BMC medical education · 2026
AI literacy and ethical attitudes toward AI in medical students: evidence from a structural model.
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Ülkü Hilal Hatice, Torun Fulya
Аннотация
BACKGROUND: The rapid integration of artificial intelligence (AI) into healthcare has raised ethical concerns regarding autonomy, beneficence, non-maleficence, justice, accountability, and human oversight. While AI literacy is increasingly being adopted as a fundamental competency area in medical education, there is limited empirical evidence regarding its relationship with ethical attitudes toward AI. This study was conducted to examine the relationship between AI literacy and ethical attitudes toward AI among medical students and to explore how AI literacy is associated with ethical preparedness.
METHODS: This cross-sectional correlation study was conducted with 461 medical students at a state university. Data was collected using a Demographic Information Form, AI-Literacy Scale, and AI-Ethics Scale. Descriptive statistics, independent samples t-tests, one-way ANOVA, Pearson correlation analysis, simple linear regression, and Partial Least Squares Structural Equation Modeling (PLS-SEM) were used to analyze relationships and associations between variables.
RESULTS: A significant positive correlation was found between AI literacy and ethical attitudes toward AI (r = 0.648, p < 0.001). Regression analysis showed that AI literacy was significantly associated with ethical attitudes and explained 42% of the variance (R² = 0.420). Structural model analysis confirmed a strong positive path effect (β = 0.655, p < 0.001; R² = 0.430; f² = 0.753). Students who received formal AI training achieved significantly higher scores in AI literacy and ethical attitudes, while no significant differences were observed between AI usage frequency and academic year. Although AI literacy did not differ by gender, female students reported higher ethical attitude scores.
CONCLUSIONS: AI literacy was significantly associated with medical students' ethical attitudes toward AI. No significant association was observed between frequency of AI use and ethical preparedness in the current study. These findings suggest that AI literacy should be conceptualized not only as a technical skill but as an important component associated with ethical preparedness in AI-enabled healthcare systems.
METHODS: This cross-sectional correlation study was conducted with 461 medical students at a state university. Data was collected using a Demographic Information Form, AI-Literacy Scale, and AI-Ethics Scale. Descriptive statistics, independent samples t-tests, one-way ANOVA, Pearson correlation analysis, simple linear regression, and Partial Least Squares Structural Equation Modeling (PLS-SEM) were used to analyze relationships and associations between variables.
RESULTS: A significant positive correlation was found between AI literacy and ethical attitudes toward AI (r = 0.648, p < 0.001). Regression analysis showed that AI literacy was significantly associated with ethical attitudes and explained 42% of the variance (R² = 0.420). Structural model analysis confirmed a strong positive path effect (β = 0.655, p < 0.001; R² = 0.430; f² = 0.753). Students who received formal AI training achieved significantly higher scores in AI literacy and ethical attitudes, while no significant differences were observed between AI usage frequency and academic year. Although AI literacy did not differ by gender, female students reported higher ethical attitude scores.
CONCLUSIONS: AI literacy was significantly associated with medical students' ethical attitudes toward AI. No significant association was observed between frequency of AI use and ethical preparedness in the current study. These findings suggest that AI literacy should be conceptualized not only as a technical skill but as an important component associated with ethical preparedness in AI-enabled healthcare systems.