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Record W4386834358 · doi:10.2196/49956

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

2023· article· en· W4386834358 on OpenAlexaffvenue
Wenjia Wu, Sylvie Le May, Nicole Hung, Olivier Fortin, Christine Genest, Maxime Francoeur, Estelle Guingo, Kate St‐Arneault, Annie Sylfra, An Kateri Vu, Janick Carmel, Laurence Lessard, Stephany Cara-Slavich, Katheryn De Koven, Julie Paquette, Hunter G. Hoffman, Marie-Eve Asselin

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldDentistry
TopicDental Anxiety and Anesthesia Techniques
Canadian institutionsCentre intégré universitaire de santé et de services sociaux de l'Est-de-l'Île-de-MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité de MontréalUniversité du Québec en Abitibi-TémiscamingueCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineAnxietyRandomized controlled trialVirtual realityProtocol (science)Dental clinicHealth carePhysical therapyFamily medicineAlternative medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Dental fear and anxiety (DFA) is a condition that affects approximately one-quarter of children and adolescents. It is a significant cause for pediatric patients to avoid dental care later in adulthood. Lack of patient cooperation due to DFA can create an environment of stress, often obligating dentists to end appointments prematurely and consider alternative pharmacological treatment options. Virtual reality (VR) use during dental care, providing an immersive experience through sensory stimuli, is potentially an additional nonpharmacologic tool to better manage DFA in children with special health care needs (SHCN) undergoing dental procedures. OBJECTIVE: This pilot study aims to assess the feasibility and acceptability of VR immersion as a tool to reduce DFA in pediatric special needs patients undergoing dental procedures. The study also aims to gain insight on parent and health care provider perspectives on the use of VR during dental appointments. METHODS: This pilot randomized controlled trial study will follow a parallel design including 2 groups: a control group (clinic's standard care using a wall TV) and an experimental group (using a VR game). We will randomize 20 participants to either group. Recruitment will be carried out at the dental clinic of the Centre Hospitalier Universitaire Sainte-Justine, a tertiary-quaternary care center that mostly serves pediatric patients with SHCN. The primary outcome will be patient recruitment rates and completion rates of planned procedures. DFA in children will be assessed using both an observation-based proxy assessment with the Venham Anxiety and Behavior Rating Scale and physiological assessments using parameters such as change in heart rate and levels of salivary alpha-amylase as a stress biomarker before and 10 minutes after the procedure. Sociodemographic characteristics, measures of the levels of parent and health care professional satisfaction, occurrence of side effects, and any deviation from normal procedure length will also be collected. Descriptive statistics, nonparametric tests, and effect sizes will be used for demographic and clinical variables and to present parent and health care professional satisfaction levels as well as procedural time. RESULTS: This study will be conducted from May 2023 to May 2024, with results expected to be available in December 2024. CONCLUSIONS: The pilot study will provide insight on the feasibility and acceptability of VR use in clinical dentistry to reduce DFA for pediatric patients with SHCN. This study will guide future research on VR use in pediatric dentistry and can serve as a framework for a larger randomized clinical trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT05898100; https://classic.clinicaltrials.gov/ct2/show/NCT05898100. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49956.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.079
GPT teacher head0.473
Teacher spread0.394 · 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 teacher head, not a consensus.

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

Citations5
Published2023
Admission routes2
Has abstractyes

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