Artificial Intelligence in Mental Health : A Qualitative Expert Study on Realistic Application Scenarios and Future Directions






Faculty/Professorship: Information Systems and Services  
Author(s): Reis, Lea  ; Maier, Christian  
Title of the compilation: SIGMIS-CPR '22: Proceedings of the Conference on Computers and People Research
Corporate Body: Association for Computing Machinery
Conference: SIGMIS-CPR '22: 2022 Computers and People Research Conference, June 2 - 4, 2022, Atlanta, Georgia
Publisher Information: ACM Digital Library
Year of publication: 2023
Pages: 1-9
ISBN: 978-1-4503-9231-0
Language(s): English
Remark: 
Abstract: What can we do to address the rising numbers of people suffering from mental health problems facing the lack of mental health professionals? This study uses 15 qualitative expert interviews to identify six realistic application scenarios for artificial intelligence in mental health that reduce mental health professionals' workload and improve treatment. We classify the application scenarios concerning the type of intelligence they embed (mechanical, analytical, emotional) and the type of task they support (automation, decision support, engagement) to assess their implementation readiness and success. Based on this classification, we develop four application scenarios with the potential for immediate implementation and two possible future directions. Our results contribute to the research stream of artificial intelligence in general and in mental health.
DOI: 10.1145/3510606.3550209
Peer Reviewed: Ja
International Distribution: Ja
Type: Conferenceobject
URI: https://fis.uni-bamberg.de/handle/uniba/57789
Release Date: 24. January 2023