Kowatsch, TobiasTobiasKowatschNißen, MarciaMarciaNißenShih, Chen-Hsuan IrisChen-Hsuan IrisShihRüegger, DominikDominikRüeggerVolland, DirkDirkVollandFiller, AndreasAndreasFillerKünzler, FlorianFlorianKünzlerBarata, FilipeFilipeBarataBüchter, DirkDirkBüchterBrogle, BjörnBjörnBrogleHeldt, KatrinKatrinHeldtGindrat, PaulinePaulineGindratFarpour-Lambert, NathalieNathalieFarpour-Lambertl’Allemand, DagmarDagmarl’Allemand2023-04-132023-04-132017-08-27https://www.alexandria.unisg.ch/handle/20.500.14171/102058Health professionals have limited resources and are not able to personally monitor and support patients in their everyday life. Against this background and due to the increasing number of self-service channels and digital health interventions, we investigate how text-based healthcare chatbots (THCB) can be designed to effectively support patients and health professionals in therapeutic settings beyond on-site consultations. We present an open source THCB system and how the THCP was designed for a childhood obesity intervention. Preliminary results with 15 patients indicate promising results with respect to intervention adherence (ca. 13.000 conversational turns over the course of 4 months or ca. 8 per day and patient), scalability of the THCB approach (ca. 99.5% of all conversational turns were THCB-driven) and over-average scores on perceived enjoyment and attachment bond between patient and THCB. Future work is discussed.enconference paper