Clinical Research Directory

THE EFFECT OF FILLING MATERIAL AND PLACEMENT TECHNIQUE ON POSTOPERATIVE PAIN IN NON-SURGICAL ENDODONTIC RETREATMENT: A RANDOMIZED CLINICAL TRIAL

Postoperative pain is a common concern following root canal retreatment. The type of root canal filling material and the technique used to place it may influence pain experienced after treatment. This randomized clinical trial aims to compare the effects of two calcium silicate-based root canal filling materials (BioMTA+ and Well-Root PT) and two placement techniques (manual compaction and reverse-rotation compaction) on postoperative pain following nonsurgical endodontic retreatment. A total of 56 adult patients requiring root canal retreatment due to persistent inflammation around the root tip will be randomly assigned to four treatment groups. All procedures will be performed in a single visit. Postoperative pain will be evaluated using a visual analog scale (VAS), and the use of pain-relieving medication will be recorded. The study aims to determine whether the type of filling material, the placement technique, or their combination influences postoperative pain following nonsurgical root canal retreatment.

Generative AI-Based Immersive Training for Endodontic Risk Disclosure and Informed Consent Among Dental Students

The objective of this prospective, parallel-group, 1:1 randomized controlled trial is to evaluate the effectiveness of a generative artificial intelligence (AI)-based immersive training program, utilizing the Gemini platform, in improving endodontic risk disclosure and informed consent (RD-IC) quality, communication competence, self-efficacy, and reducing communication anxiety among undergraduate dental students during their clinical clerkship. Traditional pedagogical methods in dental education, such as case-based learning (CBL) and peer role-playing, often struggle to simulate the high-stakes interpersonal tension and technical complexity involved in specialized endodontic risk disclosure. Complications like instrument separation, pulp floor perforation, and acute flare-ups require clear, empathetic, and legally sound communication. While standardized patients (SPs) are effective, they pose severe logistical and financial constraints for large student cohorts. To address this gap, 96 fifth-year undergraduate dental students undergoing clinical rotation were recruited and randomly allocated to either the experimental group (1-month generative AI-based immersive training via the Gemini platform) or the control group (1-month conventional case-based learning). The AI intervention provided interactive, real-time conversational simulations across six high-stakes endodontic clinical scenarios, delivering instantaneous, personalized feedback on technical accuracy and empathetic delivery. The primary outcome evaluated was the RD-IC completeness score. Secondary outcomes included SEGUE communication framework scores, Self-Efficacy in Clinical Communication Scale (SCS) scores, Communication Anxiety Scale (CAS) scores, blinded standardized patient (SP) ratings, user satisfaction, and long-term clinical skill retention assessed at 1-month (T2-1m) and 2-month (T2-2m) post-intervention follow-ups.