A paper titled Incentive-Based Telematics and Driver Safety: Insights from a Naturalistic Study of Behavioral Change authored by Armira Kontaxi, Harris Sideris, Dimitrios Oikonomopoulos and George Yannis has been published in Sensors. This paper investigates driver profiling and behavioral change using high-resolution telematics data collected through the OSeven DrivingStar smartphone application. The naturalistic driving experiment was divided into two main phases: a baseline period with personalized feedback (Phase A) and an incentive-based phase (Phase B) comprising two gamified driving challenges with distinct reward criteria. The analysis of K-means clustering identified three driver profiles — Low-Exposure Cautious, Balanced/Average, and High-Risk Drivers — based on exposure, harsh events, speeding, and mobile phone use. The findings indicate that the Balanced/Average group exhibited statistically significant improvements during both challenges, reducing speeding frequency and intensity, while High-Risk Drivers achieved moderate reductions in speeding intensity. Furthermore, this Study contributes to the growing body of research on gamified driver feedback by linking behavioral clustering with responsiveness to incentives, providing a foundation for adaptive and personalized road safety interventions.