NCT07449884

AI Avatar Video vs. Tell-Show-Do for Reducing Anxiety and Improving Cooperation in Children During Local Anesthesia

Artificial Intelligence-driven Avatar-based Video vs. Tell-show-do for Reducing Anxiety and Improving Cooperation in Children During Local Anesthesia: a Randomized Controlled Trial

• Status: Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 70 (estimated)
• Sponsor: Saint-Joseph University · Academic / Other
• Sex: All
• Age: 5 Years – 7 Years
• Healthy volunteers: Accepted

Summary

This randomized clinical trial aims to compare two behavior guidance techniques used to reduce anxiety in children during local anesthesia injections in dental treatment. The study evaluates the traditional Tell-Show-Do (TSD) technique versus an artificial intelligence (AI)-driven, avatar-based video method called the "Mini Dentist." Children aged 5 to 7 years who require local anesthesia for routine dental treatment will be randomly assigned to one of two groups. The control group will receive the conventional Tell-Show-Do explanation from the pediatric dentist. The experimental group will watch a short animated video featuring an AI-generated avatar that explains and demonstrates the procedure in a child-friendly manner before the injection. Anxiety and behavior will be assessed using heart rate monitoring, behavioral observation (FLACC scale), and a self-reported pain scale (Wong-Baker FACES). The goal is to determine whether the AI-based method improves cooperation and reduces anxiety compared to the traditional approach. Participation is voluntary, and all procedures follow ethical research standards.

Detailed description

Dental anxiety is common among children, particularly during local anesthesia injections. The Tell-Show-Do (TSD) technique is widely used in pediatric dentistry to reduce fear by explaining and demonstrating procedures before performing them. However, its effectiveness may vary depending on communication style and child engagement. With increasing exposure to digital media, children may respond more positively to visual and technology-based tools. This randomized controlled clinical trial will compare traditional TSD with an AI-driven avatar-based video modification ("Mini Dentist") during buccal infiltration anesthesia in children aged 5-7 years receiving local anesthesia for the first time. Eligible children will be randomly assigned (1:1) to: * Group A: Traditional Tell-Show-Do * Group B: AI-driven avatar-based Tell-Show-Do video All injections will follow a standardized protocol and be performed by the same pediatric dentist to ensure consistency. Primary outcome: Physiological anxiety measured by heart rate at five standardized time points. Secondary outcomes: * Behavioral pain response assessed using the FLACC scale * Self-reported pain using the Wong-Baker FACES Pain Rating Scale Behavior during injection will be video recorded for objective scoring by calibrated evaluators. The study is approved by the Research Ethics Committee of Saint Joseph University of Beirut. Participation is voluntary, and informed consent is obtained from parents or legal guardians. The objective is to determine whether integrating AI-based behavioral preparation improves anxiety control and cooperation during pediatric dental injections.

Conditions

• Anxiety
• Fear
• Local Anesthesia
• Pediatric Dentistry

Interventions

Type	Name	Description
BEHAVIORAL	AI Avatar-Based video	A pre-recorded artificial intelligence-driven avatar-based educational video shown to children prior to administration of local anesthesia. The video explains the injection procedure in simple, age-appropriate language to reduce dental anxiety and improve cooperation.
BEHAVIORAL	Tell-Show-Do Technique	A conventional behavior management technique used in pediatric dentistry in which the dentist tells the child about the procedure, shows the instruments in a non-threatening way, and then performs the treatment. This method aims to reduce anxiety and improve cooperation during local anesthesia administration.

Timeline

• Start date: 2026-02-16
• Primary completion: 2027-04-30
• Completion: 2027-05-30
• First posted: 2026-03-04
• Last updated: 2026-03-30

Locations

1 site across 1 country: Lebanon