Patient experiences, attitudes, and profiles regarding artificial intelligence in rheumatology: a German national cross-sectional survey study

Labinsky H, Klemm P, Graalmann L, Thiele T, Hornig J, Fink D, Morf H, Mucke J, Kiltz U, Pecher AC, Pfeil A, Elling-Audersch C, Bendzuck G, Krusche M, Hueber A, Knitza J (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Rheumatology International Springer Verlag (Germany)

Book Volume: 45

Article Number: 269

Journal Issue: 12

DOI: 10.1007/s00296-025-06023-x

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.

Authors with CRIS profile

Harriet Morf Department of Medicine 3 – Rheumatology and Immunology Axel Hueber Department of Medicine 3 – Rheumatology and Immunology

Involved external institutions

Deutsche Rheuma-Liga Bundesverband e.V. DE Germany (DE) Universitätsklinikum Hamburg-Eppendorf (UKE) DE Germany (DE) Philipps-Universität Marburg DE Germany (DE) Universitätsklinikum Würzburg DE Germany (DE) Justus-Liebig-Universität Gießen DE Germany (DE) Medizinische Hochschule Hannover (MHH) / Hannover Medical School DE Germany (DE) Rheumazentrum Mittelhessen DE Germany (DE) Rheumazentrum Ruhrgebiet DE Germany (DE) Universitätsklinikum Tübingen DE Germany (DE) Friedrich-Schiller-Universität Jena DE Germany (DE)

How to cite

APA:

Labinsky, H., Klemm, P., Graalmann, L., Thiele, T., Hornig, J., Fink, D.,... Knitza, J. (2025). Patient experiences, attitudes, and profiles regarding artificial intelligence in rheumatology: a German national cross-sectional survey study. Rheumatology International, 45(12). https://doi.org/10.1007/s00296-025-06023-x

MLA:

Labinsky, Hannah, et al. "Patient experiences, attitudes, and profiles regarding artificial intelligence in rheumatology: a German national cross-sectional survey study." Rheumatology International 45.12 (2025).

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