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

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.

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Publication Details

Journal
Rheumatology International
Published
2025-11-10
DOI
https://doi.org/10.1007/s00296-025-06023-x
Citations
6
Primary Topic
Rheumatoid Arthritis Research and Therapies
Type
article
Field-Weighted Citation Impact
10.01
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article

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

Uta Kiltz, Harriet Morf, D. Fink, Martin Krusche et al.
6 citations
Rheumatology International
Rheumatoid Arthritis Research and Therapies
10.01
article

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

Uta Kiltz, Harriet Morf, D. Fink, Martin Krusche, Philipp Klemm, Lukas Graalmann, Axel J. Hueber, Johanna Mücke, Ann‐Christin Pecher, Johannes Hornig, Corinna Elling-Audersch, Gerlinde Bendzuck, Johannes Knitza, Thea Thiele, Hannah Labinsky, Alexander Pfeil
article en
6 citations

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.

Rheumatology InternationalVol. 45(12)
Universität Hamburg (DE), Philipps University of Marburg (DE), Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Justus-Liebig-Universität Gießen (DE), Medizinische Hochschule Hannover (DE), Universitätsklinikum Erlangen (DE), Rheumazentrum Ruhrgebiet (DE), Nuremberg Hospital (DE), University Medical Center Hamburg-Eppendorf (DE), University Children's Hospital Tübingen (DE), Universitätsklinikum Würzburg (DE), Kerckhoff Klinik (DE), Jena University Hospital (DE), Technische Hochschule Mittelhessen (DE), Friedrich Schiller University Jena (DE)
Openalex Percentile: Top 2%
Rheumatoid Arthritis Research and Therapies
10.01
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