Bottesch, SvenTerhorst, YannikFörster, Maximilian2024-12-262024-12-262025-01-07978-0-9981331-8-8fc8e50c5-197d-4de7-94e6-8d7b19942f4fhttps://hdl.handle.net/10125/109010It is anticipated that apps based on artificial intelligence (AI) will be instrumental in mitigating the global shortage in mental healthcare. One important purpose of such apps is to encourage users’ self-help. This study is dedicated to examining the potential role of explainable AI (XAI) for mental health apps. We build on mental health literature to conceptualize potential effects of explanations in terms of patient empowerment. We implement an online experiment with a fully instantiated mental health app based on a real-world dataset. The randomized between-subject experiment is conducted with 409 participants to test the effectiveness of feature importance and counterfactual explanations on patient empowerment, intention to use, and intention to act. Our results show that the provision of counterfactual explanations alongside AI-generated predictions of depression risk in a mental health app can significantly increase users’ intention to use and empowerment.10Attribution-NonCommercial-NoDerivatives 4.0 InternationalExplainable Artificial Intelligence (XAI)digital phenotyping, explainable artificial intelligence (xai), mental health, online experiment, smart sensingConference Paper10.24251/HICSS.2025.171