Construction and implementation of an AI-enhanced progressive training model for clinical competency development in obstetrics and gynecology residents

BACKGROUND: This study aimed to develop and validate the effectiveness of an artificial intelligence (AI)-enhanced progressive training model for clinical competency development in obstetrics and gynecology residents and investigate innovative approaches to enhance the quality of obstetrics and gynecology resident training. METHODS: A pre-post self-comparison research design was employed with 28 obstetrics and gynecology residents from three consecutive cohorts (2021–2023) as research subjects. The AI technologies utilized in this study included an intelligent case simulation platform, an adaptive learning algorithm-driven personalized training pathway system, and a competency-based intelligent assessment system. The “Three-Coordination” training model and “Four-Stage Progressive” teaching system were systematically integrated into the curriculum. Based on the “Four-Dimensional Integrated” clinical competency framework, standardized assessments, validated questionnaires, and semi-structured expert interviews were used to compare residents’ clinical competency development, learning experiences, and satisfaction before and after training. RESULTS: Following implementation the AI-enhanced progressive training model, residents demonstrated significant improvements in professional knowledge competency (74.3 ± 6.8 vs. 86.7 ± 5.4, p < 0.001), clinical skills competency (72.6 ± 7.3 vs. 88.5 ± 4.9, p < 0.001), clinical reasoning competency (68.4 ± 8.1 vs. 84.9 ± 5.7, p < 0.001), and professional conduct competency (76.5 ± 6.2 vs. 85.6 ± 5.3, p < 0.01). Assessment of five core clinical skills revealed post-training performance enhancements of 11.6% − 16.3% (p < 0.001). Multiple parameters measuring clinical case analysis capabilities improved by 9.8% − 15.7% (p < 0.001). Additionally, 92.9% of residents expressed satisfaction with the training model, and 100% of clinical instructors endorsed its potential for broader implementation. CONCLUSIONS: The AI-enhanced progressive clinical competency training model significantly improved obstetrics and gynecology residents’ clinical competency across all measured domains, with particularly notable enhancements in clinical skills and reasoning abilities. The “Three-Coordination” training model and “Four-Stage Progressive” teaching system constitute a promising framework for advancing standardized training of obstetrics and gynecology residents and offer potential applications across other medical specialties.