Digitalization has fundamentally transformed human system interaction in nuclear main control rooms, yet the quantitative mechanisms by which interfaces amplify procedural risks remain insufficiently understood. This study presents a systematic assessment of interface procedure coupling based on real operational events collected from 2021 to 2025 in a modern nuclear power plant. A reusable three dimensional labeling framework and a four factor interface mechanism model are developed to characterize layout, semantic, mismatch, and labeling deficiencies. Results show that interface issues function as a significant risk amplifier. A total of 42.6 percent of events involved interface deficiencies, and their presence more than doubled the likelihood of procedural deviation. Machine learning interpretation further reveals that composite interface procedure coupling, particularly driven by semantic mismatches and layout induced traps, is the dominant contributor to coupled failures. Simulator based validation confirms that semantic confusion accounts for 27.3 percent of interface induced errors, with overall error patterns consistent with historical data. The study provides a data driven HRA workflow for early vulnerability identification in digital control rooms and proposes a systematic framework for interface procedure semantic alignment to support risk informed design and verification.