Patient experiences, attitudes, and profiles regarding artificial intelligence in rheumatology: a German national cross-sectional survey study
Year: 2025
Type: article
Study design: Observational Study
Abstract: While artificial intelligence (AI) is gaining attention in rheumatology, little is known about patient perspectives. This study addresses this gap by examining patients' experiences and attitudes toward AI. A nationwide, cross-sectional, web-based survey was conducted between March and May 2025 among adult patients with rheumatic diseases in Germany. Data were analyzed descriptively and with cluster analysis. A total of 778 patients completed the survey (70.4% female, mean age 51.3 years). The most common diagnosis was rheumatoid arthritis (31.7%). While 26.8% reported current AI use for health-related purposes, 57.8% expressed interest in using it. Patients were particularly interested in AI-based symptom checkers (64.3%), therapy recommendations (50.6%), and chatbots for medical inquiries (44.5%). 57.6% of patients indicated that they would welcome their rheumatologists using AI-based clinical suppport. The most frequently cited benefits of AI included improved information access (63.5%) and faster diagnosis (57.7%), while concerns centered on faulty AI (74.3%) and reduced human interaction (59.6%). Cluster analysis identified three distinct patient profiles: 'AI-savvy' (41.4%), 'AI-pragmatic' (44.8%), and 'AI-skeptical' (13.8%). Cluster membership was significantly associated with age and education, with younger patients more often belonging to the 'AI-savvy' group. Patients with rheumatic diseases showed substantial interest in AI-supported care, although actual use in medical contexts remained limited. Age and education differences highlight the need for tailored implementation strategies to ensure equitable and patient-centered adoption of AI in rheumatology.
Source: Rheumatology International
Institutions: University of Würzburg, Universitätsklinikum Würzburg, Justus-Liebig-Universität Gießen, Medizinische Hochschule Hannover, Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsklinikum Erlangen, Rheumazentrum Ruhrgebiet, Universitätsklinikum Tübingen, University of Tübingen, Jena University Hospital, Friedrich Schiller University Jena, University Medical Center Hamburg-Eppendorf, Nuremberg Hospital, Philipps University of Marburg
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,990
Funder: Philipps-Universität Marburg
OpenAlex ID: W4416094230
