternative pharmacological treatments. The use of virtual reality (VR) during dental procedures, offering an immersive sensory experience, may serve as an additional nonpharmacologic tool to better manage DFA in children with special health care needs (SHCN) undergoing dental treatment. Objective: This study aims to assess the effectiveness of VR immersion in reducing anxiety and pain among pediatric patients with SHCN undergoing dental procedures. The study also seeks to understand the satisfaction of parents and health care providers with the use of VR during dental appointments. Methods: This randomized controlled trial follows a parallel design with two groups: a control group receiving standard care and an experimental group using VR. A sample size of 400 participants was calculated. Participants will be randomly assigned equally to each group. Recruitment will take place at the dental clinic of the Centre Hospitalier Universitaire Sainte-Justine, a tertiary- and quaternary-care center that primarily serves pediatric patients with SHCN. The two primary outcomes will include both observed and objective biomarker-based measures of anxiety. DFA will be evaluated using the Venham Anxiety Rating Scale as well as changes in mean levels of salivary alpha-amylase. Sociodemographic characteristics, parents' and health care professionals' satisfaction levels, participants' pain intensity and behavior during the procedure, changes in heart rate, occurrence of side effects, procedure duration, and any deviations from normal procedural length will also be collected. Descriptive and comparative statistics will be conducted for demographic and clinical comparisons and will be used to present sociodemographic and clinical data, parents' and health care professionals' satisfaction levels, child satisfaction with the game, and procedural time. Results: This study will be conducted from November 2023 to December 2025. As of November 2025, 300 participants have been recruited. Results are expected to be available in June 2026. Conclusions: We believe that the results of this study will confirm the efficacy of VR in reducing DFA in children with SHCN, providing an additional nonpharmacological alternative for better managing this condition in pediatric hospital settings.

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)0.021
metaresearch head score (Gemma)0.021
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 score0.061
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.021
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0140.006
Bibliometrics0.0030.003
Science and technology studies0.0030.003
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0610.007

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 head0.058
GPT teacher head0.479
Teacher spread0.420 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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