An artificial intelligence-based chatbot for prostate cancer education

• Verfasst von: Görtz, Magdalena [VerfasserIn]
• Verfasst von: Baumgärtner, Kilian [VerfasserIn]
• Verfasst von: Schmid, Tamara [VerfasserIn]
• Verfasst von: Muschko, Marc [VerfasserIn]
• Verfasst von: Woessner, Philipp [VerfasserIn]
• Verfasst von: Gerlach, Axel [VerfasserIn]
• Verfasst von: Byczkowski, Michael [VerfasserIn]
• Verfasst von: Sültmann, Holger [VerfasserIn]
• Verfasst von: Duensing, Stefan [VerfasserIn]
• Verfasst von: Hohenfellner, Markus [VerfasserIn]
• Titel: An artificial intelligence-based chatbot for prostate cancer education
• Titelzusatz: design and patient evaluation study
• Verf.angabe: Magdalena Görtz, Kilian Baumgärtner, Tamara Schmid, Marc Muschko, Philipp Woessner, Axel Gerlach, Michael Byczkowski, Holger Sültmann, Stefan Duensing and Markus Hohenfellner
• E-Jahr: 2023
• Jahr: May 2, 2023
• Umfang: 11 S.
• Fussnoten: Gesehen am 12.06.2023
• Titel Quelle: Enthalten in: Digital health
• Ort Quelle: Thousand Oaks, Calif. [u.a.] : Sage, 2015
• Jahr Quelle: 2023
• Band/Heft Quelle: 9(2023), Seite 1-11
• ISSN Quelle: 2055-2076
• DOI: doi:10.1177/20552076231173304
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1848799721

Abstract

Introduction - Artificial intelligence (AI) is increasingly used in healthcare. AI-based chatbots can act as automated conversational agents, capable of promoting health and providing education at any time. The objective of this study was to develop and evaluate a user-friendly medical chatbot (prostate cancer communication assistant (PROSCA)) for provisioning patient information about early detection of prostate cancer (PC). - Methods - The chatbot was developed to provide information on prostate diseases, diagnostic tests for PC detection, stages, and treatment options. Ten men aged 49 to 81 years with suspicion of PC were enrolled in this study. Nine of ten patients used the chatbot during the evaluation period and filled out the questionnaires on usage and usability, perceived benefits, and potential for improvement. - Results - The chatbot was straightforward to use, with 78% of users not needing any assistance during usage. In total, 89% of the chatbot users in the study experienced a clear to moderate increase in knowledge about PC through the chatbot. All study participants who tested the chatbot would like to re-use a medical chatbot in the future and support the use of chatbots in the clinical routine. - Conclusions - Through the introduction of the chatbot PROSCA, we created and evaluated an innovative evidence-based health information tool in the field of PC, allowing targeted support for doctor-patient communication and offering great potential in raising awareness, patient education, and support. Our study revealed that a medical chatbot in the field of early PC detection is readily accepted and benefits patients as an additional informative tool.