Renal clinical study participants support data sharing and use of Artificial Intelligence: clinical research
Introduction - Kidney diseases are a global health concern. Sharing data from renal clinical studies and the use of artificial intelligence (AI) can advance research in these pathologies. Understanding participant attitudes toward these practices is essential for ethical and effective implementation...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
May 2026
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| In: |
Kidney international. Reports
Year: 2026, Volume: 11, Issue: 5, Pages: 1-13 |
| ISSN: | 2468-0249 |
| DOI: | 10.1016/j.ekir.2026.106354 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.ekir.2026.106354 Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S2468024926025854 
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| Author Notes: | Verónica Aramendía-Vidaurreta, Leyre Garcia-Ruiz, Maite Aznárez-Sanado, Malene Aastrup, Michela Bozzetto, Paolo Brambilla, Rebeca Echeverria-Chasco, Esben S.S. Hansen, Larisa Micu, Jose María Mora-Gutierrez, Siria Pasini, Anish Raj, Steffen Ringgaard, Anika Strittmatter, Giulia Villa, Ioana Urdea, Gorka Bastarrika, Niels Henrik Buus, Nuria Garcia-Fernandez, Nicholas M. Selby, Matias Trillini, Susan T. Francis, Lucian-Mihai Itu, Christoffer Laustsen, Frank G. Zöllner, Anna Caroli and Maria A. Fernández-Seara |
| Summary: | Introduction - Kidney diseases are a global health concern. Sharing data from renal clinical studies and the use of artificial intelligence (AI) can advance research in these pathologies. Understanding participant attitudes toward these practices is essential for ethical and effective implementation. This study explored their perspectives using a structured survey, based on the hypothesis that participants held positive views of data sharing and AI use. - Methods - The survey was distributed to European clinical centers. It included 42 questions assessing attitudes toward data sharing, AI use, and collecting explanatory variables. Data were analyzed using descriptive statistics, Cronbach’s alpha for internal consistency, statistical tests to evaluate the effect of selected variables, regression to identify predictors of attitudes, and principal component analysis (PCA) to explore underlying factors. - Results - Participants expressed positive views about data sharing (mean score: 0.52 ± 0.24) and AI use (0.33 ± 0.24) on a normalized scale from −1 (negative) to 1 (positive). Internal consistency was high. Regression analysis identified institutional trust and family income as predictors of attitudes toward data sharing. Health status, institutional trust, and AI knowledge were predictors of attitudes toward AI, indicating that those with better health, more institutional trust, and higher AI knowledge had a more favorable view. PCA revealed 2 distinct dimensions for data sharing (benefits and concerns) and 1 for AI (concerns). - Conclusion - Renal clinical study participants generally support data sharing and AI use, although views on AI are less favorable in patients than healthy volunteers. Institutional trust shapes attitudes in both areas, highlighting the relation between both domains. |
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| Item Description: | Online verfügbar: 12. Februar 2026, Artikelversion: 21. März 2026 Gesehen am 23.04.2026 |
| Physical Description: | Online Resource |
| ISSN: | 2468-0249 |
| DOI: | 10.1016/j.ekir.2026.106354 |