Work

Development and validation of the Dietitians’ Perceived Trust in Artificial Intelligence Scale: A multidimensional measure for professional practice

Year: 2026

Type: article

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.

Source: Nutrition & Dietetics

DOI: 10.1111/1747-0080.70081

Authors: Tuba Nur Yıldız Kopuz, Mehmet Haydaroğlu, Kübra Uçar Baş

Institutions: Karamanoğlu Mehmetbey University, Istanbul Medeniyet University, Osmaniye Korkut Ata University

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $2,780