Laumer, SvenHorneber, David2024-08-212024-08-212024https://dl.gi.de/handle/20.500.12116/44361Overweight and obesity are common health problems. To address these problems, mobile health technologies based on artificial intelligence (AI) have emerged. These technologies aim to encourage healthy behaviors by helping individuals monitor their exercise and dietary behavior and providing personalized recommendations to support their weight loss. Despite their potential, research has shown that users often abandon these apps prematurely. To address this, our research-in-progress investigates user resistance during the trial phase of mobile health AI-based technology adoption. We propose several factors that explain trial-period rejection, occurring when individuals either fully embrace or reject the technology. This rejection can manifest at the service, digital, or device level. By understanding these sources of resistance, we can enhance the effectiveness of mobile AI-enabled health technologies.enhttps://creativecommons.org/licenses/by-nc/4.0/mobile healthrejectiontrial periodobesityText/Workshop Paper10.18420/muc2024-mci-ws05-220