Artificial intelligence in adult and paediatric rheumatology practice and research: pilot results from an international survey

Ana Isabel Rebollo-Gimenez¹, Saverio La bella², Krystel Aouad³, Latika Gupta⁴, Davide Cangelosi⁵, Thomas Högle⁶, Johannes Knitza⁷, Nicolino Ruperto⁸, Vincenzo Venerito⁹, Abdellah El Maghraoui¹⁰, Alessandra Alongi¹¹, Wilson bautista molano¹², Deniz Bayraktar¹³, Thomas Davergne¹⁴, Dzifa Dey¹⁵, Ihsane Hmamouchi¹⁶, Alison Hoens¹⁷, Linda Li¹⁷, Angela Migowa¹⁸, Erin Treemarcki¹⁹, Nelly Ziade²⁰, Tue Kragstrup²¹ and Diego Benavent²², ¹Department of Rheumatology, Gregorio Marañon University Hospital, Gregorio Marañon Health Research Institute, Madrid, Spain, ²UOC Reumatologia e Malattie Autoinfiammatorie, IRCCS Istituto Giannina Gaslini, Genoa, Italy, ³Department of Rheumatology, Saint George Hospital University Medical Center, Beirut, Lebanon, ⁴School of Infection, Inflammation and Immunology, College of Medicine and Health, University of Birmingham; Royal Wolverhampton NHS Trust; Centre for Musculoskeletal Research, School of Biological Sciences, The University of Manchester, Manchester; Francis Crick Institute, London, Birmingham, UK, United Kingdom, ⁵Unità di Bioinformatica Clinica, Direzione Scientifica, IRCCS Istituto Giannina Gaslini, Genoa, Italy, ⁶Department of Rheumatology, University Hospital Lausanne (CHUV) and University of Lausanne, Lausanne, Switzerland, ⁷Institute for Digital Medicine, University Hospital Gießen-Marburg, Philipps University, Marburg, Germany, ⁸Université Milano Bicocca and Fondazione IRCSS S. Gerardo dei Tintori, Monza, Monza and Brianza, Italy, ⁹Univeristy of Bari "Aldo Moro", Italy, Bari, Bari, Italy, ¹⁰Department of Rheumatology, Military Hospital Mohammed V, Rabat, Morocco, ¹¹Università Milano Bicocca, Milano, MILAN, Italy, ¹²University Hospital Fundacion Santa Fe de Bogota, Bogota, Colombia, ¹³Department of Physiotherapy and Rehabilitation, Faculty of Health Sciences, Izmir Katip Celebi University. Arthritis Research Canada, Vancouver, British Columbia., Izmir, Turkey, ¹⁴Department of rehabilitation.Team METHODS, CRESS UMR ¹¹⁵³ – University of Paris Cité, Paris, France, ¹⁵Rheumatology Unit Department of Medicine and Therapeutics, Korle bu Teaching Hospital, University of Ghana Medical School, Accra, Ghana, ¹⁶Health Sciences Research Center (CReSS).Faculty of Medicine, International University of Rabat, Rabat, Morocco, ¹⁷Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada, ¹⁸Aga Khan University Medical College East Africa, Nairobi, Kenya, ¹⁹Department of Pediatrics, Division of Pediatric Rheumatology, University of Utah, Salt Lake City, UT, ²⁰Department of Rheumatology, Saint-Joseph University and Hotel-Dieu de France, Beirut, Lebanon, ²¹Department of Biomedicine, Aarhus University & Rheumatology Sector, Medical Diagnostic Center, Silkeborg Regional Hospital, Silkeborg, Aarhus C, Denmark, ²²Hospital Universitari de Bellvitge, Madrid, Spain

Meeting: ACR Convergence 2025

Keywords: Bioinformatics, Health Services Research, population studies, Qualitative Research

Session Information

Date: Sunday, October 26, 2025

Title: (0175–0198) Health Services Research Poster I

Session Type: Poster Session A

Session Time: 10:30AM-12:30PM

Background/Purpose: Artificial intelligence (AI) is transforming rheumatology care, with innovative tools now empowering physicians and health professionals (HPRs). Our survey examines how adult and pediatric rheumatologists, and HPRs currently perceive and utilize AI tools in rheumatology clinical and research environments, by identifying their experiences, concerns, and unmet needs.

Methods: An international, cross-continental online survey following CROSS & CHERRIES frameworks was shared in March 2025 to gather perspectives from the adult and paediatric rheumatology community. The questionnaire included 27 questions, both multiple-choice and open-ended, in four sections: sample characteristics, AI usage and applications, opinions and concerns, and expectations for AI implementation in clinical practice and research.

