Developing a generative ai–based anti-doping consultation system to enhance coaching practice and athlete decision-making

Abstract

This study aimed to develop a generative AI-based intelligent counseling chatbot system for doping prevention and to evaluate its performance. The retrieval corpus was constructed from publicly available resources such as regulations and prohibited substance lists available on the Korea Anti-Doping Agency (KADA) website. The system was constructed by combining the Qwen3:30B-A3B model with a vector database (ChromaDB). For performance evaluation, 51 test items were extracted from KADA's Frequently Asked Questions (FAQ) and “Voice of Customers” sections. The analysis results showed that the proposed system achieved an overall accuracy of 82.35% and a response consistency of 96.08%, demonstrating high performance. This system can provide counseling and educational services to diverse groups—including athletes, coaches, and parents—regardless of time and location, thereby enhancing the efficiency and accessibility of doping prevention administration.