Researchers validated a Japanese version of the ATTARI-12 scale to measure medical trainees' attitudes toward AI in healthcare.
Key Details
- 1The J-ATTARI-12 scale was developed and validated based on a nationwide survey of 326 Japanese medical students and residents.
- 2The scale assesses two dimensions: 'AI anxiety and aversion' and 'AI optimism and acceptance.'
- 3Psychometric evaluation showed good validity, reliability, and model fit.
- 4The tool enables structured assessment of readiness, concerns, and acceptance of AI in medical training.
- 5J-ATTARI-12 will be used in a new 'Medicine and AI' program at Juntendo University from 2026.
- 6Published in JMIR Medical Education on January 14, 2026.
Why It Matters
Understanding medical trainees’ attitudes toward AI is critical for effective curriculum development and the responsible integration of AI into clinical practice. The J-ATTARI-12 scale provides a culturally adapted tool to identify barriers and support the future workforce in adopting AI, including in radiology.
Source
EurekAlert
Related News
•EurekAlert
USC Unveils Joint Biomedical Engineering Department Bridging Medicine, Engineering, and Imaging
USC's medical and engineering schools launch a joint biomedical engineering department to accelerate interdisciplinary research and innovation, including imaging and AI.
•EurekAlert
AI Predicts Risks for Outpatient Stem Cell Therapy in Myeloma
Researchers use machine learning to predict adverse events during stem cell therapy for multiple myeloma, improving outpatient safety.
•EurekAlert
AI-Enhanced CT Heart Fat Measurement Boosts Cardiovascular Risk Prediction
AI-derived measurement of heart fat from CT scans significantly improves long-term cardiovascular disease risk prediction.