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Renal Clinical Study Participants Support Data Sharing and Use of Artificial Intelligence
Verónica Aramendía-Vidaurreta1,2, Leyre Garcia-Ruiz1,2, Maite Aznárez-Sanado3
1Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain.
Kidney International Reports
|March 30, 2026
Summary
Participants in kidney disease studies generally support sharing clinical data and using artificial intelligence (AI). Institutional trust is a key factor influencing these positive views on data sharing and AI applications in renal research.
Area of Science:
- Nephrology
- Medical Informatics
- Bioethics
Background:
- Kidney diseases pose a significant global health challenge.
- Advancing renal research necessitates data sharing and artificial intelligence (AI) integration.
- Understanding participant perspectives is crucial for ethical implementation of these advancements.
Purpose of the Study:
- To explore European renal clinical study participant attitudes toward data sharing and AI use.
- To identify factors influencing these attitudes.
- To test the hypothesis that participants hold positive views on data sharing and AI.
Main Methods:
- A structured survey with 42 questions was administered across European clinical centers.
- Data analysis included descriptive statistics, Cronbach's alpha, statistical tests, regression, and principal component analysis (PCA).
- Exploratory variables included institutional trust, family income, health status, and AI knowledge.
Main Results:
- Participants showed positive attitudes towards data sharing (0.52 ± 0.24) and AI use (0.33 ± 0.24) on a normalized scale.
- Institutional trust and family income predicted attitudes toward data sharing.
- Health status, institutional trust, and AI knowledge predicted attitudes toward AI, with higher scores correlating with more favorable views.
Conclusions:
- Renal clinical study participants largely support data sharing and AI in research.
- Attitudes towards AI are less favorable among patients compared to healthy volunteers.
- Institutional trust is a significant predictor for both data sharing and AI attitudes, underscoring its importance in building participant confidence.
