Cross-cultural adaptation and psychometric evaluation of the Japanese version of the scale for the assessment of non-experts’ AI literacy among medical trainees in a multicenter cross-sectional study
- 1Department of General Medicine, Juntendo University Faculty of Medicine
- 2School of Modern Languages and Cultures, Durham University
Abstract
This cross-sectional study aimed to develop the Japanese version of the “Scale for the assessment of non-experts’ AI literacy” (J-SNAIL) and provide its initial psychometric evidence. In 2025, after translating the SNAIL into Japanese according to an international cross-cultural adaptation guideline, we distributed the translated scale as an anonymous online self-administered questionnaire to medical students in five universities and residents in nine hospitals across Japan. We tested the questionnaire’s structural and convergent validity and internal consistency reliability. 326 participants were included in the analysis. Exploratory factor analysis led to a modified 25-item J-SNAIL comprising 3 factors, including “technical understanding,” “critical and ethical appraisal,” and “risk awareness.” Notably, the original SNAIL’s “practical application” factor was not identified; instead, “risk awareness” factor emerged, which may reflect linguistic, cultural, or educational contextual differences. The J-SNAIL total score had a significantly positive correlation with the global rating scale for measuring AI literacy, which indicated good convergent validity. Cronbach’s alpha value for the total of 25 items was 0.92, indicating good internal consistency reliability of the J-SNAIL. Future investigation of the scale may strengthen factor construction. J-SNAIL may contribute to future educational initiatives and research on AI literacy in Japan.
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BibTeX
@article{fujikawa2026crosscultural,
title = {{Cross-cultural adaptation and psychometric evaluation of the Japanese version of the scale for the assessment of non-experts’ AI literacy among medical trainees in a multicenter cross-sectional study}},
author = {Hirohisa Fujikawa and Hirotake Mori and Kayo Kondo and Yuichiro Yano and Yuji Nishizaki and Toshio Naito},
journal = {Scientific Reports},
year = {2026},
month = jul,
doi = {10.1038/s41598-026-62794-8},
url = {https://doi.org/10.1038/s41598-026-62794-8},
note = {CC BY},
}
RIS
TY - JOUR
TI - Cross-cultural adaptation and psychometric evaluation of the Japanese version of the scale for the assessment of non-experts’ AI literacy among medical trainees in a multicenter cross-sectional study
AU - Hirohisa Fujikawa
AU - Hirotake Mori
AU - Kayo Kondo
AU - Yuichiro Yano
AU - Yuji Nishizaki
AU - Toshio Naito
PY - 2026
DA - 2026/07/01
JO - Scientific Reports
DO - 10.1038/s41598-026-62794-8
UR - https://doi.org/10.1038/s41598-026-62794-8
AB - This cross-sectional study aimed to develop the Japanese version of the “Scale for the assessment of non-experts’ AI literacy” (J-SNAIL) and provide its initial psychometric evidence. In 2025, after translating the SNAIL into Japanese according to an international cross-cultural adaptation guideline, we distributed the translated scale as an anonymous online self-administered questionnaire to medical students in five universities and residents in nine hospitals across Japan. We tested the questionnaire’s structural and convergent validity and internal consistency reliability. 326 participants were included in the analysis. Exploratory factor analysis led to a modified 25-item J-SNAIL comprising 3 factors, including “technical understanding,” “critical and ethical appraisal,” and “risk awareness.” Notably, the original SNAIL’s “practical application” factor was not identified; instead, “risk awareness” factor emerged, which may reflect linguistic, cultural, or educational contextual differences. The J-SNAIL total score had a significantly positive correlation with the global rating scale for measuring AI literacy, which indicated good convergent validity. Cronbach’s alpha value for the total of 25 items was 0.92, indicating good internal consistency reliability of the J-SNAIL. Future investigation of the scale may strengthen factor construction. J-SNAIL may contribute to future educational initiatives and research on AI literacy in Japan.
SN - 2045-2322
ER -