Results: By early May 2025, a total of 263 respondents (63.5% female) from 43 countries completed the survey, including rheumatologists, paediatric rheumatologists, and HPRs (figure 1). Median age of responders was 38 [IQR 32–48.5] years; only a minority of participants primarily worked in paediatric rheumatology (52, 19.8%), as HPRs (24, 9.1%), or mainly in research rather than clinical practice (54, 20.5%).Most respondents (220, 83.7%) reported using large language models (LLMs) for medical purposes, commonly for text editing (176, 66.9%), brainstorming (137, 52.1%), summarizing papers (133, 50.6%), and manuscript writing assistance (115, 43.7%); only 30 (11.4%) respondents had never used LLMs. Attitudes towards AI were predominantly positive, with 204 (81.4%) expressing optimism regarding AI’s efficacy and safety. However, up to 151 (58.1%) participants emphasized the need for strict AI regulation in medicine.AI literacy was highly valued, with 214 (81.6%) rating it as very or extremely important, with 92 (35.5%) having or having had subscriptions to AI models/tools. Respondents favoured LLM use for practical tasks: email drafting (191, 72.9%), copy-editing (191, 74%), generating manuscript sections (136, 51.9%), and facilitating reference access (157, 59.9%). Substantial support existed for integrating AI into peer review, assisting reviewers (118, 45%) and editors (112, 42.7%). Respondents indicated AI’s greatest future impact in research (212, 80.6%), diagnosis (183, 69.6%), and administrative tasks (177, 67.3%).Key concerns included ethical issues (176, 67.2%), lack of trust in AI-generated decisions (181, 69.1%), and insufficient training (156, 59.5%). Respondents supported AI integration into rheumatology practice, with only 5 (1.9%) not recommending AI tools to colleagues.

Conclusion: Pilot results suggest the rheumatology community is recognizing AI’s transformative potential whilst acknowledging the need for appropriate governance frameworks. AI tools are widely used and positively perceived by rheumatology and pediatric rheumatology professionals. However, concerns about ethics, trust, and training highlight the need for clear guidance and targeted education to support safe integration into clinical and research practice.

Figure 1 . Geographic distribution of survey respondents

Disclosures: A. Rebollo-Gimenez: None; S. La bella: None; K. Aouad: None; L. Gupta: None; D. Cangelosi: None; T. Högle: None; J. Knitza: GAIA, 2, Vila Health, 12,, 2; N. Ruperto: Abbvie, 2, 6, AClaris, 2, 6, AlfaSigma, 2, 6, Amgen, 2, 6, AstraZeneca, 2, 6, Aurinia, 2, 6, Boehringer-Ingelheim, 2, 6, Bristol Myers and Squibb, 2, 6, Eli Lilly, 2, 6, Galapagos, 2, 6, Genentech, 2, 6, Guidepoint, 2, 6, Idorsia, 2, 6, Janssen, 2, 6, Novartis, 2, 6, Pfizer, 2, 6, Roche, 2, 6, Sanofi, 2, 6, Takeda, 2, 6; V. Venerito: None; A. El Maghraoui: None; A. Alongi: None; W. bautista molano: None; D. Bayraktar: None; T. Davergne: None; D. Dey: None; I. Hmamouchi: None; A. Hoens: None; L. Li: None; A. Migowa: None; E. Treemarcki: None; N. Ziade: None; T. Kragstrup: None; D. Benavent: AbbVie/Abbott, 2, 6, Eli Lilly, 6, Janssen, 6, Novartis, 5, 6, Pfizer, 6, Savana, 7, UCB, 2, 6.

To cite this abstract in AMA style:

Rebollo-Gimenez A, La bella S, Aouad K, Gupta L, Cangelosi D, Högle T, Knitza J, Ruperto N, Venerito V, El Maghraoui A, Alongi A, bautista molano W, Bayraktar D, Davergne T, Dey D, Hmamouchi I, Hoens A, Li L, Migowa A, Treemarcki E, Ziade N, Kragstrup T, Benavent D. Artificial intelligence in adult and paediatric rheumatology practice and research: pilot results from an international survey [abstract]. Arthritis Rheumatol. 2025; 77 (suppl 9). https://acrabstracts.org/abstract/artificial-intelligence-in-adult-and-paediatric-rheumatology-practice-and-research-pilot-results-from-an-international-survey/. Accessed .

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