Evaluation of health professionals' perceptions on the use of artificial intelligence in radiology: a questionnaire-based study.

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Abstract

Artificial intelligence has become an integral part of modern radiology, improving diagnostic accuracy, workflow efficiency, and decision-making processes. However, the acceptance and effective use of artificial intelligence in healthcare largely depends on healthcare professionals' perceptions and literacy regarding these technologies. The aim of this study was to develop and validate the "Perception Scale for Artificial Intelligence in Radiologic Imaging" and to examine the factors that influence healthcare professionals' perceptions of artificial intelligence in radiology. It also aimed to determine healthcare professionals' perceptions regarding the use of artificial intelligence in radiology and to examine the factors that influence these perceptions, particularly the role of artificial intelligence literacy. This cross-sectional, questionnaire-based study was conducted between March and May 2025 among healthcare professionals working in public and private hospitals in Turkey. Data were collected from 425 participants using convenience sampling. The "Perception Scale for Artificial Intelligence in Radiologic Imaging" was developed for this study, and the "Artificial Intelligence Literacy Scale" was employed to test contextual validity. Validity and reliability were evaluated using Cronbach's Alpha, and analyses were performed with parametric tests in SPSS 26.0 and AMOS 24. The Perception of Artificial Intelligence in Radiologic Imaging Scale demonstrated a valid three-dimensional structure with 14 items and high reliability. The mean perception score of healthcare professionals regarding artificial intelligence in radiologic imaging was 3.14 ± 0.66 (mean ± standard deviation), indicating a moderate level of perception. A significant positive correlation was observed between artificial intelligence literacy and perception (r = 0.270, p < 0.001), while no significant differences were found across demographic variables (p > 0.05). The study highlights that healthcare professionals in Turkey hold a moderately positive perception of artificial intelligence use in radiology. Furthermore, higher artificial intelligence literacy levels are associated with more favorable perceptions. These findings emphasize the need for educational initiatives to improve artificial intelligence literacy and foster informed, confident adoption of artificial intelligence technologies in clinical radiology practice.

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