Considering the rapid growth of the global aging population, healthy aging has become a key priority of the World Health Organization. Healthy aging can be promoted by targeting health behaviors, such as sedentary behavior. A promising way to disrupt sedentary behavior, is to bring this automatic behavior and its context into conscious awareness by providing point-of-choice prompts to stand or move. However, in previous prompt-based interventions, people were often prompted by a basic vibration when not being receptive (ie not able/wiling to respond), resulting in frustration and disengagement. Consequently, future prompt-based interventions should adapt the provision of support to an individual’s needs. This project will apply innovative methods to determine when, how and to whom prompts should be delivered to reduce prolonged sedentary behavior. Firstly, an observational event-based ecological momentary assessment study will be conducted to identify the optimal conditions to deliver a sedentary behavioral prompt. Secondly, an experimental micro-randomized trial will be performed to determine the most appropriate content for a sedentary behavioral prompt. Finally, a collaboration will be set up with computer scientists and engineers to use this empirical evidence to feed a reinforcement learning algorithm. This way, proper individualized decision rules will be developed for a just-in-time adaptive intervention aimed at interrupting prolonged bouts of sedentary behavior.