In a cross-sectional survey examining perceptions of artificial intelligence in healthcare, artificial intelligence exposure was statistically associated with adoption willingness among medical PhD students through an indirect association with ethics-related appraisal. Researchers evaluated 202 medical PhD students, who represent future leaders in healthcare innovation, to investigate how familiarity and appraisal influence willingness to adopt AI tools amidst observed variability in adoption attitudes across healthcare professionals.
The statistical analysis revealed that AI exposure had a positive standardized total association of 0.537 with willingness to adopt AI, accompanied by a 95% confidence interval ranging from 0.352 to 0.696. However, when ethics-related appraisal was introduced into the model, the direct association between AI exposure and adoption willingness was not statistically significant, exhibiting a 95% confidence interval spanning -0.161 to 0.184. In contrast, the indirect association linking AI exposure to adoption willingness via ethics-related appraisal was 0.509 with a 95% confidence interval of 0.341 to 0.727, accounting for 94.79% of the total association.
To measure the constructs, the investigators utilized specific item sets across the survey sample. Willingness to adopt artificial intelligence was evaluated using three 5-point Likert items that assessed respondents’ recommendation intentions, willingness to participate, and overall optimism regarding AI-driven outcomes. Exposure to artificial intelligence was similarly determined through three items assessing participants’ familiarity with core AI concepts, practical clinical applications, and integration within medical education.
Ethics-related appraisal was quantified through four survey items designed to capture perceptions of governance adequacy, application boundaries, alignment with international standards, and legal-ethical awareness. Data were analyzed using SPSS 30.0 and SPSS Amos 30.0.
The researchers noted that while ethics-related appraisal has been recognized as an important correlate of AI adoption willingness, its indirect role between exposure and adoption willingness had previously remained underexplored in medical PhD trainees. Based on the findings within this cross-sectional sample, the study authors concluded that ethics-related appraisal is closely related to AI adoption attitudes, suggesting that enhancing real-world AI exposure in combination with structured ethics education may support more informed engagement with artificial intelligence in healthcare.
Subject of Research: Ethics-related appraisal and artificial intelligence adoption willingness among medical PhD students
Article Title: Ethics-related appraisal in AI mediating AI exposure and adoption willingness in medical PhD Students: cross-sectional study
Article References: Pang, M., Wang, H., Zhou, H., Chen, J., & Zhang, W. (2026). Ethics-related appraisal in AI mediating AI exposure and adoption willingness in medical PhD Students: cross-sectional study. BMC Medical Ethics. https://doi.org/10.1186/s12910-026-01587-0
Image Credits: AI Generated
DOI: 10.1186/s12910-026-01587-0
Keywords: artificial intelligence, medical education, PhD students, ethics appraisal, technology adoption, cross-sectional study, healthcare innovation, Ethics-related, appraisal, mediating, exposure, adoption
