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%T Fine for others but not for me: The role of perspective in patients' perception of artificial intelligence in online medical platforms %A Hudecek, Matthias %A Lermer, Eva %A Gaube, Susanne %A Cecil, Julia %A Heiss, Silke F. %A Batz, Falk %J Computers in Human Behavior: Artificial Humans %N 1 %V 2 %D 2024 %K Digital health technology; Perspective; Trust in medical services; Online medical platform; Kurzskala Technikbereitschaft (TB, technology commitment) (ZIS244, doi:10.6102/zis244); Deutsches modifiziertes Health Anxiety Inventory (MK-HAI) (ZIS71, doi:10.6102/zis71) %@ 2949-8821 %~ FDB %> https://nbn-resolving.org/urn:nbn:de:0168-ssoar-103817-3 %X In the near future, online medical platforms enabled by artificial intelligence (AI) technology will become increasingly more prevalent, allowing patients to use them directly without having to consult a human doctor. However, there is still little research from the patient's perspective on such AI-enabled tools. We, therefore, conducted a preregistered 2x3 between-subjects experiment (N = 266) to examine the influence of perspective (oneself vs. average person) and source of advice (AI vs. male physician vs. female physician) on the perception of a medical diagnosis and corresponding treatment recommendations. Results of robust ANOVAs showed a statistically significant interaction between the source of advice and perspective for all three dependent variables (i.e., evaluation of the diagnosis, evaluation of the treatment recommendation, and risk perception). People prefer the advice of human doctors to an AI when it comes to their own situation. In contrast, the participants made no differences between the sources of medical advice when it comes to assessing the situation of an average person. Our study contributes to a better understanding of the patient's perspective of modern digital health technology. As our findings suggest the perception of AI-enabled diagnostic tools is more critical when it comes to oneself, future research should examine the relevant factors that influence this perception. %C NLD %G en %9 Zeitschriftenartikel %W GESIS - http://www.gesis.org %~ SSOAR - http://www.ssoar.info