Armira Kontaxi has successfully defended her PhD dissertation titled: The Driver Behavior Telematics Feedback Mechanism, under the supervision of NTUA Prof. George Yannis. Data from a 21-month naturalistic driving experiment involving 230 drivers across six feedback phases generated a robust dataset of 106,776 trips, covering 1.3 million kilometers. Advanced statistical and machine learning models, including Generalized Linear Mixed-Effects Models (GLMMs), Structural Equation Models (SEMs), and Survival Analysis methods (e.g., Weibull AFT, Cox-PH with frailty, and Random Survival Forests), were utilized to analyze behavioral metrics such as speeding, mobile phone use, harsh braking, and accelerations which demonstrated substantial impacts on reducing risky behaviors. Key findings suggest that the overall impact of feedback significantly improved driving behavior and safety, with notable variations across user groups and driving contexts. Urban environments demonstrated the most substantial reductions in mobile phone use and harsh events, likely driven by the heightened complexity and demands of navigating urban settings. These findings highlight the need for continuous and adaptive engagement strategies, incorporating diverse features tailored to the specific needs of different user groups and driving contexts, to ensure long-term effectiveness and sustained safety improvements.