Kowatsch, TobiasTobiasKowatschVolland, DirkDirkVollandShih, IrisIrisShihRüegger, DominikDominikRüeggerKünzler, FlorianFlorianKünzlerBarata, FilipeFilipeBarataFiller, AndreasAndreasFillerBüchter, DirkDirkBüchterBrogle, BjörnBjörnBrogleHeldt, KatrinKatrinHeldtGindrat, PaulinePaulineGindratFarpour-Lambert, NathalieNathalieFarpour-Lambertl’Allemand, DagmarDagmarl’AllemandMaedche, Alexandervom Brocke, JanHevner, Alan2023-04-132023-04-132017https://www.alexandria.unisg.ch/handle/20.500.14171/10321510.1007/978-3-319-59144-5_36The open source platform MobileCoach (mobile-coach.eu) has been used for various behavioral health interventions in the public health context. However, so far, MobileCoach is limited to text message-based interactions. That is, participants use error-prone and laborious text-input fields and have to bear the SMS costs. Moreover, MobileCoach does not provide a dedicated chat channel for individual requests beyond the processing capabilities of its chatbot. Intervention designers are also limited to text-based self-report data. In this paper, we thus present a mobile chat app with pre-defined answer options, a dedicated chat channel for patients and health professionals and sensor data integration for the MobileCoach platform. Results of a pretest (N = 11) and preliminary findings of a randomized controlled clinical trial (N = 14) with young patients, who participate in an intervention for the treatment of obesity, are promising with respect to the utility of the chat app.enbook section