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

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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Publication Details

Journal
Nutrients
Published
2026-09-07
DOI
https://doi.org/10.3390/nu18172931
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Canan Altınsoy, Fatma Nişancı Kılınç, Çiler Özenir, Biriz Çakır et al.
Nutrients
Mobile Health and mHealth Applications
article

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

Canan Altınsoy, Fatma Nişancı Kılınç, Çiler Özenir, Biriz Çakır, Mihrican Kaçar
article en

Abstract

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.

NutrientsVol. 18(17)
Recep Tayyip Erdoğan University (TR), Erzincan Binali Yıldırım University (TR), Academy of Nutrition and Dietetics (US)
Recep Tayyip Erdogan Üniversitesi
Quality Education
Openalex Percentile: Top 6%
Mobile Health and mHealth Applications
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