Development and validation of the Dietitians’ Perceived Trust in Artificial Intelligence Scale: A multidimensional measure for professional practice
Abstract Aims Trust plays a critical role in the decision‐making and responsible use of artificial intelligence within professional contexts in health science. This study aimed to develop and validate a novel scale to assess dietitians' perceived trust in dialogue‐based artificial intelligence systems within professional practice. Methods A three‐phase approach was employed to develop and validate the Dietitians’ Perceived Trust in Artificial Intelligence for Professional Practice Scale. Phase I involved generating 53 items from a literature review, which were reduced to 33 items by 10 experts via the Davis technique. In Phase II, exploratory factor analysis was conducted on data from 92 participants, resulting in a 12‐item, four‐factor structure: Data Security, Professional Competence, Scientific Accuracy, and Usability. In Phase III, the psychometric properties were evaluated, and its relationship with the Artificial Intelligence Literacy Scale was examined in a sample of 190 dietitians. Results Confirmatory factor analysis confirmed model fit with all standardised loadings ranging from 0.69 to 0.89. Internal consistency was high (Cronbach's alpha = 0.89), and reliability values ranged from 0.84 to 0.94 across the factors. Test–retest reliability was supported by intraclass correlation coefficients ranging from 0.66 to 0.86. A significant correlation was observed between the total scores of the Dietitians’ Perceived Trust in Artificial Intelligence for Professional Practice Scale and the Artificial Intelligence Literacy Scale ( r s = 0.256, p < 0.001). Conclusions The Dietitians’ Perceived Trust in Artificial Intelligence for Professional Practice Scale is a valid and reliable instrument capturing multidimensional aspects of trust in artificial intelligence tools among dietitians.
Institutions
- Osmaniye Korkut Ata University (TR)
- Karamanoğlu Mehmetbey University (TR)
- Istanbul Medeniyet University (TR)
Publication Details
- Journal
- Nutrition & Dietetics
- Published
- 2026-05-19
- DOI
- https://doi.org/10.1111/1747-0080.70081
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00