Associations between pregnant women's attitudes toward, and literacy in, artificial intelligence, and their association with perceived influence of internet-based information on decision-making
Objective This study aimed to determine the level of perceived influence of internet-based information on decision-making among pregnant women and to examine its associations with artificial intelligence (AI) literacy and attitudes toward AI. Methods This cross-sectional study was conducted among 423 pregnant women attending a university hospital in Balikesir, Türkiye, between March and December 2025. Data were collected using a Personal Information Form, the Decision-Making Scale via Internet on Pregnancy (DMSIP), the Artificial Intelligence Literacy Scale (AILS), and the General Attitudes toward Artificial Intelligence Scale (GAAIS). Descriptive statistics, group comparisons, correlation analyses, hierarchical multiple linear regression, structural equation modeling (SEM), and mediation analysis within the SEM framework were performed. Results The mean DMSIP score was 34.39 ± 7.73. The hierarchical regression model explained 59.0% of the variance, with positive attitudes toward AI emerging as the strongest associated factor. In the structural equation model, the contextual latent composite construct representing selected sociodemographic and obstetric characteristics (SDS) showed the strongest direct association with DMSIP, followed by attitudes toward AI. AI literacy was not significantly associated with DMSIP in the structural model. Mediation analysis showed that attitudes toward AI mediated the association between AI literacy and DMSIP. Conclusion The role of AI should also be considered when examining the perceived influence of internet-based information on pregnancy-related decision-making. As AI becomes increasingly integrated into pregnancy-related information environments, the development and validation of pregnancy-specific instruments to assess AI literacy and attitudes toward AI may strengthen future research in this field.