Positive and Negative Attitudes Toward Artificial Intelligence and E-Healthy Diet Literacy Among Adults: A Partial Least Squares Structural Equation Modeling Study.

چکیده اصلی

Background/Objectives: This study aimed to examine the association between e-healthy diet literacy (e-HDL) and general attitudes toward artificial intelligence (AI) among adults. Methods: This cross-sectional study included 610 adults aged 19-64 years. Data were collected through face-to-face interviews using a questionnaire consisting of five sections, including sociodemographic characteristics, digital nutrition information practices, AI use in nutrition and dietetics, the e-Healthy Diet Literacy Questionnaire (e-HDLQ), and the General Attitudes toward Artificial Intelligence Scale (GAAIS). Descriptive statistics, validity and reliability analyses, correlation analyses, and Partial Least Squares Structural Equation Modeling (PLS-SEM) were performed. Statistical significance was accepted at p < 0.05. Results: The mean age of the participants was 33.07 ± 11.36 years, and 50.8% were female. The measurement model demonstrated acceptable reliability and convergent validity. Structural model analysis showed that positive attitudes toward AI were positively associated with e-HDL (β = 0.243, p < 0.001), whereas negative attitudes toward AI were negatively associated with e-HDL (β = -0.232, p < 0.001). Among the e-HDLQ dimensions, the strongest loading was observed for finding e-healthy diet information (β = 0.844), followed by applying e-healthy diet information (β = 0.641), digital healthy eating literacy (β = 0.636), judging e-healthy diet information (β = 0.308), and understanding e-healthy diet information (β = 0.277). Together, positive and negative attitudes toward AI explained 12.2% of the variance in e-HDL (R2 = 0.122), indicating a modest explanatory contribution. Conclusions: Positive and negative attitudes toward AI were independently associated with e-HDL among adults. Although the explained variance was modest, AI attitudes may represent one of several factors associated with digital nutrition literacy, warranting further investigation in future studies.

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