Psychometric properties of an Iranian instrument for assessing adherence to ethical principles in the use of artificial intelligence among healthcare providers.

Abstract

Artificial Intelligence (AI) technologies, especially machine learning and deep learning, are increasingly utilized to improve diagnostic accuracy and treatment selection in healthcare. The aim of this study was to conduct psychometric properties of an instrument for assessing adherence to ethical principles in the use of AI among healthcare providers. This study was a methodological cross-sectional research study conducted in Iran in 2024. It consisted of three major steps: the construction of items, the assessment of validity utilizing face, content, and construct validity, and the evaluation of reliability through Cronbach's alpha and the interclass correlation coefficient (ICC). The exploratory factor analysis yielded six major components: Accountability, Absence of bias, Irreplaceability of human, Accuracy, transparency, accessibility, fairness, and utility of outcomes, Privacy, fairness and utility in services, and Transparency of input of data and information. The final version of the study instrument consisted of 14 items and was established as a valid and reliable tool for assessing adherence to ethical principles in the use of artificial intelligence among healthcare providers, with a Cronbach's alpha value and ICC of 0.79. Our study provided a novel instrument that can be utilized in various areas to ensure adherence to ethical standards in the use of AI among healthcare service providers. Further research is necessary to offer a more comprehensive and detailed understanding of the context.