The main argument in this thesis is that mobile technology has to adapt information presentation to the mobile use context and Human Factors (attention, workload and individual characteristics). This will provide better support for work in these domains than non-adaptive systems. We expect such context-aware mobile support (CAMS) systems to improve task performance (decision accuracy, response and handling time) and optimize the user experience (trust, preferences and acceptance). The central question in this thesis is: Which features of context-aware mobile systems can support team task performance and optimize the user experience, specifically for mobile information exchange and team collaboration in professional domains? Taking the police work environment as application domain, the research in this thesis focused on designing and evaluating CAMS system features, specifically to support mobile information exchange and team collaboration. Following a Situated Cognitive Engineering method, we conducted a field study and five experiments to test the effects of context-aware notification and task allocation support on task performance and the user experience. The main findings were that context-aware notification and task allocation support improved decision making accuracy but slowed down response time to incident messages. People trusted and preferred the CAMS system more than a non-adaptive system, leading to a positive user experience. Further research should address technological constraints in CAMS systems (e.g. accuracy and reliability of context representation) and focus on summative evaluation of CAMS systems in operational settings. This way, CAMS systems can provide benefit for teams of mobile professionals by facilitating mobile information exchange and optimizing team collaboration.