Research in the Digital Health Communication division is conceptually geared toward the differential susceptibility of audience members to the digital and mass media paradigm, particularly from a comparative perspective. The paradigm assumes that media effects are contingent upon both structural, individual, and cultural factors that make media effects more or less likely to occur. Therefore, our research centers around the preference-based reinforcement effects of media use, taking into consideration the algorithm-driven micro- and macro-level differences. Our research conceptually addresses narrowcasting of information, self-confirmation, and homophilic social media environments that are likely to foster tailored persuasion and looks at different content elements and methods to automatically analyze visuals, monitor how users select information from new media, and integrate individual predispositions into explanations of reinforcing media effects over time and across cultures.
The Digital Health Communication division addresses specific questions such as how new technologies (e.g., wearables, health trackers, or smart medical devices), new media, and new possibilities of data processing (e.g., machine learning, artificial intelligence, automation) change the perception, selection, processing, and impact of messages relevant for health? What new opportunities emerge for doctors, health professionals, and the health industry from these developments?